diff --git a/.idea/workspace.xml b/.idea/workspace.xml index 8cc70ed..8672a5f 100644 --- a/.idea/workspace.xml +++ b/.idea/workspace.xml @@ -4,29 +4,22 @@ - @@ -536,6 +528,7 @@ - \ No newline at end of file diff --git a/E_Sign_Document.py b/E_Sign_Document.py index aa32d71..676615f 100644 --- a/E_Sign_Document.py +++ b/E_Sign_Document.py @@ -111,7 +111,8 @@ def Create_E_Document(diction): Verification des input acceptés """ field_list = ['token', 'file_name', 'related_collection', 'related_collection_id', - 'email_destinataire', 'source_document', 'type', 'file_cononical_name'] + 'email_destinataire', 'source_document', 'type', 'file_cononical_name', + 'class_id', 'session_d'] incom_keys = diction.keys() for val in incom_keys: @@ -177,6 +178,17 @@ def Create_E_Document(diction): new_diction['statut'] = '0' new_diction['valide'] = '1' new_diction['locked'] = "0" + if( 'class_id' in diction.keys()): + new_diction['class_id'] = diction['class_id'] + else: + new_diction['class_id'] = "" + + if ('session_d' in diction.keys()): + new_diction['session_d'] = diction['session_d'] + else: + new_diction['session_d'] = "" + + new_diction['secret_key_open'] = str(secret_key) new_diction['email_destinataire'] = str(diction['email_destinataire']) new_diction['source_document'] = str(diction['source_document']) @@ -229,7 +241,8 @@ def Create_E_Invoice(diction): Verification des input acceptés """ field_list = ['token', 'file_name', 'related_collection', 'related_collection_id', - 'email_destinataire', 'source_document', 'type', 'file_cononical_name'] + 'email_destinataire', 'source_document', 'type', 'file_cononical_name', + 'class_id', 'session_d'] incom_keys = diction.keys() for val in incom_keys: @@ -295,6 +308,17 @@ def Create_E_Invoice(diction): new_diction['statut'] = '0' new_diction['valide'] = '1' new_diction['locked'] = "0" + + if ('class_id' in diction.keys()): + new_diction['class_id'] = diction['class_id'] + else: + new_diction['class_id'] = "" + + if ('session_d' in diction.keys()): + new_diction['session_d'] = diction['session_d'] + else: + new_diction['session_d'] = "" + new_diction['secret_key_open'] = str(secret_key) new_diction['email_destinataire'] = str(diction['email_destinataire']) new_diction['source_document'] = str(diction['source_document']) @@ -920,8 +944,8 @@ def Create_E_Signature_For_E_Document(file_img=None, Folder=None, diction=None): with open(qr_code_img_file, "rb") as image2string: qr_code_converted_string = base64.b64encode(image2string.read()).decode() - - + outputFilename = "" + orig_file_name = "" """ On est sur une fonction sans token, mais pour recuperer des infos en mode connecté comme le dictionnaire je vais aller prendre le token du compte admin @@ -1314,8 +1338,38 @@ def Create_E_Signature_For_E_Document(file_img=None, Folder=None, diction=None): new_file['file_name_to_store'] = outputFilename + tab_key_word = "" + if("type" in e_document_data.keys() and e_document_data['type']) : + tab_key_word = str(tab_key_word).strip()+"," + else: + tab_key_word = "e-document," + + if ("file_cononical_name" in e_document_data.keys() and e_document_data['file_cononical_name'] ): + tab_key_word = tab_key_word +str(e_document_data['file_cononical_name']).strip() + + if ("signed_email" in e_document_data.keys() and e_document_data['signed_email'] ): + tab_key_word = tab_key_word +str(e_document_data['signed_email']).strip() + + + new_file['tab_key_word'] = tab_key_word + + tab_related_collection = [] + if ("class_id" in e_document_data.keys() and e_document_data['class_id'] ): + node_class = {} + node_class['related_collection'] = 'myclass' + node_class['related_collection_id'] = str(e_document_data['class_id']) + tab_related_collection.append(node_class) + + if ("session_d" in e_document_data.keys() and e_document_data['session_d']): + node_session = {} + node_session['related_collection'] = 'session_formation' + node_session['related_collection_id'] = str(e_document_data['session_d']) + tab_related_collection.append(node_session) + + + print(" ### new_file new_file = ", new_file) - local_status, local_retval = attached_file_mgt.Internal_Usage_Store_User_Downloaded_File(MYSY_GV.upload_folder, new_file) + local_status, local_retval = attached_file_mgt.Internal_Usage_Store_User_Downloaded_File(MYSY_GV.upload_folder, new_file, tab_related_collection) if( local_status is False ): print(" ## WARNONGGG Impossible de stocker le fichier") diff --git a/GlobalVariable.py b/GlobalVariable.py index 42a8926..482c167 100644 --- a/GlobalVariable.py +++ b/GlobalVariable.py @@ -3,6 +3,7 @@ Ce fichier contient les variables globales du systeme ''' from pymongo import MongoClient from spellchecker import SpellChecker + from nltk.stem.snowball import SnowballStemmer import spacy import logging diff --git a/Inscription_mgt.py b/Inscription_mgt.py index 09ecd90..7036867 100644 --- a/Inscription_mgt.py +++ b/Inscription_mgt.py @@ -585,7 +585,7 @@ def AddStagiairetoClass(diction): else: local_diction['tab_ue_ids'] = "" - #print(" ### Init_AcceptAttendeeInscription_For_Initial_Formation 11 local_diction = ",local_diction ) + print(" ### Init_AcceptAttendeeInscription_For_Initial_Formation 11 local_diction = ",local_diction ) local_inscription_liste_ue_status, local_inscription_liste_ue_retval = Init_AcceptAttendeeInscription_For_Initial_Formation( local_diction) @@ -6081,6 +6081,8 @@ cette fonction prend en entrée : - inscription_id - class_id +Important : on fait l'inscription que pour les UE qui sont marquées sur la session. Verifier la cohérence, que ces +UE soient bien sur la formation aussi. """ def Init_AcceptAttendeeInscription_For_Initial_Formation(diction): @@ -6145,7 +6147,7 @@ def Init_AcceptAttendeeInscription_For_Initial_Formation(diction): """ Suppression des données existe dans les collections : inscription_liste_ue et inscription_liste_ue_type_eval - pour l'inscrit et la formation conernée + pour l'inscrit et la formation concernée """ clean_inscription_liste_ue = MYSY_GV.dbname['inscription_liste_ue'].delete_many({"partner_owner_recid": str(my_partner['recid']), @@ -6167,7 +6169,7 @@ def Init_AcceptAttendeeInscription_For_Initial_Formation(diction): tab_ue_ids.append(tmp) """ - Recuperer les UE de la formation + Recuperer les UE de la promotion, en s'assurant qu'elle est bien configurée sur la formationformation """ tab_class_ue_id = [] @@ -6182,9 +6184,26 @@ def Init_AcceptAttendeeInscription_For_Initial_Formation(diction): if( "list_unite_enseignement" in New_retVal.keys() ): for local_val in New_retVal['list_unite_enseignement'] : - if( "tab_ue_ids" not in diction.keys() ): + # Verifier que l'UE est presente sur la session / promo + print(" ### local_val = ", local_val) + + print(" ### QRYY local_val = ", {"partner_owner_recid": str(my_partner['recid']), + 'valide': '1', + 'class_id': str(diction['class_id']), + 'list_unite_enseignement._id':str(local_val['_id'])}) + + is_ue_in_session = MYSY_GV.dbname['session_formation'].count_documents({"partner_owner_recid": str(my_partner['recid']), + 'valide': '1', + 'class_id': str(diction['class_id']), + 'list_unite_enseignement._id':str(local_val['_id'])}) + + print(" ## A INSCRIPTIONNN is_ue_in_session = ", is_ue_in_session) + + if( ("tab_ue_ids" not in diction.keys() or str(diction['tab_ue_ids']).strip() == "") and is_ue_in_session > 0 ): tab_class_ue_id.append(str(local_val['_id'])) + print(" ## A INSCRIPTIONNN2222 is_us_in_session = ", is_ue_in_session) + new_data = {} new_data['inscription_id'] = str(diction['inscription_id']) new_data['class_id'] = str(diction['class_id']) @@ -6203,6 +6222,7 @@ def Init_AcceptAttendeeInscription_For_Initial_Formation(diction): key_data['valide'] = "1" key_data['partner_owner_recid'] = str(my_partner['recid']) + print(" ### key_data = ", key_data) result = MYSY_GV.dbname['inscription_liste_ue'].find_one_and_update( key_data, @@ -6215,7 +6235,7 @@ def Init_AcceptAttendeeInscription_For_Initial_Formation(diction): " Impossible de valider l'inscription pour la formation initiale (2) ") return False, "Impossible de valider l'inscription pour la formation initiale (2) " - elif ("tab_ue_ids" in diction.keys() and str(local_val['_id']) in tab_ue_ids ): + elif ( "tab_ue_ids" in diction.keys() and str(diction['tab_ue_ids']).strip() != "" and str(local_val['_id']) in tab_ue_ids and is_ue_in_session > 0): print(" ### traitement inscription PARTIEL UEEE ", str(local_val['_id'])) tab_class_ue_id.append(str(local_val['_id'])) @@ -9800,6 +9820,8 @@ def Sent_Convention_Stagiaire_By_Email(tab_files, Folder, diction): "params": convention_dictionnary_data, } + orig_file_name = "" + outputFilename = "" # Verifier s'il s'agit d'un document à envoyer avec une version de pièce jointe. if ("joint_pdf" in courrier_template_data.keys() and str(courrier_template_data['joint_pdf']) == "1"): @@ -9881,6 +9903,9 @@ def Sent_Convention_Stagiaire_By_Email(tab_files, Folder, diction): new_e_document_diction['related_collection'] = "inscription" new_e_document_diction['related_collection_id'] = str(inscription_data['_id']) + new_e_document_diction['class_id'] = str(session_data['class_id']) + new_e_document_diction['session_d'] = str(session_data['_id']) + todays_date = str(date.today().strftime("%d/%m/%Y")) ts = datetime.now().timestamp() @@ -10083,6 +10108,46 @@ def Sent_Convention_Stagiaire_By_Email(tab_files, Folder, diction): mycommon.myprint( " WARNING : Impossible de logguer l'historique pour l'évènement : " + str(history_event_dict)) + if (orig_file_name and outputFilename): + new_file = {} + new_file['token'] = diction['token'] + type_document = "Convention" + + new_file['file_business_object'] = str(orig_file_name) + + new_file['file_name'] = str(orig_file_name) + new_file['status'] = "1" + new_file['type_document'] = str(type_document) + + new_file['object_owner_collection'] = "inscription" + new_file['object_owner_id'] = str(diction['inscription_id']) + + new_file['file_name_to_store'] = outputFilename + + tab_key_word = "convention," + str(class_data['external_code']) + "," + str( + session_data['code_session']) + new_file['tab_key_word'] = tab_key_word + + tab_related_collection = [] + if (class_data): + node_class = {} + node_class['related_collection'] = 'myclass' + node_class['related_collection_id'] = str(class_data['_id']) + tab_related_collection.append(node_class) + + if (session_data): + node_session = {} + node_session['related_collection'] = 'session_formation' + node_session['related_collection_id'] = str(session_data['_id']) + tab_related_collection.append(node_session) + + + # print(" ### new_file new_file = ", new_file) + local_status, local_retval = attached_file_mgt.Internal_Usage_Store_User_Downloaded_File( + MYSY_GV.upload_folder, new_file, tab_related_collection) + + if (local_status is False): + print(" ## WARINNGGG Impossible de stocker le fichier de Convocation ") return True, "L'email a été correctement envoyé " @@ -11703,14 +11768,14 @@ def Sent_Convention_Stagiaire_By_Email_By_Partner_client(tab_files_name_full_pat # Recuperation du titre de la formation - class_data = MYSY_GV.dbname['myclass'].find({'internal_url': str(session_data['class_internal_url']), + class_data = MYSY_GV.dbname['myclass'].find_one({'internal_url': str(session_data['class_internal_url']), 'valide': '1', 'partner_owner_recid': str(my_partner['recid']), 'locked': '0'}) tab_class = [] - for val in class_data: - tab_class.append(val['_id']) + if class_data: + tab_class.append(class_data['_id']) # Recuperer les données du client client_data = MYSY_GV.dbname['partner_client'].find_one({'_id':ObjectId(str(diction['partner_client_id'])), @@ -11748,6 +11813,8 @@ def Sent_Convention_Stagiaire_By_Email_By_Partner_client(tab_files_name_full_pat "params": convention_dictionnary_data, } + outputFilename = "" + orig_file_name = "" # --- sujetHtml = "" # Verifier s'il s'agit d'un document à envoyer avec une version de pièce jointe. @@ -11834,6 +11901,9 @@ def Sent_Convention_Stagiaire_By_Email_By_Partner_client(tab_files_name_full_pat new_e_document_diction['related_collection'] = "partner_client" new_e_document_diction['related_collection_id'] = str(client_data['_id']) + new_e_document_diction['class_id'] = str(session_data['class_id']) + new_e_document_diction['session_d'] = str(session_data['_id']) + todays_date = str(date.today().strftime("%d/%m/%Y")) ts = datetime.now().timestamp() ts = str(ts).replace(".", "").replace(",", "")[-2:] @@ -12033,7 +12103,6 @@ def Sent_Convention_Stagiaire_By_Email_By_Partner_client(tab_files_name_full_pat diction['partner_client_id'])}) for inscription in inscription_data: - # Pour la collection inscription history_event_dict = {} history_event_dict['token'] = diction['token'] @@ -12080,9 +12149,72 @@ def Sent_Convention_Stagiaire_By_Email_By_Partner_client(tab_files_name_full_pat mycommon.myprint( " WARNING : Impossible de logguer l'historique pour l'évènement : " + str(history_event_dict)) + + """ + On va aller stocker le document + """ + # Recuperation des données du stagiaire + inscription_data = MYSY_GV.dbname['inscription'].find({'session_id': str(diction['session_id']), + 'status': '1', + 'partner_owner_recid': str(my_partner['recid']), + 'client_rattachement_id': str( + diction['partner_client_id'])}) + + if (orig_file_name and outputFilename): + new_file = {} + new_file['token'] = diction['token'] + type_document = "Convention" + + new_file['file_business_object'] = str(orig_file_name) + + new_file['file_name'] = str(orig_file_name) + new_file['status'] = "1" + new_file['type_document'] = str(type_document) + + new_file['object_owner_collection'] = "partner_client" + new_file['object_owner_id'] = str(diction['partner_client_id']) + + new_file['file_name_to_store'] = outputFilename + + tab_key_word = "convention," + str(class_data['external_code']) + "," + str( + session_data['code_session']) + new_file['tab_key_word'] = tab_key_word + + tab_related_collection = [] + if (class_data): + node_class = {} + node_class['related_collection'] = 'myclass' + node_class['related_collection_id'] = str(class_data['_id']) + tab_related_collection.append(node_class) + + if (session_data): + node_session = {} + node_session['related_collection'] = 'session_formation' + node_session['related_collection_id'] = str(session_data['_id']) + tab_related_collection.append(node_session) + + if (inscription_data): + node_inscrit = {} + node_inscrit['related_collection'] = 'inscription' + + tab_inscrit = [] + for local_inscrit in inscription_data: + tab_inscrit.append(str(local_inscrit['_id'])) + + node_inscrit['related_collection_id'] = tab_inscrit + tab_related_collection.append(node_inscrit) + + # print(" ### new_file new_file = ", new_file) + local_status, local_retval = attached_file_mgt.Internal_Usage_Store_User_Downloaded_File( + MYSY_GV.upload_folder, new_file, tab_related_collection) + + if (local_status is False): + print(" ## WARINNGGG Impossible de stocker le fichier de Convocation ") + + """ - Gestion des emails via mail_queu et internal email - """ + Gestion des emails via mail_queu et internal email + """ # Recuperation des donnes smtp (local_stpm_status, local_SMTP_COUNT_smtpsrv, local_own_smtp_value, local_SMTP_COUNT_password, local_SMTP_COUNT_user, local_SMTP_COUNT_From_User, diff --git a/Job_Cron_Common.py b/Job_Cron_Common.py index 2dc8a6b..39a9eb7 100644 --- a/Job_Cron_Common.py +++ b/Job_Cron_Common.py @@ -225,7 +225,7 @@ def Prepare_and_Send_Convocation_From_Session_By_Email(tab_files, Folder, dictio else: print(" EMAIL DE CONVOCATION DEJA ENVOYEEEE ") - return True, " Les convocations ont été correctement envoyées par emails" + return True, " Les convocations ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -2050,7 +2050,7 @@ def Cron_Send_Attestation_From_Session_By_Email_for_not_sent(Folder, diction): return False, " L'identifiant de la session est invalide " is_warning_message = "0" - warning_message = "Les attestation ont été correctement envoyées par emails avec l'attention suivante : " + warning_message = "Les attestation ont été correctement envoyées par email avec l'attention suivante : " for attestation_formation_data in MYSY_GV.dbname['attestation_formation'].find({"session_id":str(diction['session_id']), 'partner_owner_recid':str(my_partner['recid']), @@ -2132,7 +2132,7 @@ def Cron_Send_Attestation_From_Session_By_Email_for_not_sent(Folder, diction): if (is_warning_message == "1"): return True, str(warning_message) - return True, " Les attestation ont été correctement envoyées par emails" + return True, " Les attestation ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -3045,7 +3045,7 @@ def Cron_Send_Emargement_By_Date_By_Email_for_not_sent(Folder, diction): tab_emargement_ids = [] is_warning_message = "0" - warning_message = "Les demandes d'émargement ont été correctement envoyées par emails avec l'attention suivante : " + warning_message = "Les demandes d'émargement ont été correctement envoyées par email avec l'attention suivante : " # Recuperer la liste des emargement à envoyer pour le jour = str(todays_date) @@ -3076,7 +3076,7 @@ def Cron_Send_Emargement_By_Date_By_Email_for_not_sent(Folder, diction): if (is_warning_message == "1"): return True, str(warning_message), str(len(tab_emargement_ids)) - return True, "Les demandes d'émargement envoyées par emails", str(len(tab_emargement_ids)) + return True, "Les demandes d'émargement envoyées par email", str(len(tab_emargement_ids)) except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() diff --git a/Log/log_file.log b/Log/log_file.log index 1ba16f6..367a30d 100644 --- a/Log/log_file.log +++ b/Log/log_file.log @@ -28829,3 +28829,36124 @@ INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 12:21:54] "POST /myclass/api/Get_List_U INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 12:21:54] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - INFO:root:2025-11-04 12:22:00.011657 : Security check : IP adresse '127.0.0.1' connected INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 12:22:00] "POST /myclass/api/Get_Action_Historique_List/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\main.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-04 17:28:09.803301 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-04 17:28:09.803301 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-04 17:28:09.803301 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-04 17:28:09.803301 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-04 17:28:09.803301 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-04 17:28:16.335211 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-04 17:28:16.335211 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-04 17:28:16.335211 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-04 17:28:16.335211 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-04 17:28:16.335211 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-04 17:38:36.055821 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:38:36.058838 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:38:36.061840 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:38:36.068356 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:38:36.074360 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:38:36.082355 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:38:36.095354 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:38:36.099372 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:38:36.105354 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:38:36.118358 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:38:36.128381 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:38:36.140355 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:36] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:38:37] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:50.621376 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:50.625378 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:50.627376 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:50.632383 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:50.636378 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:50] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:50.645384 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:50] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:50.656920 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:50] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:50] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:50] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:50] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:50] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:52.721982 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:52.724957 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:52] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:53] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:57.558197 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.560196 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:57.568204 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.570228 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:57.580711 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:57.621316 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.625338 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.628320 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.632880 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.638891 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.643872 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:57.660863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:39:57.664862 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/getRecodedStagiaireImage_from_front/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:57.684836 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:39:57.709282 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:57] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:59] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:39:59] "POST /myclass/api/Get_Statgaire_List_Partner_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:01.187418 : GetAttendeeDetail_perSession - Données d'inscription incohérentes. il y a plus d'une inscription pour les critère {'session_id': '68e419c2e5fea6f5328c2007', 'email': 'mysy1000formation+04@gmail.com'} +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:01] "POST /myclass/api/GetAttendeeDetail_perSession/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:04.127437 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:04.131450 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:04.134450 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:04.137978 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:04] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:04] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:04] "POST /myclass/api/Get_Inscrit_List_EU/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:04] "POST /myclass/api/Get_Inscrit_List_EU_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:05.052554 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:05.055555 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:05.059615 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:05.064582 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:05.068586 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:05] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:05.074148 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:05.080696 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:05] "POST /myclass/api/getRecodedStagiaireImage_from_front/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:05] "POST /myclass/api/GetAttendeeDetail_perSession/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:05] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:05] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:05] "POST /myclass/api/Get_List_Participant_Notes/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:05] "POST /myclass/api/Get_List_Jury_Soutenenace_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:19.798883 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:19.800883 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:19.804882 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:19.809882 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:19] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:19] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:19] "POST /myclass/api/Get_Inscrit_List_EU/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:19] "POST /myclass/api/Get_Inscrit_List_EU_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:20.730276 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:20.735276 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:20.739274 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:20] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:20.749290 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:20.755329 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:20] "POST /myclass/api/GetAttendeeDetail_perSession/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:20] "POST /myclass/api/getRecodedStagiaireImage_from_front/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:20.764291 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:20.769289 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:20] "POST /myclass/api/Get_List_Participant_Notes/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:20] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:20] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:20] "POST /myclass/api/Get_List_Jury_Soutenenace_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.534920 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.538915 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.543914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.552426 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.562430 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.588430 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.591431 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.594429 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.599427 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.604435 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.612461 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.625959 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.632957 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.636966 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.643967 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.649476 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.668497 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:26.676528 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Given_Apprenant_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:26.688529 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Apprenant_Recorded_Image_from_front/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_List_Partner_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:26] "POST /myclass/api/Get_Apprenant_List_Inscription/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:27] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:28] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:36.344972 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Update_Apprenant/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:36.441494 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:36.443987 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:36.446995 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:36.453001 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:36.454018 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:36.462526 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Get_Apprenant_Recorded_Image_from_front/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Get_Given_Apprenant_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:36.485559 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Get_List_Suivi_Pedagogique_No_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Get_List_Apprenant_Notes_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Get_List_Partner_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:36] "POST /myclass/api/Get_Apprenant_List_Inscription/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:49.479514 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:49.482628 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:49.487046 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:49.492059 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:49.496061 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:49.503059 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:40:49.507059 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:49.514062 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:49.527062 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:49.533062 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:49.554099 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:40:49.571090 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:49] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:40:51] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:16.840240 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:16.845249 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:16.848251 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:16.853248 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:16.857248 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:16] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:16.863836 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:16] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:16.868803 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:16] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:16] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:16] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:16] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:16] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:19.279536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:19.283539 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:19] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:19] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:24.520500 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:24.523501 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:24.527501 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:24.529502 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:24] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:24.537519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:24] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:24] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:24] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:25] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:37.571617 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:41.443589 : L'utilisateur destinataire de l'email est invalide +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:41] "POST /myclass/api/AddStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:41:41.481508 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:41.485521 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:41.489506 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:41.492504 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:41:41.496503 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:41] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:41] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:41] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:41] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:41:42] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:19.527486 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:19.528525 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:19.531768 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:19.534863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:19.538913 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:19.540914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:19] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:19] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:19] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:19] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:20] "POST /myclass/api/Get_Statgaire_List_Partner_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:20] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:22.247704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:22.251686 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:22.254690 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:22.258685 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:22] "POST /myclass/api/Get_Inscrit_List_EU/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:22] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:22] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:22] "POST /myclass/api/Get_Inscrit_List_EU_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:23.304830 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:23.308811 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:23.313813 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:23.318344 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:23] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:23.326848 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:23] "POST /myclass/api/GetAttendeeDetail_perSession/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:23.334900 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:23] "POST /myclass/api/getRecodedStagiaireImage_from_front/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:23] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:23.344368 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:23] "POST /myclass/api/Get_List_Jury_Soutenenace_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:23] "POST /myclass/api/Get_List_Participant_Notes/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:23] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:30.970891 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:30] "POST /myclass/api/UpdateStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:31.127965 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:31.128966 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:31] "POST /myclass/api/GetAttendeeDetail_perSession/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:32] "POST /myclass/api/Get_Statgaire_List_Partner_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:58.866747 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:58.868748 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:42:59.540678 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:42:59.543677 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:59] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:42:59] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:00] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:43:01.640635 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:43:01.643634 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:01] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:43:02.302370 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:43:02.307362 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:02] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:02] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:03] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:43:13.055727 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:13] "POST /myclass/api/UpdateStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:43:13.185753 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:43:13.189767 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:13] "POST /myclass/api/GetAttendeeDetail_perSession/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:14] "POST /myclass/api/Get_Statgaire_List_Partner_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:43:18.178179 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:43:18.180178 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:18] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:43:18.768918 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:43:18.771892 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:18] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:19] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:43:20] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:46.103800 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:46.104800 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:46.108806 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:46.112805 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:46.119817 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:46.125224 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:46.127226 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:46.134740 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:46.143766 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:46.149775 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:46.154186 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:46.160185 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:46] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:47] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:50.831143 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:50.833918 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:50.837850 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:50.841855 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:50] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:50.848929 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:50] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:50.855968 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:50] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:50.863486 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:50] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:50] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:50] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:50] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:55.319154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:55.321175 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:55.325274 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:55.328785 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-04 17:47:55.334984 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:55] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-04 17:47:55.346084 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:55] "POST /myclass/api/Get_List_Survey_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:55] "POST /myclass/api/Get_List_Survey_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:55] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:55] "POST /myclass/api/Get_List_Specific_Survey_Internal_Code/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [04/Nov/2025 17:47:55] "POST /myclass/api/Get_List_Survey_with_filter/ HTTP/1.1" 200 - +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-06 12:32:59.977640 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-06 12:32:59.978658 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-06 12:32:59.978658 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-06 12:32:59.978658 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-06 12:32:59.981746 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-06 12:34:11.777164 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-06 12:34:11.777164 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-06 12:34:11.778176 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-06 12:34:11.778176 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-06 12:34:11.778176 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-06 12:34:11.910080 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:11.912968 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:11.915974 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:11.917974 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:12] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:12] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:12] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:12] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:15.472485 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:15.488499 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:15.510672 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:15.520670 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:15.540719 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:15] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:15.566719 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:15.604367 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:15] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:15.683369 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:15.702745 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:18.885973 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:18.892971 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:18.919183 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.287844 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.294843 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.306975 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.296573 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.308873 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.310935 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.329425 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.344767 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.345900 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.350892 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.352886 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.356643 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.362618 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.367344 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.391618 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.402308 : Get_List_Ressource_Humaine_no_filter - impossible de récupérer les données de l'utilisateur +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.422610 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.432820 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.443439 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.464738 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.501345 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.575979 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.595306 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.613148 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.619766 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.622893 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.634750 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.676510 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.686050 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.714571 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.727338 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.736989 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.756887 : Get_Partner_List_Partner_Client - impossible de récupérer les données de l'utilisateur +INFO:root:2025-11-06 12:34:20.758784 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.761808 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.769538 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.770527 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.808346 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:20.829964 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.878416 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.904650 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.915525 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.923642 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:20.942328 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:20] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:20.976489 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.985098 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.991906 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:20.992882 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:21.373281 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:21.375812 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:21] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:21] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:21] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:45.408466 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.416466 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:45.445471 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.457466 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.467478 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:root:2025-11-06 12:34:45.473251 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:45.495263 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.512286 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:45.522286 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.527098 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.550686 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:45.556679 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:45.560744 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:45.570707 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:45.576517 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:45.578469 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:45.600288 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:45.605230 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:45.609244 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:45.624403 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.640404 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:45.670613 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:45.681908 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:root:2025-11-06 12:34:45.693777 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:45.700772 : get_connected_data_from_token -'NoneType' object does not support item assignment - ERRORRRR AT Line : 605 +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:45.712772 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:root:2025-11-06 12:34:45.713816 : Check_Connexion_And_Return_Partner_Data - impossible de récupérer les données du partenaire +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:45] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:48.424387 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:48.430388 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:48.431486 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:48.435490 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:48.439488 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:48] "POST /myclass/api/get_List_domaine_formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:48] "POST /myclass/api/Get_Suggested_Fr_Cities/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:48] "POST /myclass/api/Get_Suggested_Word/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/get_all_class/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.368022 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.381029 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.392578 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.417586 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.455271 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.477310 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.492979 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.519976 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.541097 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.564838 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:49] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:49.598914 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.606926 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.620009 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.632636 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.652206 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:49.676305 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:50.061607 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:50.068606 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:50.073617 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:50.087189 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:50.097211 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:50.139087 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:50.150116 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:50.165109 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:50.175337 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:50.189995 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:50.197002 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:50.206975 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:50.230010 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:50.244029 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:50] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:51.791508 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:51.796627 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:51.799621 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:51.803560 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:51] "POST /myclass/api/get_List_domaine_formation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:51.905152 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/Get_Suggested_Fr_Cities/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/Get_Suggested_Word/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/get_all_class/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.530243 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.538272 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.547264 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.558795 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.575801 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.593448 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.604460 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.619475 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.648213 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.655230 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.687173 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.703595 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.705587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.716474 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.718532 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.721475 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.727475 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.735482 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.738593 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.753547 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.758476 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.760478 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.766478 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.771544 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.778544 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.782743 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.786158 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.790165 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:52.794731 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:52.797717 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:52] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:55.221805 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:55] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:56.216585 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.221590 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.230697 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.245688 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:56.268691 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.285714 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.292714 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:56.299529 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:56.321619 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.328562 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.345518 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:56.356517 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:56] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:59.197506 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:59.204551 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:59.212244 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:59.224340 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:59.236420 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:59.249429 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:59.263092 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:59.269173 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:34:59.280171 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:59.291081 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:59.304180 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:34:59.333390 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:34:59] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:02.704535 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:02.708402 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:02.716614 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:02.727646 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:02.737636 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:02.748870 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:02.762475 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:02.777492 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:02.801646 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:02] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:09.724085 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:09.728599 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:09.732708 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:09.743290 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:09.752277 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:09] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:09] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:09] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:09] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:10] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.667194 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.673295 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.684581 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.709689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.719792 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.785697 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.795929 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.805491 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.814676 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.833340 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.852394 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.860411 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.871409 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.880424 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.906390 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:35:55.916509 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:35:55.953744 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:55] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:56] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:56] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:35:59] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:08.222623 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:08.234723 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:08.267050 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:08.295152 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:08.320897 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:08.337891 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:08.357021 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:08.373431 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:08.396384 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:08] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:11.065084 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:11.069943 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:11.073955 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:11.084680 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:36:11.090679 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:11] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:11] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:11] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:11] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:11] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:14.099916 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:14] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:36:32.157715 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:36:32] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.545705 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.553705 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.580714 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.597862 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.614389 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.635391 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.641997 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.656017 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.677572 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.703561 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.731579 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.751914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.774919 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.787902 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.808005 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.823900 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.841907 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.858766 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.891153 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.905159 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.917155 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.933167 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:37:57.945695 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:37:57.977060 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:57] "POST /myclass/api/Get_List_Class_Niveau_Formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:37:58] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.379370 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:00.397540 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.413539 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:00.427560 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.446113 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.468697 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.489691 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.506705 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.520687 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.539736 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.558281 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.589296 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:00.606844 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:00.615652 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:00.626649 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_Given_Class_List_Default_Documents/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:18.438115 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:18] "POST /myclass/api/Update_Class_Default_Document/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:22.843338 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:22] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:33.206543 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:33] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.266847 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.274358 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.278357 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.298359 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.319366 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.378904 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.384908 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.391910 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.415916 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.417923 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.431444 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.439452 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.456975 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.467985 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:40.480156 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.493149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:40.507148 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:40] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:42] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:46.496244 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:46.501776 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:46.506876 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:46.509778 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:46.530791 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:38:46.534796 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:46.553999 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:46.570513 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:46.582507 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:46] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:48.734196 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:48] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:38:56.615646 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:38:56] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:08.726200 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:08.732213 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:08.739216 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:08.746735 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:08.760756 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:08.774440 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:08.783970 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:08.797118 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:08.805116 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:08.816109 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:08.826131 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:08.844655 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:08] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:09] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:11] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:13.471852 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:13.482887 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:13.492894 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:13.507464 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:13] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:13] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:13.526442 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:13] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:13.538455 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:13] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:13.555464 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:13] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:13] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:13] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:17.155835 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:17.165387 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:19] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:39:24.742647 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:39:24.750646 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:24] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:39:24] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:38.451103 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:38.454103 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:38.460112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:38.472102 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:38.485102 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:38.502110 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:38.518146 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:38.532148 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:38.545152 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:38.557152 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:38.566151 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:38.573148 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:38] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:39.846909 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:39.857533 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:39.872171 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:39.886828 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:39.902734 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:39.924370 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:39.937869 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:39.941986 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:39.952990 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:39] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:45:39.985166 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:40.002719 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:45:40.020813 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:40] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:40] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:40] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:40] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:41] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:45:42] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:48:20.343852 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:48:20.351852 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:48:20.359366 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:48:20.370391 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:48:20.380921 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:48:20.394922 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:48:20.408934 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:48:20.416923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:48:20.427922 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:48:20.434923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:48:20.457922 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:48:20.470929 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:20] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:21] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:48:22] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:13.369515 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:13.376512 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:13.385520 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:13.393520 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:13.403519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:13.408520 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:13.426255 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:13.439822 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:13.457827 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:13.471860 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:13.478858 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:13.505862 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:13] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:14] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:15] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.426259 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.436251 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.439250 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.444257 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.480783 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.504307 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.510317 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.516295 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.527325 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.538297 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.557298 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.574298 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.585305 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.596861 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.604864 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:26.625910 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:26.630915 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:26] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:27] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:28] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:47.704245 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:47.708369 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:47.714771 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:47.718782 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:47] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:47] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:47.728090 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:47.732087 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:47] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:47.738087 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:47] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:47] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:47] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:47] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:50.967314 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:50.972071 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:50] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:52] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:49:53.817704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:53.821718 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:53.825073 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:53.828085 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:49:53.832087 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:53] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:53] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:53] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:54] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:49:54] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:14.230094 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:14] "POST /myclass/api/Get_Session_Nb_Sequence/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:23.853260 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:23] "POST /myclass/api/Decale_Session_Sequence_X_days/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:24.060563 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:24] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:27.032292 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:27.039399 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:27.043292 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:27.049706 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:27.052706 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:27] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:27] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:27] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:27.062444 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:27.068377 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:27] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:27] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:27] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:27] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:33.046080 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:33.049079 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:33.053598 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:50:33.057487 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:33] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:33.062285 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:33] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:33] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:33] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:33] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:36.074164 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:36] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:50:38.356966 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:50:38] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:10.967912 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:10.974926 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:10] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:10.989922 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:10.998924 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:11.008921 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:11.052228 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:11.061238 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:11.070756 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:11.080754 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:11.088756 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:11.098755 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:11.112756 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:11.138754 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:11.141757 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:11.152754 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:52:11.169283 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:52:11.187328 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:11] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:52:12] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:53:42.113984 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:42.118982 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:42.126209 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:42.134218 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:42] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:42] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:42] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:53:42.161864 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:42.168877 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:42.177870 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:42] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:42] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:42] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:42] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:53:44.961805 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:44.966804 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:44.972806 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:44.983339 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:53:44.989860 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:44] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:45] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:45] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:45] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:45] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:53:50.100412 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:50] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:53:52.436587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:53:52] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:07.910414 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:07.919252 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:07.926505 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:07.934413 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:07.940515 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:07] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:07] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:07] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:08] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:08] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.413073 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:36.419598 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:36.425601 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:36.432776 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.457864 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.551584 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:36.558101 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:36.562099 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.580113 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.590629 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.606160 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.618163 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.631158 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:36.644175 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.666297 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:36.697274 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:36.714273 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:36] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:37] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:38] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:40.023860 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:40.028436 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:40.031678 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:40.036319 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:40.042401 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:40] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:40] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:40.050800 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:40] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:40.057936 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:40] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:40] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:40] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:57.327580 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:57.333714 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:57.336154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:57.338162 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:54:57.344165 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:57] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:57] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:57] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:57] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:57] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:54:59.456353 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:54:59] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:55:01.804124 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:55:01] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:07.991844 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:07.994843 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:07.999845 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:08.006852 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:08] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:08.027892 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:08] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:08] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:08] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:08] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:15.699119 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:15] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:18.290235 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:18] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:21.932325 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:21] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.042684 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.045527 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.049348 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.054359 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.058821 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.063938 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.071349 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.090953 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.097461 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.104839 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.109836 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.124837 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.136809 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.141807 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.152806 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:49.162805 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:49.193689 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:49] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:50] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:54.535306 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:54.539836 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:54.542905 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:54.546531 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:54] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:54.555530 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:54.559532 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:54.563531 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:54] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:54] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:54] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:56.865880 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:56.868890 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:56.874125 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:56.878205 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:56:56.883196 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:56] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:56] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:56] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:57] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:57] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:56:59.542177 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:56:59] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:57:02.146746 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:57:02] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:58:33.064341 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:58:33.072338 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:58:33.078851 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:33] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:58:33.093860 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:58:33.103857 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:33] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:33] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:33] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:33] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:58:51.854856 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:51] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:58:58.315169 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:58:58.318400 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:58] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:58:58] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:59:16.704182 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:59:16.711182 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:59:16.722187 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:16] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:59:16.733191 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:59:16.743194 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:16] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:16] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:16] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:17] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:59:47.272638 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:59:47.279645 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:59:47.287645 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 12:59:47.295869 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:47] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 12:59:47.306879 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:47] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:47] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:47] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 12:59:47] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:06.706825 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:06.716845 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:06.723920 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:06.728917 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:06.735918 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:06.742918 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:06] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:06.749917 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:06] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:06] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:06] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:06] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:10.422178 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:10.426564 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:10.432565 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:10] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:10.446319 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:10.460587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:10] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:10] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:10] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:10] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:15.512124 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:15] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:17.512292 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:17.516282 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:17] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:17] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:00:20.054646 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:00:20.058167 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:20] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:00:20] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:07.601808 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.608336 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.615330 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:07.627330 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.643364 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:07.686515 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.693019 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.702620 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:07.720148 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.723147 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.732669 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:07.748666 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:07.768675 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.775665 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:07.803680 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.812223 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:07.833200 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:07] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:08] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:09] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:18.171085 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:18.177107 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:18.180104 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:18.191718 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:18.194618 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:18.202618 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:18] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:18.211725 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:18] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:18] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:18] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:18] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:18] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:18] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:22.055668 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:22.059015 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:22.062243 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:22.065616 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:22.069616 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:22] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:22] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:22] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:22] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:22] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:24.623681 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:24] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:27.918237 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:27.921237 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:27] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:27] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:02:32.142348 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:02:32.148977 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:32] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:02:32] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.529806 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.536805 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.552807 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.559808 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.571811 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.616325 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.623328 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.632328 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.639324 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.647322 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.652727 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.673435 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.693445 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.698442 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.719444 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:18.733444 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:18.745446 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:18] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:19] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:20] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:32.506347 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:32.513347 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:32.531871 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:32.567873 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:32.569874 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:32.576891 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:32.588427 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:32.598423 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:32.604419 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:32.627423 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:32.636457 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:32.654426 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:32] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:33] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:34] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:38.143938 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:38.154512 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:38.156213 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:38.160689 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:38] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:38.167697 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:38] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:38.174100 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:38] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:38.184525 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:38] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:38] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:38] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:38] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:42.178416 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:42.181427 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:42.184091 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:42.188616 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:42.190620 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:42] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:42] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:42] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:42] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:42] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:44.898147 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:44] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:46.875581 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:46.879711 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:46] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:46] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:03:48.615047 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:03:48.620111 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:48] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:03:48] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:45.036710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.046708 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:45.059706 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.070706 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.085708 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:45.128232 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.133735 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.143748 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:45.160746 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.163748 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:45.179749 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.190749 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:45.207755 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:45.224762 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.235285 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.242283 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:45.251818 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:45] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:46] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:47] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:50.997961 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:51.003891 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:51.005441 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:51.019645 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:51.022635 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:51.038650 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:51.050185 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:51] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:51] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:53.735371 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:53.737736 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:53.740863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:53.745865 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:53.747862 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:53] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:53] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:53] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:53] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:53] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:55.868020 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:55] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:04:58.827532 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:04:58.832529 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:58] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:04:58] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:01.162458 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:01.168458 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:01] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:01] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:04.210532 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:04.213051 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:04] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:04] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:06.321582 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:06.328008 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:06] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:06] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:35.226713 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:35.229151 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:35.231601 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:35.236109 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:35.237111 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:35.240280 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:35.242291 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:35.252043 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:35.261146 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:35.268452 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:35.277431 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:35.282935 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:35] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:36] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:38.017536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:38.022612 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:38.023013 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:38.028077 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:38.032078 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:38] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:38.039822 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:38] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:38] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:38.044832 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:38] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:38] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:38] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:38] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:39.883753 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:39.889640 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:39] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:41] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:47.502814 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:47.516937 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:47] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:47] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:49.532052 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:49.542080 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:49] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:49] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:51.509468 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:51.517144 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:51] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:51] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:05:53.127891 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:05:53.131902 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:53] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:05:53] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:06:28.922509 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:06:28.932523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:06:28.942631 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:06:28] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:06:28.960048 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:06:28.969051 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:06:28] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:06:28] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:06:29] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:06:29] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:07:07.509952 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:07:07.516953 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:07:07.524951 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:07:07.535955 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:07] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:07:07.554963 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:07] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:07] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:07] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:07] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:07:45.387881 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:07:45.394986 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:07:45.401981 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:07:45.412994 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:07:45.420903 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:45] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:45] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:45] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:45] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:07:45] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:15.853447 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:15] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:26.219273 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.225274 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.231501 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.241509 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:26.253032 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.257038 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:26.283589 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.293590 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:26.310601 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.318599 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.334150 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:26.337111 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:26] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:27] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:29.565639 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:29.580650 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:29.601199 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:29.616305 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:29.628207 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:29.642318 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:29.656223 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:29] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:30.513447 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:30.519457 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:30.525451 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:30.533448 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:30.546448 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:30.555540 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:30.577463 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:30.580457 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:30.594006 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:30.598998 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:30.616999 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:30.656007 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:30] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:32] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:32.251868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:32.261402 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:32.266993 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:32.282629 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:32.295715 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:32] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:32] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:32] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:32] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:32] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:33] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:34.856403 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:34] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:36.717259 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:36.724386 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:36] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:36] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:08:40.173159 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:08:40.178156 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:40] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:08:40] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:09:09.288818 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:09.295924 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:09.304818 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:09.313862 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:09.317917 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:09] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:09] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:09] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:09] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:09] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:09:17.890891 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:17] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:09:20.032492 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:20.038489 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:20] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:20] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:09:21.898577 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:21.904581 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:21] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:21] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:09:24.025263 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:24.031271 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:24] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:24] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:09:25.856375 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:09:25.862380 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:25] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:09:25] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:10:02.775534 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:10:02.781430 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:10:02] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:10:02] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:10:04.314224 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:10:04.316235 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:10:04] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:10:04] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:29.396317 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:29.403311 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:29.412312 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:29.421310 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:29.429311 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:29.446308 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:29.463312 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:29.479315 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:29.486351 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:29.497865 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:29.509879 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:29.536866 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:29] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.499384 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:30.503391 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:30.517392 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.531393 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:30.538393 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.559394 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.575400 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.584420 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:11:30.603981 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.619012 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.643636 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:11:30.649638 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:30] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:31] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:32] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:11:33] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:12:19.204114 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:19.208791 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:19.211890 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:19.217642 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:19.220832 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:19.222834 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:19] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:19] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:19] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:12:19.235093 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:19] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:19] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:19] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:19] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:12:21.438970 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:21.443490 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:21.447490 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:21.451488 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:21] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:12:21.457945 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:21] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:21] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:21] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:21] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:12:27.134076 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:27] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:12:28.875336 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:28.880869 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:28] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:28] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:12:34.427089 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:12:34.430682 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:34] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:12:34] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:38.302530 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:38.309536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:38.319000 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:38.327102 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:38.346000 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:38.361005 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:38.371002 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:38.378000 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:38.387110 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:38.400226 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:38.407222 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:38.420296 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:38] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:39] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:40.251112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:40.263112 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:40.280113 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:40.294120 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:40.297120 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:40.314146 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:40.321146 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:40.336147 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:40.359147 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:40.368150 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:40.378149 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:40.417671 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:40] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:41] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:54.121674 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:54.126687 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:54.130682 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:54.135203 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:54.136843 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:54] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:54.145493 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:54.148499 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:54] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:54] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:54] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:56.148868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:56.152877 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:56.157070 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:56.158073 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:13:56.162589 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:56] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:56] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:56] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:56] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:56] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:13:59.439832 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:13:59] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:01.617415 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:01.620418 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:01] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:01] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:04.411031 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:04.414341 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:04] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:04] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:33.334558 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:33] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:35.509974 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:35.515018 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:35] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:35] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.060505 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.063515 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.067687 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.074686 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.084775 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.148486 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.151591 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.155600 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.161601 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.166337 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.168493 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.172954 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.177953 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.179951 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.188438 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.192436 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.200882 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.384970 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.389452 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.393451 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.400715 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.406715 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.414891 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.423026 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.428036 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.433037 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.444401 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:39.448374 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:39.465443 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:39] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:40] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:40] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:41] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.336945 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.343939 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.359061 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.364058 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.377062 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.436360 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.441360 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.447880 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.455877 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.474877 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.483910 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.493898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.504879 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.512877 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.530947 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:47.545959 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:47.566173 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:47] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:48] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:49] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:51.381713 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:51.384715 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:51.388838 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:51.394109 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:51.397121 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:51.408128 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:51.412152 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:51] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:51] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:54.009113 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:54.012112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:54.015309 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:54.019310 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:54.024318 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:54] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:54] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:54] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:54] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:54] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:55.804775 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:55] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:14:57.550067 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:14:57.553066 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:57] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:14:57] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:00.573016 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:00.580014 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:00] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:00] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:20.793780 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:20] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:22.796537 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:22.803532 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:22] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:22] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:24.457425 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:24.461418 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:24] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:24] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:26.960523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:26.964256 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:26] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:27] "POST /myclass/api/Get_List_Survey_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:29.288821 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:29.299936 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:29.318823 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:29.327879 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:29] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:29.345636 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:29] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:29] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:29] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:30] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:31.352745 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:31] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:33.114564 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:33.121682 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:33] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:33] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:34.181387 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:34.206121 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:34.221128 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:34.251128 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:34.270251 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:34.287989 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:34.311904 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:34.337913 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:34.348805 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:34.370617 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:34.387057 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:34.407155 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:34] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:36] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:37] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:39.811217 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:39.820197 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:39.836162 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:39.855208 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:39] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:39.875800 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:39] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:39] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:39] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:39.899272 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:39.913347 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:39] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:39] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:39] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.263062 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.270159 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.281164 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.299176 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.310824 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.740393 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.746398 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.752403 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.759409 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.774409 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.776419 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.806173 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.814317 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.834313 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.841310 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:42.855315 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:42.867432 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:42] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:43.593708 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:43] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:43] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:45.158778 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:45.165898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:45] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:45] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:45] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:15:47.112984 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:15:47.118980 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:47] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:15:47] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:05.089471 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:05] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:07.042023 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:07.049038 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:07] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:07] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:30.363245 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:30.371244 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:30.389284 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:30.392241 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:30.407258 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:30.420249 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:30.434258 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:30.451304 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:30.470302 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:30.474308 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:30.487312 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:30.505835 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:30] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:31.600593 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:31.607597 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:31.614593 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:31.618594 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:31.634605 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:31.650131 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:31.675133 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:31.687130 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:16:31.695141 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:31.705139 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:31.724685 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:16:31.756737 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:31] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:32] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:33] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:16:34] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:04.846027 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:04.854029 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:04] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:04.867028 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:04.870027 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:04.879028 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:04] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:04] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:05] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:05] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:14.775812 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:14.784034 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:14.802566 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:14.832259 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:14.839465 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:14.871947 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:14.883950 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:14.904965 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:14.921507 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:14.944517 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:14.960514 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:14.980529 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:14] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:15.002523 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:15] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:15.021573 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:15.025555 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:15.038555 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:15] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:15.058558 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:15] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:15] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:16] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:17] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:49.169101 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:49.173113 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:49.175118 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:49.179547 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:49.183567 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:49.187575 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:49] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:49.200061 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:49] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:49] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:49] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:52.490677 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:52.496977 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:52.501037 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:52.507037 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:52.510036 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:52] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:52] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:52] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:52] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:52] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:55.303407 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:55] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:56.952619 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:56.957699 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:56] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:56] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:17:58.719857 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:17:58.723298 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:58] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:17:58] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:18:00.172313 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n\n\n\n\n\n\n\n\n
  
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Entre les soussignés
1)  France Active Seine et Marne Essonnes FA SME, 29 allée Jean Rostand, 91000 Évry-Courcouronnes, représenté par son président Christian Mesnier,
2)   NOM  : aaa
               PRENOM :  bbb
               ADRESSE :      
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Est conclue la convention suivante, en application de l’article\n

Article 1 : Objet  de la convention 
FA SME organisera l’action de formation suivante : « Bloc 4 Élaborer son action commercial RCNP 35215BC04 » - CONDUIRE UN PROJET 
-    Formation : CONDUIRE UN PROJET  
-    Objectif : Acquérir les connaissances et compétences de base, nécessaires au métier « d’entrepreneur» lié à la création, à la gestion et au développement de petites entreprises. 
-    Programme et méthode : joints en annexe.
-    Type d’action de formation (article D.6313-1 du code du travail modifié par la loi 2018 -771 du 5 Actions de formation
-    Date : du 10/11/2025 au 18/11/2025 
-    Durée : 15.0   heure (s)
-    Lieu :  adr site1  , cp site 1 - vile sit1 

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Article 2 : Effectif formé
France Active Seine et marne Essonne accueillera 15 personne(s)

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Article 3 : Dispositions financières
En contrepartie de cette action de formation, bbb  aaas’acquittera des coûts suivants : 
•    Frais de formation : 1500.0  € TTC

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Article 4 : Modalités de règlement
Le coût de la formation peut être réglé :
•    Par mobilisation du Compte Personnel de Formation (CPF) : via la plateforme MonCompteFormation (MCF) Le règlement est effectué directement par la Caisse des Dépôts et Consignations, conformément aux Conditions Générales d’Utilisation de MCF. La validation définitive de l’inscription est conditionnée par l’accord de financement sur la plateforme et par l’acceptation des conditions de service par le bénéficiaire.
•    Par financement personnel : Dans ce cas, le règlement est à effectuer par chèque, espèce ou virement (si paiement en une seule fois), à réception de la facture émise par FASME. Le paiement devra être intégralement effectué avant l’entrée en formation, sauf accord particulier formalisé entre les parties. La validation définitive de l’inscription est subordonnée à la réception du paiement ou à la signature d’un échéancier de paiement.

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Article 5 : Dédit ou abandon
Toute annulation d’inscription intervenant moins de 7 (sept) jours ouvrés avant la date de début de la formation, et en dehors du délai de rétractation, donne lieu à des frais d’annulation égaux à 100 % (cent pour cent) du prix de la formation indiquée sur la Commande.

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Article 6 : Différents éventuels
En cas de contestation, l’organisme ou les stagiaires peuvent contacter le service réclamation à l’adresse mail : formation@franceactive-seineetmarneessonne.org. Un traitement de la réclamation sera effectué dans un délai de 7 jours ouvrés. Si une contestation ou un différend ne peuvent être réglés à l’amiable, le Tribunal de Paris sera seul compétent pour régler le litige.

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Fait en double exemplaire, à Évry, le , 06/11/2025 

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Pour France Active Seine et Marne Essonne
Emmanuelle Billard, Directrice Générale

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Entre les soussignés
1)  France Active Seine et Marne Essonnes FA SME, 29 allée Jean Rostand, 91000 Évry-Courcouronnes, représenté par son président Christian Mesnier,
2)   NOM  : ccc
               PRENOM :  sss
               ADRESSE :      
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Est conclue la convention suivante, en application de l’article\n

Article 1 : Objet  de la convention 
FA SME organisera l’action de formation suivante : « Bloc 4 Élaborer son action commercial RCNP 35215BC04 » - CONDUIRE UN PROJET 
-    Formation : CONDUIRE UN PROJET  
-    Objectif : Acquérir les connaissances et compétences de base, nécessaires au métier « d’entrepreneur» lié à la création, à la gestion et au développement de petites entreprises. 
-    Programme et méthode : joints en annexe.
-    Type d’action de formation (article D.6313-1 du code du travail modifié par la loi 2018 -771 du 5 Actions de formation
-    Date : du 10/11/2025 au 18/11/2025 
-    Durée : 15.0   heure (s)
-    Lieu :  adr site1  , cp site 1 - vile sit1 

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Article 2 : Effectif formé
France Active Seine et marne Essonne accueillera 15 personne(s)

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Article 3 : Dispositions financières
En contrepartie de cette action de formation, sss  cccs’acquittera des coûts suivants : 
•    Frais de formation : 1500.0  € TTC

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Article 4 : Modalités de règlement
Le coût de la formation peut être réglé :
•    Par mobilisation du Compte Personnel de Formation (CPF) : via la plateforme MonCompteFormation (MCF) Le règlement est effectué directement par la Caisse des Dépôts et Consignations, conformément aux Conditions Générales d’Utilisation de MCF. La validation définitive de l’inscription est conditionnée par l’accord de financement sur la plateforme et par l’acceptation des conditions de service par le bénéficiaire.
•    Par financement personnel : Dans ce cas, le règlement est à effectuer par chèque, espèce ou virement (si paiement en une seule fois), à réception de la facture émise par FASME. Le paiement devra être intégralement effectué avant l’entrée en formation, sauf accord particulier formalisé entre les parties. La validation définitive de l’inscription est subordonnée à la réception du paiement ou à la signature d’un échéancier de paiement.

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Article 5 : Dédit ou abandon
Toute annulation d’inscription intervenant moins de 7 (sept) jours ouvrés avant la date de début de la formation, et en dehors du délai de rétractation, donne lieu à des frais d’annulation égaux à 100 % (cent pour cent) du prix de la formation indiquée sur la Commande.

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Article 6 : Différents éventuels
En cas de contestation, l’organisme ou les stagiaires peuvent contacter le service réclamation à l’adresse mail : formation@franceactive-seineetmarneessonne.org. Un traitement de la réclamation sera effectué dans un délai de 7 jours ouvrés. Si une contestation ou un différend ne peuvent être réglés à l’amiable, le Tribunal de Paris sera seul compétent pour régler le litige.

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Fait en double exemplaire, à Évry, le , 06/11/2025 

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Pour France Active Seine et Marne Essonne
Emmanuelle Billard, Directrice Générale

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ttx9kB7oARSbstqdiAxrubiiy9e/KDUZTFixIji29/+dvF6jWLljM4hE1onoKCVxNCJxx0/ScGtVqTRhx4WJbhrtTvVgtalVGw6paH3lNS1R+pDbRaYa6Atar11BsdrVA+6GlZefoXYa/vUkxNllZoVujSOOuqoSGijKnLkCfvvv3/xjW98o/jZz35WeSajq8iE1glQztASpSUnyXHDo4+0NKuvudrqHRq/pnKdvlnS2Z/SoCqywrLLxof/byboAhi+8y7FSccfP4lkUzX+/Nlncc6Bxv33ewER6AoZOHBgJLSzzjorxtMSDjnkkGLqqacuXnrppcozGV1FJrROwI/wwAMOiD2KZH0S6OnrdTz7jDMrzyCND4rbbh1fXHnFFcWEUrsQa+7kE0+KzeD6ObUBUYRQXElqm+UxYcKEaKkYywavvfpaVKEw0ehnP5u83Qe4alq27r7rruLKK6+IY/fKI/lYO3fdcUdU2zBoheDhisstH+cI/Ptf/4ok+2awQB3Hddde26qDRrXX5+iJaWn6vBLI9pnXX3stNpub5JRalCxcLUvXh214kBdK8J4bwvtJCHEra8G1oCHHGk4QZ9IOZrbCtddc0+pmagV7/rnnw3WqT3zNAq1uCyywQIyVvVU1ZpDLOVP4PRhhmNE9ZELrJMhVa9bWGI5E9COS8SHmaCHDhMcmFCuvsGK02jSLU+7Yfdfhxd8DqVGw1VitWdpnNGOLBZ195lnxOWqxpLtJ5OhL/P7ll0cXTEO756nIvvTi5HdylhapH83xmsM1zO8xfLeosKFUgGoF9RCvLbvU0vF9SE2sSo/jyuH//T14rbWKmaabPpDHNTHrRh7J+bJK7Z/8ESAXTeaOy3EfHlxuIM7ovc7N5whTgvM2Wcp7nf+Siy0eruXEsXkJelldky2GbR7/1iR/4nHHRRWT+eeeJ/6b9uXYqH78pIaqbbPBTYp1Nm+4XtV9uiNHjoz1aO/X6E3N6BwyoXUSMlXkghDCRx/9KloLCGvYJptG6wSBbLDeesWcs85W3HLTzTGmRjfMTMlLLrooih8efcSRUWLHSLaHHngwWj2nnXpqVKhYZsBSxeWXXlY8+cQTMWhPOYJkkB87i4c8D6KqbmwXj2PB0QD7RSC3zYcNi+oYXGMqE/6f/I/Xvnf++ZHwBq64UiC0X8XPIhuqGCP23CsORmFZcYmJNl595VXxbyoXSIXFSdEDuTjHX/z8F9FaYgUOXGnluO1HH300Cj9yIQ0Kds2WW3qZcE4vxqG/yJCqSXUxKcttgfnmLYZuOCT+fd+99xazzjhTsd7gwcXLwYrUkG8bdOLWXXudYsnFF49Tqpod48ePj4Q2dOjQyjMTscsuu0QLrZY6cEbnkAmtCzjogAMjsXDfLr/ssijYaI4lICFWkAWZ1CQeDKSFLJIg4p2BMPxtelLCmFNOjduhFptgAPJss8wcR+VxXU864cRIcIazfPy7SWcZiN3df//9USNss0CurBykSSljv2ABcJMfCK8Dkl1p+RWiy8lC+02F0Ej4fPJxy/g5U6XE2FhaZKyd57CNN4lDfa8O7ue++4yIIo+sQgSJqFmsW262eSTPDdZdP36GC/lEsE642OsE6+/SSy6J7rp9seCq41801hZaYP5i441aFr5hKa71NcFiLEN8jTqu7SDxZsfYsWMjoW233XaTxM+cx3rhhjVPsFw7Ip2e0TYyoXUBjz3ySCQfAobbbr11scA887beXZ995tlIOttvs21rgsBAXuSy1x57xL9pdtUjNPGohNPHnBbft8aqqxXbbb1NJLYdtt0uZlSrM4AmMbGmNg9kRrrH+332xhtuiJLZYnzPlSaVs6S4a4nQjNwzET3Fo8waRXJcym222iqO5nNOtvtksLB+99vfxalMhq0gK8fGajLUZN999okWmOf3G7lvMT6QqmMjUrl9OH7bMh+UG55mmiZUExphyLlmm32ycXrNRmi+D+RdD2PGjGlNCJQhPjhkyJBi5kDauUm9+8iE1gVE2erVVy/ISLNgtttmm1byQhaIAhmkhXZqsLpi0qDyYzb6zQLfdaed49/A5URorJ8EwXiksMduu7daeyynJGedoIREHE98Kk2Gop5L0lrMj7ouCw3pgcQB62iV6HJOJLTVVlk1LMoWQrPQuHTzB7KWDACEJYngWIzYA0Tef/El4nVARmkmp1kFpsdTsaW/xj3lOqf6sj9/9ue4gFl1ZVQTmilS3PX9R+0X9+/x29/+NsbWmoHQJHuQFCvrimBFp++pGgcFSxOhfa+UTAJS6msEK3f2cMPraMlPRn1kQusiTCufdqqpopw2kcQyDAMWR+LSDdlg/Sgtve5a68T4Fbzx+hvRimP9iLdZ5CZMfecb34huWoKMKAlw2zI6b9gmm0Rp68sumfgeQD5mTxrB53XurvosJDr+1ltjhnDxhReJpGLwC3dTgmDpJftHUpFZXbRfvxjjKlsZ3FXzNpWqbDJ0aIxjsUgJK7KyNlx//bg9x7fNVlvGshZxQc+T3W6xQveMi9z18rfkA8VbNXBp/mkZYm5zhvchU3B86wXicgMwf9TjhOOOj27boGC5LjT//F9q7Omiiy6KROUx11xz1SXX4cOHF1/72tci6ZXBsps/nMOywb034T2je8iE1kWYiH5+RZG1LF0NAvasK3LXpjeR3U5kBqySG66/PtZQkdqmIvvC8y8UZ5955iTlCkAvi5Ui/mbOAGL4wdsTq8wTLPwTjjsuFv4iWMkGUt1KOeCxRx6N+9p3xIjinrvvjllKcTlkIzD//UCkV1919STJBqQx4dHHomu56847R3IyYZ5Vctkll4Rj2jUeE+vSXACquo7VOZtZYEpV6k/0GdanbdiWbZbnjCY434suuCAmGxIkRJS62JfPG1IDYpimv9cadTcloG5szjnnjGQ2SyBc/54SrPFqqxNYaF//+tdjtrMMvx2Etnqw+DO6j0xoPQg/7OpsZBksq1o//lrw3ra2BQjI++qhM/srI51H9WfrHZPn6x1H+kw5MN4ReH+tY/iywJo69NBDi//3//5fzFzec889MQ4mY1kNx67W7H/+538mIzRZ6GmDS7399tu3WUjcFbC2kT2r0X6Ui6RuhGa5jo1GJrSMjC6A5bnEEktE5YzzzjsvFiCTBRo0aNBkxITEEZai2meeeabybAtYeSw7WdBGgdV9d7DC991332LuueeOGVT6a/avuNexsCRZvm0lMnojMqFlZHQB48aNi0SEKCSCAFEgEEmLauy3337RQqNUW8aNN94YXdHLSrHTtvDQQw9FN7WeheV1+3JsCy20ULHFFlvE1qrRo0cXu+++e7QivcaylIi49dZbY6KlryATWkZGJyGjvddee0Vi2GyzzWJgH8HUIzQu5xFHHBHfX22hHX/88cV0003XocZ0rVEsQJahAu9qIEey3gsuuGBxzTXXxOlf1VC6s+WWW8Z9Oh4Ep+Wtr+ArQ2iamX//ySfdmp79ox/+KGYNywN2O4zwo/bDTo8vCwYC6zH99UeTKn04Jouy3rGl41bWIZifejctRNckyeFwoW4bH7b/655TEknHUu9YexpctSShzfqBRGjUZ6trBEEMjXta3YDOLURAHalBe+KJJ+I2ZpxxxtiJUcbDDz9crLXWWsWGG25YPPvss5Vna0O3hffZlsc+++xT85h7I/o0ofnB+6IVoypRUD2v+t0C7Apk7VStK3jtLE4/bWwsVzCIV8X9LjvtVFxy0cU177SdgXPkggj4thfotfxV3pv2/nBwTcrgdiiHUM+meb0M2USlGIp+773nnmK2784clUXUnN1w3fWxpGLsaS3XxKR0RcTV228U1LRtPmyzYovw2HTjjWOhrwzolCzdYGVpVeJCnnNOS4cIcOtkO2uR+WGHHRbdvHIDuljXkksuGcmuPSCh1VZbLRIQIj399NMrr7QQLJFIMt5+7x0Bq0yZiW0Z0tJXauD6NKFdeP75sfZqrtnniEWYKtPXWn2N4uILL6q8o3M48/RxsfhVmUJnMXznXeNntSXtstPOxYDwQ1Y0O3znnTskOVQPWq2WX3qZ4sD992+X0EC5hJalatICbVczTDNtsdfuu1eeaanId8yzByK/9+67I3kedsihsbQCkJzzGFO5JvuOGBkJrtb2G4ErLteXOmPsA9XTukb413VdbZWBxU+mUIEtEkME//3f/92atXTtDz744OhyKmGphsSBz2hPS2AVDRgwoDjppJMqz9QG8uFmUrq1DY9jj20RCXBDu/fee6PVZh+dwc0331x85zvfids74YQTOvT7aXb0WUKz0FWvq54nfZO+LI3gZfPa+8456+xibFiQquqrK70fDz/YscEiI5Nz7NFHRwtt7JgxlVeL2BhtqrjnNFLXm5q+x/Dd40J/qjKujFQQi1FRapJe1sytgZ0ckXqvcixG07v6sdODJcRStHg1fas9m37qqaPVd/+998Vzk7nSbqUX1Pu1WlH6AL2eswYL66EHJ7egxFwU+660wgpx2/Dee+/FImAFuwp9dSUgq6Qscs1VV8em+tMq10StmwJawekE21Wf5lhYbu2Vn7SFq664MvaKnlGxUNSt6UCYcbrpiksuvjiGFB4O56a42f7uDt8pUlYHR/HDsafv343E8Tz22GPx/5U32MYpJ54Yrfh6GUBzAZCAYL4hJwk77rhjzCLWKr84++yz42fuumuiwgi3sV+/fm12OigPETdLRJYepLwdn/Nl5Rm4Uq9Uph6ECyQNbE9crS+gzxKaRm4tM/oY6y0g0jwayRdbaKFi6f4DotyPglDkAdddc01c4Bb0CssuV/RfbPFIQInQnnvu2agiQS6HxTXXHHMUxx97XM07XSI0Wl+AKFZcfvm4PcW0T4fntQnZH7d47mBVbrDuulFayF34iMNGx+PTAYAIL734kkBg9xaLLbxwlONxjI5FfI9G2BKLLBq3M2DJJSLBkNz54ovPo8tZj9Asjs2DW2x7yBn0hSIsVhm89eZb4Zr1i/2dzhPx1iK05HIiVm1gi4TPkAyy7TPHjYuvVcP2tGElMq2FRGga5sGi3mmHHeJ3rVD48ccmxK4I595/8Zbvy3eCjEkzcZfTudFz87pC4FdffiV+x66j72Hw2mvXdMO45mJlSEA5RDn2tffee8fMYtK+KyNZaLfffnvlmZa4V//wffqO60HMTVwuEVlyOREneSnJBoQn2N8VCyupgLAs3+kFqiXtoc8SmubnmYNrckZwE2vBj8iit9ieDz8GdUSar7lPN914Y6yetygQhsWpiVoMzOviYbDJRkMjmamm1wmwblgE5HVqVfLrx0RoiPbmm24KbueOYVszxnYmlhi5n9lnniU2ctt3tLymmSYsxmMLEj8Dllgy9o7qq/zNr38TBSQlOqh8fHf66Yvttt66ePH5F6KlQRvt0YcfidvVZsUdcx7iTDoN6hEaiOul/QKCd84C0oB8+803f7FVRQ+uHqEhMpbKWmsMig3sSJZuGUtvkWCV1FrE4nP03tYZtGZdsUOEZn/Dd9k1Xqtjjz6qmHuO2SN5IXPXhbyR75NopTYvRCoJQkZp5hlnKA4LriGwdLmrdwQL9sxxZ0QrTwzwD7//fbC8351M2ihhq0DmSIC2WYqBummaraniv1bnwh133BE/k9xC7xeM10HQFi699NL4OQ8WoX3PEW6c3F3kuUK4iYnP1TvW9uA34pgRZXUGtjeizxIaGecW16Q2oZHSsXD3DAs2QTvSjNNOF9UsLA7upR7GhPPPPS8ubtvUIM66o8d1wvHHx15M/YnkdR4sxUkSEJqFznrwWHrAgKi+odnbnRG56lPkQgEl2/kCOZLj+ehXHxVbb75F3DdCOOuMM1sXEjdquuByWogp6/dxWMxcPFYUzTNWR7/5F4gDbo8cPbpNQnvzjTejBUjT//XXXg+EsHyxViCYdFwIbaGwra2Di9IWoSEVmVBWJYvn5ODGnXLiSXF7ekw1r1djmy22LGYJBON7ExOsBYQm6cBKdM2QFXf7kUownIXHeqP+QWSTxbvQAgtGtw7JacJfdeVVohXuBoUIJTeQKVUPN6idg+tIj64WEJFuAATD1StbcRtttFFsNK/l+pmM7jPHHHNM5ZkiuntiV21BfC0RmrkDJ4breOSRR7bGvlhn5ba6rmDnnXeO23rggQcqz/Re9FlC0z9JedWP/U9/nDwlTaMMoY0IbkICqZ2ZgrWjaZpgoYW6RXBTEhBJIjQ/ZISmcVt/pB5DUjkeb4dFX41koZHS1l8pfpFcYSqtSyy6aJwzkNQqIqEF94ySB1fQMBMa+sjBMe4ZtgeIGaEhksBoLVXpwdKcMyxO1thdd95RDB3SIsbIxWqP0GCbQFZij9RmHbPsZ0JnCE0pB0JbKrhVnneN9t93VHHAqP2Kn747ucqsZIv3k2MSm6sFhDbLjDPFa+G6vfPjd1pDBNzPLTYdFrch3nlnsIo01FMMSVnQg/Y/oFgwkJYe3KUCIR16UIu15magnEVzPbcYEdYavsICVvKAADSUp+8L1g/fn0yk76saLFyfkTgArUg+X61eCynG57uk4rFpIN5dd901fv6SSy6Jvz1kuEq4uZVnW3QW6QZ4dLhWtn11Sbqqt6LPEpp6K9LVCMg0ppdeeDEG0h8JrtAbb7wRhQUXCIt2zWBuc3+4R2Ip3i9wy0Xx+vLhRydlLjhL8tnr44LLiYxIViM0ahZgJJzt1vpBpxharYZsP+D1w8JjSaUgs6A3wj0p3JHFbd6vzBIQg2OhDFxppThzQJDb+5SBWGyykJIhLBHWigVD4QJJdJTQiDCKLYnXsVhS3A86SmgC3q4ZeR8k/Ga45vC3QD6uUSLzMsSeSBvRmytXr1vYyMr3EF1sMbTgLlaD2gcy42ZyG1nZNNgWDC5ymkPA8nJ9VgnWmxtSivX5DUgI2RfLeZqppoqkVw3freJVBLBouAmJzYFz5f4puK11bo7dIJRhw4bFvyUilg/WarV1Ja6mNi2NtNMnqk3pwgsvjGUfKXiv9er99xsj2W0KVSLL3o4+S2hA/sZdmEWDLFhBFpusJpw1blwxb1gA3MYVllsuvkbRATFYrEcdcUSU2Vk8fA6B9F9siWKGqQPJnHBi/LxYm8Xhjr9quFsikR223bZmPGOn7XeIckMsl1oQYxFbsshWWWnFSFrcvl9++Mu4UO0fgVqgSiiOOerI+DmLltvl2EkMiaMZvoJkxAfFo7hm4nPabmQ5p/n2t4OrOrlbnCBhgcimm/o7xbprrT1J1o7lSt4HubtGAvG2l2YHSMLIuiZ1XHJIrD3nxV32fXhPrUxgLXifwDh3Tu3XOuusU3zra1+PmeBqIMT11103hgqQ6DprrhVvauruqKOA70YNm9gZiaMUwLe9/oF8HSPrbNmlBkQpo2o4np3CzQMB6N3kxoLtiGkho1pAloL7Jqa7bty8ZK0lKPcQVyMzxKJDdiuF712h7PXXXx/3SZkj7bNRcCzc2epi3d6IPk1oYMGTfD76yCMjQUnnlxUHHnrggeLYY44pjgiWiwLSdMcFP0Iu4ujDDouTkLiBSLL8Q1d+wYo6PLyHq6rMw3ar8dwzz0bN/+q2mDJefvGl4pSwsLhTF4c7stgZWCykd0YHF/LoI4+KRJoWIogfOT9lCuJnrI3Tx44tjj7qqJiweO7ZZ4rxt9wag9VKRCQl0rZrgRXix+19r7w8ae8hF0sZCEuHy2LWgPela6IMxnkmEUrvMUNAnNE1OuWkk+ICTe5OW2AtcanEpSxmD8FrNW/lQb1lvBOs8NPGnBpczmPCMT4ZLWKuZPl7PSZcFwmAcWMnFqe+EazX9D1K+ogl1gLLMcWcEFqKLSIZMTV9lLW+f/tfKtxgEBKXUdlFuTgWXHPEMn24AZuf4H3fDTcmNyLXwTBipN5eJ0Bn4Hw2DzdACYdarVK9DX2e0DJ6JxAeC2XjjTeOE5Fk8rQbLRcs6a7on3EDufYkwk22Yg13tUxhhx12iITG4ko3KC4lIqrntrHsEAfFC1YY8itnet081w3Wpe2Krflb4Ss31j64oMjc5xqZjXRdJBrEz2qFSnobMqFlNC0ODO6x9iJV8SrsVcuLKdUreG0LssISLLKaEiQXBQu4K2B9OS7EoxYsdQUgR5X8bQXWkbLPKfdQf8a1T2BxLh6OzeusN7Afz7Gi1LtdcMEFxXXXXddhd72jELftyjVtRmRCy2hKUI7gfqm7Qhq3BTfXYi+3DnUGLB6zHYQPlLp0B6cF116AXlIgWVl33nlntCAF++shFdd6kOQuw6yB9BpSRFqSD8o2kgvLmuKGNxKSDY6lrVBIb0ImtIymA2tF8Fz1uhYqrqISBQHyerGzKYk0wWmGGWZoPZ4rr7wyWmhlq6saYl/UaX12/1KdHfc6WX3qy9SscbdtXyV/T8GxmzilqV12vC+gVxKau5dslfqj6ocMZRnubuRsBPxTjEBRp6D7ezVqgHoC+juVUEhGSO9XB8QdswLbX4S7vXPoCHyG1ZG25ZpYBJQevqjcxZ2795RLIMrwuuC9EoD2gvT/CPtTha9jotpKsB3STIan/CXsrz189umn8b21YmG+VzEd8aKUBZTxQwTVWUFwPSUmJCuqz+E/8bh+H/flOrSHzz79rOW4KkXL1eC2KjlJfZmykYL3wB1sa0gKqIVDUqw7emUJEjzI2jY1q/tujzrqqFjiUU5mNBo33HBD3Kfe1L6CXklo2oL0La65+hqx586EIANvtc3svuuulXe14MLvXRBLBR4ouRlqsRTd3nHbxL66ngKi0bWgFKClRmr5SWZvalMauuGGsZjTQylBvSr1BPV0yiZSg7b4zRabbR4/r4zkqCOPjMT4+Refx7ow6h7lUhKEJPsr46iOTnFxrdqpBIvUlKe555gzll+Y/K7mDpCIYTFKX5SaDF5r7djmVA9333lXHJ9njJ7SiptuuLHySkvGjYv1ja9/PT58n5r5JQYE4KutH9X9A8N77Ne2ZKLL8N0rxfD62oPWLJ55un4wXX+nbTku5Tfq6xJcm4svuii2n3ld3y53mDWlrhEMEBbAr76hlqEmkEosEilbXsg2ZXIV5iJnbiCrrdEuZoJ9LLbYYrGNqiwk0NvRKwnt5PCjJxuj7kp9mYWs7cjfqtETWAA6BqoJwoJXh2SCeU/Dj1V1vMr37513XhzAq68SoYBU+SEHHVzcctNNxbHhrmzBkMZhedQCK1MRrXo0Vt3nYbFtV+kMOPOMM2K9mx5WjfeggV0NGhWJBIXF/cJ1U0+mfk0haT0rDiFrI3KNFbPusuNOsbDVtCVQCKsIV0eF81N0SystVbuXIRMoKK/Ql6qIurqFF1gwNryD2ripvv3tmAhQCa8vdkD//nGyksxg+ZogdfNAjQrUo+lGIXPp3ECczLXcbJNNohqK5ng9rX/4/eRWIcJeasn+cZ7qJRdeVKy28iqxX1UhMjz80MPxHDcZunEkyTlmnS32UiKgq666Kr5H98Cq4TdY7zqCmwrtMedXJhFEJx5nexrfxdpkM9PErEYDSbIov/Wtb8VOhBSj6wvo1TE0agOan1lg1GTLcFe97977Yk0XAnM3T1+cmi0V/x0htFdfeTXWVdUjmAR1TPoVq3/QLJiy9aOo00J7tmIteC25SgKzrBJ9is6tFhTmKppFHsAaYvkRsfRDFX+RxdOnCCrzNx06NJJk2uYPAomOGjGiGHvqmNgvitCMoKsFtXcsHJ0BwF1HkPZn27TT/K3mC8ztVNiqHq8aaWjw9wLBgJuNvs4LK8N31193veJrwdWUBZQIoKLxnammirGpai1+zeQKpkkkgRo8f6cOAiMCKWs89mhLkH7HQPS+89TzWcaFYXE7rjQIetzYsfFvXQmgQR/xp66CocE65jYiIEF1GUKERE67LXAfZWrVfJWLWIUi1JfZHrJToCsp0hY5dgdq52RSdS4k0YG+gl5PaNxO7TWpEjzBlHAL252bNYNELr+0ZRBFRwnNHXVQsDbKFk890N1yl6+V/v5dICrKDwpQWRVbBvetXBgrLvPKKy8XZ59xZnAZ54/HV8/VINCo8p5yBeg/1RCf1DFYbSxA5532wTUtt10lYvc3y6stQtMJgKCOqzRVc29db430iFFNl46EdDwtah7fbb3WZSAG+3uw0gTNrUMUhxx4ULQE5w9EZlGnWq69grXt702Cy1kNljgyTMSp2FcLmOvDKnZcWrdSD+exRx0dJ8mLnVaDy+2mQMASbg5kwiLbf9SoSCprB8vfNU9SQYeFm+R/VwhNszlrlPtp6HBb+OEPfxhjaD53ZkX+CLTaIRfPe5D1TtezJ3BxsNbth35bR6S/0w3ZemMBs2jFalNjfnvx1ymJPkloRBcpWmh9kb15JVgZJoP7mxtqcXaE0Cx8VeNUIF6riDCW8Z/wn1Yg3QJIQ+zFEFxEIXieYIjv/IFcuWqIJok8JliE+kZnDFYBWWkEVwviMyaVrx3I5I+VgLouiOnCYkq9lGJn3DrSR3/6Y0vjNLfTAtWjWYbm6/YIjcVDASPF60gZaQ9afeCqxUsvvhTdNFYlIoWzzzwrEtqF57dYXQmuJetUS1UiVsSGSDT0s8BYZ1xOC9/NRIznf4Jrd3CVxA63e4fttovXKwlN2iZC23/ffeMNxPlT20hlFUkpJVldZWyz5VYxxvn4hMfj36SP3AxH7LV3/I05X6GNlCw45+yz43EhBS1ZDz74YAzqJ3e3Ht56661WlYwDwneeQD3Dc1xrfZupj7Mn4BjVwBmSUhabrAXnLkwgacCi8zlFzrOF35Jj5WIjX3HE9jyYKYU+SWisFgvFoiNDY8EKZrOOkJ0WpY66nG2BFbXzjjtFy0zA2I9+uaWXiWKRt958S+VdLfEebqsYF2sRqVm0CbFd6KabY1sT62rjIRtNouKQ4HwHrb56se1WW7VaggQYWWiJ0Fgn5H8QTcqYandiYTjvMjpCaGJGCCoRmju6vlJJmDdeez0u9oErTSQ07/P+6sZud3FuqmuUCE0gXqKBJcRd427NFMiTa6aui6z01wPJiZGVgRxNX+cWJkITJ6U6cmAgCkQuDiZxlAhN/24k2op7W4aYpOuTCE3Dv+uy38iRMWsrXovwEqFpWSoT2rXXXhuPleVDv+z555+vaWFfHr4r7Us+p1RCVlrLlMlRMpopY9pTYEkmOaI03KUWkJPeYhbczME69/62Hm48ZhqUOx++LPRJQuPaITQW2fHHHBvdDYtZDIcaakcttPZgkYp7Cd6StVl+mRY5GHMa//Ln2oJ7p5x0chRklBmsBdI9Fl6t2IYFJfGx9RZbtGbTxAann3qa2KcKXELkPXSDIfFv0AdogSaV14SOEBpXjlt4eEWx9u0334qBf1YNt0N8jpLvjyrXn7XFRX3ogclnChx68MExHndX5bojPcmZcYEgiAyKl80XiIWFqk1omkBQ3P1ajfQHHXBgtMjS7ALqwjMFq+P0MS1KKGSANOWnhMPBgehc1/vuaVGrLYObzILV7wpXBgL1+0i9ngbEuE7KQ0CWXBbWYpa1TOobYn/+RW612qoSmSBucTQqxeJnMrgmr/ck/FZZfiwr06GQT9lVTP9/U1g7FENSjFDygzKvJAXilc3Vw5qsPO/x4DKrHaS592WiTxIaxViLWuzDD8tXpQ4sZRZTDE2Gzt2eW6WCXGN3NcTOWHlpbFs93HP3XcWywTqrjqEpyxDIZy1RmmWlCFaL0wDrSeCdFBDzfvWBA4t5gtVSq4A0LtRg+rOKUlO04+JiyuApa0DaXFuB7QTlKWJorMQyOkJoZIuiUkY4rth+c/750TIShIcjRx8Rg/FaicRUWEWs1VqV55rqvZcYpePfftttoxLGcccdF12xdcJCQ3DbbrNNtGT6LbBAvEmkWE0ZZjz4DvfdZ0Qk+h222zbGSZM776ZlX+efd15UK+EWU/z9qNKqVIY6Re8VS3NcBB7LiQ7bck1ZeYjAtr4b9p0Ws3o0bVAyscogZA+rG8hZnVtvvXV8r8wiUmOlSQBQuu1psBjXXnvtWCunZKTct+k1cTFlIsjYOSErQpasTjdoay2B9+B8JC5YekpYfEbtoHOqpzY8JdCrCc2PL6b+w4IToC6Dbr3FKnZFNsj/c+ngsPAlTP3tqQKh3R1/oFL6U4cFVJ2Z++tf/hrcwxWKb4cvrL3eP6KN3LNyRhPosokbKddYOPzoSf+oS0uFnldfeVU8NvVgguIsS1I89ZICxx9zXFxs5fmOyIVVZD+xvCC4QeUYHit1vrnmbtUkS6CCgRS4b21l1Iyos13uon+5xKmkgOuMYFlx3LIF5p2vuPbqiUWjZShMlQWddabvBisvHOusswXraHRx6KGHxmA5a5O7znphrbHmWEu14PqxElldvv+5wnGxnJKl4UbGVUSYjpvIowRHLVigJNvTcfmM40okzzJL5+gai69tWLHK0kOLlkWPoFhq1STseJEJC8e1o4XmcxQ4zBkoW0s9AXE67qN+0nI4w34lMwYPHtxKSuJ7XE5ICaR6EJOmdEtFxOd9d7aVBv9MafRqQrMIxR0MiKiusPeaEgOunXQ8GaDk43MLLeZPPv4kEscd4Qfl9XLxacKERx+NmTGB5q7AtKX7wkI99+yz40PcqLwfx8ByOTu4g0oxxJdYa/WAlJDTAftNbJ1xrlwvweprg+vFGk1w3BbjFsOGTVb0+cc//ilaaZRf21pQimhNUpI5vj5sv/payMixZFmH5jO0tQh++5vfFjdef33clmJn1hOJHHd6NwOzLalW7BSsJN9fPWIHBCleSknYxKty5hje++l7McbouGyrreMSy/I9OC7fUfW18tsRy5NU8B2xXFItGgUNPaaORzO5AtvqCn+Bc9aPLgjHecstt8ShKsikpxvDNbRzGal5vF8RhXStERvrENGxHLn9yLX6OnYEkg1KUlwP7qeuDpbdlEavJrSvKk46/oRo1cletgckN0dwN5PgYjMBiWoBYtGI3XB7NHhb6M0Ox2vxeiTNMgtYPdm5NeKjEgmIL2nxKVNBsD0t2SMWK8bHgpKsAIQlfpesMu7+2LFju51djcmniqUmG0pQYEojE1ovhLu/MoRrr7q6+FeVi1uGH66snoB5W5bOlwlTwzWhy6yJ8Sh/EKvraResu2CRJUJbc801I0EhBLG05K4lODfS2Yilp6r/a0E4YM8994zkwiIEvwmdCMsss0w89oUXXjgW+VZblF0Bq5ayrrIO23ajmpIT7SETWsaXBmULYkksMg/V9kQNkUOzg0XGNbZwZQ1BUF1tVjUZc0W5m+11EjQSrEUTpbiSSRnXdXUDkZnlFmqzarR6iZuRoS6ui+SIUEKKF08JZELL+NIg9iYZ4CH2JBhdzqY1M7hXSQpIQkCMjRVmpkC1G6nzAVlz86aE5SlQrx4OoZApEmNFqmrdlGNwkVlpyf1tNLTfpQJicbVafb09hUxoGV8KLGyxJlk1i4xlU6t2q1nBQnPsFq0yDJal/2elQZm41HVpSq+VdGo07ENgH2kpE1ErSADB/E7Hx72XoKhVuN0oSLAgd98rd7faBe9JZELr4+B6dNXkl22lXdYRq8J77EdWt6NgPVhkiKGrSrRfFpBEqtlShyXg7/+5cqrm77vvvujOSXooZdDE3tOQLaWYK44nrucYXdeBAwfGY3PTaLSLWQ9uVvbpMW5c7WHfPYE+S2gffPCLWAahH0/B5A3XXT9ZYPy1cJclq6PHrhralQwU1gSteNPQ2t4Gpr72r+qWp47GqC677LLYatVWGUkCy0DRr2HBHcGbb75Z9OvXL/7glQ7oGrg8uElkidT8/exnE7XP1BsqvTBcWdkE9ylBkJs0k+Jg9XvicmUoc1E0PWKffVoKqdtJjljwBivbl33WK2EwqCQpZKRHUtLw/wpTUzmE9+n37EmkEiZDZByHQD+3099cY8mBVLIxJTBhwoSYsVbaooF/Srja0CcJTUP6umuvHfsm/Zj323dUMTL8oMndJFjU22+zTfGdb32r2HHb7SrPtkCRrILdVVdeJbYUmSM5+tCW1p/ehM//+c8oJpmmaztnEkf12q6qoVVK0Sq12vbAOiPceMRhh1eeqQ81ULJh3BGxlpNPPikWBtO0Mz1eh0fSsPOdGQA9MGzbsSu83WfPvYp//buFmLS16ZRA2muusUax8ZAhrUq4b7/1drHsgKVi5b95pAp/6c7VwzPPPB23v9kmm8baxX1HjqyrasxtS+1BHuJTfndqImVrk6qGh6nnPQnlH7KJ6sxkGPWWarNCbFxP8wo6oqrRSIiFyqA6f9p2PV1rl9AnCU1FuIWopSjBHax8l9BYrRF8k6FD47/lWZt+zMQCSWInWIT17jKsk5dferl45qmnJxkC60tkTaSCTp+32KqLNstADBqun3v2uUkKWOmDKegUjC5/XiO2/ficCe7Oo1xAysJIVobz0VjO6vzzZ5+1djW0HP9Lkx2/GrbFFlmk7o/x88+/iNfRZ7U6qcw/UoV9ZbvOlxiAyetiOQmuQSobECzXoaED4a1AQMCSTteaesm8c84VC3ZBCYpeUh0YrGhtVoqiQZM/ocs7KvVPWta0U7letklfbYN116t5Pq7RBuutV2y52eatrzuGet85YUdBd+fAAipbYM71oIMOil0AylDcUNoq6u0OHJ+uhG233Ta2i1HrkFxBZixEQpKJ4KckeAfG8bk+1HinVOa6TxKaim9yPONLihfVoB9G7VTHwJKLLlaMCT+EBJ0B7ub1ppyXoa4IKZLRXnuNQcHFW63Vurjt1lvDglozkEQLMalH2mjDDeq24JCI3iDcZVX2rxlcPVYljA/bMUV9ow2HRKUOFougrh/zDttuH6yPgwJJ7RU1yohdanVKmbZ9gst9zNFHR8LjlmkDog6yyUZDY5aLO+f/0/GvEY4/9UO2RWhI8KAD9o8WENlwZEHlY7NgqZwTXDV3aD2yrK71Bw+OPbcEN0GMiSvGwjGFnCuItBCj7ZZJhEw4ee1kXUscaCPTIXDn7XfEljE9sKBbhGyQodHAyj42nHsCYUnXp7o2yndI1n2eOecIVvu2sVuA+KSe4HrQwmSxejgX7T9lIEj7EcPsycXsBjRq1Kh4HLsHT4I1aKAMQhND+7LqD/1m0kBmZS1TKtPZJwkNcey4/fbhBzpXbISu7vNEBiutsELrD596xeqrDIwDNeDXv/4oLnCkpvm6rfS2xujbb7s9Lrhf/eqXMWZFMQPooOn7Sw3R9msB6jOthrv6issuF6WsHa8ygEQs3JjXXn0t3uXvuvPO2MBNBQNWX3W1KIukXeejj34diVmTNqKGoYEEd9t1eLSaPKc3dYdwN9cKhADcvTWvx+MPi0+TO3kiaIvQLrvkknh9rrv2umidmWae1GWpM1CBXaTfQsUjwUJgHY8aMTLq+h8dCEaJRpKcViN1+/jxsfMBkVNIMW4OAYNYljkF6RjowNGdcw21ktH3TxOLEIc+1t122TWqqujhRU4J1DRY4yy5MpAC8UnflanqPiMWWP27SfA9yhpqME+KEwaOTGk4DrVt9s8KMnuBFLg6sCkZL6uHpPMmGVGOe/Yk+mxSwJ3+/HPPiaqlLIdEAHDrLbfEYSLcGTAAQwzngQcmZtpMMTK7gDTOMv0HBGttcknpBNYIkcdbb745WljkrkFjtf2kRnHuIWUQfZvV0INpQb1Zo/0EkZn4/dgjjxYXfO/8qN2VpKfXCIS274gR8f/BPpDmGRXS3HTjTWIMEBA9cjikSjCxfPzrDw7HH6xDqEdorD9ijUmW290XUaWAuMfAQE5ianpFCUGedMKJxcwzzRS1s5CBhAPZHPVQXCaiio899mhsMNcEfkFFIBI5lQnN9yo2yvrzYHGlGwbi5DLuMXy32M+K0MrX2oAWv4WkoZZgsbmGZhiwCAlhUul4553aVe7cfllNyYx1gnXqfNWfJVd7SgDhnx8sTvsWi3STEMejXJJ6lr9MsLKvCJ6IpIDvPFtoDcKHH3wYXTeL3F0LOVCXmHv22aMVZlFKIFBt2Gv3yWVcBIW33nKrYtWwQMsKFgm0uijIGsZh2Mn6gdC4izAZoYUvlUVRi9BYBAOCpVWO24FFcuzRx0TiIkRIKcRgkURoLMKyW8VKWSa4gawcqCY0FhAXNUFTd8vxb9py/NzDcLeHeoTGsnOOe4cF7YdL+cOCSmTmsXBwC5HHtlttHVUxVllp5RigZplxxfQVKnFQM1WG89106MbRjQdJHTeIFDdEVJIA1197bXzYRxKXdJy+S5+REGHJlWWUJEiWW2rpyeZPsI4PPfiQqO4hgcDKJRlUrU6SIF7GOlOOcNppp8XznZJxItfCMGLHkK63WJ16r3Ks8suGUIA4nlhattAaCMFyMjliW6RgxJHIxSgBOOP0M+KDAmuMr/xo8ruymZ5kcapluFkEKX6UYhVcF5pmIFZmX+mO6V8uT9kNSqDvNe+cc4ZjndQdejpYOCYQja/04slW2WbZQhuxd0usDbhJ8841d+t4uEkI7dNPo9uXLDTHjwAs4hSI33348Bj3gjYttOAaI3FIMRwxsVSbNcsss0QLzXuRljgKUUDV8kAvzPs0eZfhOCiDbLfNNvHvq6+8slgwXHvuMLBSF1to4eKF556PSRLxtBTrdPNaMFyr64MbDIjRTSBh9GGHx/NP7mwZFtySiy4etfLaA7kjpRiC/WJnMrVqv6ZElwPSpObLtU9ZVseiCb1eicmXBao22sNkfdtKhDUSfZLQKNFSpHgw/NjuufvuOAHJ3dqPlmIsscNXX550ipCxaiSc1a4R/DvtlFOLh8Od2P8L7K8XLBdxmTJYEzGYHiwcZEcWh5sjFgQWr7s+RVSketD+B0QF1mrlWBDHYW0hVlJATz35RFyYMoT95l8gBq2Vkxx2yKFR4/+8c1pKLyxQQX66aq+++kosRVlx+eVb67E22mDDqL8GfvCOd/11BgdCeC5aO8ocZAId/w2BVJcIBJYImWQ4/a9aP0a1YoQouWjkciysb37jG9Ei4/ZwNWafZdZYrU66RqW8vr5E/ApPZQnFnq74/hVRspzb61qRR0ozU52H2CIrW6ZTAsOMUAvb+Wy80Uax/u2F55+LiRHXXkYYyJoj/2uDNeN7XHyRReMMhnpgmSFPSaE3Xn8jJh4E9ashqcHa9J3ZF0IXN+xpCW03B/VlLFtupvgdMiVlxPpuNrBkHatZoylJ1dPok4Sm5IE09LLBvfDYOVhQLwbLh0Wi+PK4Y46NsZgyxKgU0HIHSe1sMHjdmMGjmMrCqed+KDngprFGjguuH3WLo45ouctze5SA2MagYEmx2OiYIdlaeCdYh9xhLqM4EWFFpHnm6eOKFcKiHrL+hpG4uIySACB7KHAuBuRzCKo8hGVMIGbCkylzKPOqvs6De6vvDlnH4w9ultjVURUhTMc5auTkvYnA7TzpxBOjm5xiZ6sFy84kJxaZUoZvBStCBnC68P9LBNdQoiBBRbtFKYbm+Fwjx29otEJZ31WCZIb6NLFMbm6Swga1ZkIC6seED5RzJCC9c4IVLputXMV36zupB6RgNsNK4f1uIqsGYuc2lUsuZESVY2jtSRYR0vO+nrSQXA/FvIhUwapjIBg5cuTIKLvUjOAW+10YsFJt5fcU+qzL6cf858/+HB9pcVjUCKJeTdC///XvqFLqfb6A+PngnrSX+mbBpPf57L++mPh+f5svkH7sXqu3f3Cs9uszqard++M2/vq3lu1X9vPF519Eq44Sr78dQ/UPx3udV4L3ISPb8/9Q7/j/8+9Jz6UajktcUhaL+6Ncw3Mp86alSXsTt4z6b9ofsLwQmnot+3U8zruea5K+j1pS4QjXa7WI1z7dvJxzef/1gPB0KyxcKQpVClH+HKuMiyeDV0ZHtt1V+E3Q6teH6TE03KzFzBTSNnPL2BnBwncNiT1OKXwlYmh9FX7oKy63QkwUfJnQ2uKHS95ZZiu5oO7Q6txqQfDa4uSSNhNcU7plLCF6XixMiq8JtwYL19wABas9SWIJbsDasbjsjkeje3Ljy7M9mxFJRujYyszYKYFMaL0YLJsTgjV0843123l6GhY1IUFFlBZ6ynbSOWsr4ybju35wI2U9mykzd3dws1XcU1tNA3lZkQlnnXVWDHRPiWNGZtxJWUJkhhhIlC+44ILF8OHDK+9qTvCQJIJY6eKlUwqZ0Ho5EMqUsBTagyJPmUtN0EhgyJCJY/TqwVQhiQHxp2bBBRdcEGvMlKIgNedCVpqLzHU1h1PcqqdjQm5WyIzOv1gZd978AZYZC5gL3cxgVcp4UyJ5qjKHdUqg4YQmhuLOIv6SIPj8s/d6RkyuDPv2Q6iHeFx1Fn9bsbVq2Ee9/aTzr4e2jqEa9lHvmNo6Btvv6H7ae29H9lNGipsoOnWXTmj9XVT241+uqloqrqnXOnr9ewqOQUsTC42Cbuo3ZZGJYSE05RlJATahre+p1jUqo9Zn/U38kutLXZYE0b333tvafF4eUt2soKbiZmVWZ61McU+hYYTmjqHafbddd41V5CP33qe1pmuXnXaOjb+16n86Cq05bf0wHn/88WL3sO9tttqquOrKKyd5r/oghavqmw4+8ICY0UzwI1WysdXmmxf7BOtCVXs9+PHdefvtxU7bb1/sGH74Ks/LP0ZlGnvutlvMtml7+vzziUFqLUYG6m652WbFAfuNiiUY9SCOowhUC5Ks5+MTJvaU2t+9wS3aZccdY4nG7eNvm4RwFJnKVjrXo0Yf0abKgmyhIlT1ZLK/5bIU1++G668vttt667ivRx5+qPJKC1gPBgf77JhTTo4tSaA5Gglw1xKUhIwKVo1zV/uXMswynTKkawQrxGtUNDT5NwLq1JxT6qst46477ihOOfHEqN7hO1EmIymhY2GvioWpzisJOHqwkChYILlUFoKwTYLym/O7f/qpidllIEt1wH77xe/izDPGTfL7l/zQkaBNzm8mNd9LHgkjLL7YYpFYzS41WZ4MEGuHkGS9xEkzQaxR6Y44Wr0bYk+gYYR26sknRxUECgd0pPyAU2uR3rknH3+irhXQHpQo+OLrjZLzY1D/dciBB8bjUEuUGsARgLILaXs/IK092pOSAoH364VUn7TT9jvE0oByWUAZ2qcWXrBfceLxJ8R6Kft55KGH42sUTLVJ+fEpt4j1TIEoE/Qyaiynv6Y2bPBaa8WMWS0obzD1W7/i3nvsWSy1xBKx3QaMxNMjqXtA36GCX/MsQdmB6zR4zbXjuSrNQEi13CMuoqJgE8Zl9ZZfepmowpEI2lg63RVmfioJ6R8WmFo6+Ph3H8dOgS3DTcD5LL1k/7hwLXDTtVldV4abCui0WDXcpXfeYafivHPPLRZfeJFINIAULVo9oIjFTUKpTHf7EB2HXt5pw3aVe7hBlKG5X5uZazM0uMaUWZZbdtmoPJsITNbWsaW/FYfusMMOUW471XwpySFs4F+EtuyAAa2qLQZM+74VXfttOe9jw/eVoPdVx4O14ne3wjLLRvUQlo1WIWS65qBB0TiYZ6654zGsv+56rX2rzQ5dC1z16qb9nkZDCM3ioHKgdaYW3JlMJbdY/LjcCd2lX3/t9UkULfwYNCqXBRdZfpQxyPkgrmQJlIGwDL+1faTJUltv7XWilfH8s4HsAjncXwlMWpQG9SJJjeUqzYkLws/DQkKMimqroVzA4mBFxL/DtrU57bDNtvHv/UbuG+vRUumAQtA1V1s9Li61UX74qVj09UBOhuzqKa0GkkO+RAbBMapJQ16gSHjXYPFy6Z2rQtMtw48eHn7oodiYnmqxiFIqLH28Rh8qK9Yk8aQ8QZbHkGN/W7C6BfRVwqd/+lPUI0stU5dcdHG8CbxfadpPjepiYXobZQjTdlnGfht6Y4FumXYlRb1cp28Ht+R/wp1cnIUIQCTRMS1T2buKtwMp+L3oBnH+5bo8QD6uY7J0hoe/EYjAu2NHyINWHxQ7ARBzGobiPTwB0D+qvm3smDHxbzdbnSZ6VkHLFZUQc0jT336Hvl+zSL3GWgVdEAjvsEMPja6uGB69NccnpmffEi6KrHsLuJnOod5Nu6fQEEL7ayAnxZmq0H1Z1VAZT/VBpb7gquZn7h03dIdwV4azzzwr3sk3D+b5SsG8/l5FhFAhqR+KH6aF7o5WBsJgXZx8UssPCZJMjFYjLoEG9VQ5n9QaWGYTHn0s9kWmdiM/oM3DD52ZX42fvPuTaD1YzAnHBaJVEPrpp3+K1tDRpTvw5cHldAcWC9E6hdDeq1h+CH7FcI6svGq88cbrxdyzzxHdoATWhuuiB1HRZ1oI4E5PE4yrMubkU8JCWSa6T8DSQdAXXTC5/PO+wWLcMBB0coMMijXZnQDi++//LB4DWZ8ELVG+L3VaCnlV56faOha4nlWtUlRoBbG5ur4bfZwkeRKQruZzpPvow4/EoluuCX0x27Nd59sdnBhuBr4Xx+VmUN2Mj9DKx79LcOsdg4Z02Vmu3V677xlfA2KUSEU9lZs3vPjiC7FT4vHHJ94sttpii2i1FsV/YjcD6yxZh488/HAkWS6wm6r2tOeeeza+BizeRQOZq6xHBMAlR67c8rPDte1tmJKuZkLDXM5Hwo+TkoQ7j17Fcne9uxYyUpPkLuwOrSKcXhOSc9dbcrFFozQOXHLhRdENYMmZF3jUkUfGz1gAv/5o0nS5mJH+yLIKqzYad3qxG8S1QiCP1GfHMqQtdtABBxTXXn1N/Gy5C8DCVW1fHad4/rnnozV3U0kmRlcA4qTesHRVI7T4mrsusqQK4fU0k5ELGGV9dplcyZQlSewwxVTg8EMOjS1OTwS3nVV11RUt7hwgbMflRiJuSe016frr3bSgxYrKYG2K81l8yaLkZqvUV7VPWgjplONPlGHpi/3m17+JpM89THFK8UDXAaGLPQmss5aJSFargbjW2sEs8KuuuKKYZeaZI1mQvfHd7BbcwU2GDu2QSm4tCCW4uaTaPC67G1pqYAcWvJYpclHv/+z9YsYZZiimn266aDGq8eJuLtV/QLjhjA6/kwNjLJG1JjGQQESybA3DAaP2i83/n3z8STE4uKis9BRmERv0Gxa28ODyJnki4YQBwW1HXMpGgDv+3ZlmiseydUXOKaN9NIzQgDrpiL32iq6L5uVUq3PySScXqw0cGIPO3BQkIhCfQC1iycUWL6656prinrvvCQRwZvHd8CNL7T1665YKP8rf1hjSmgitbLlx7VhHb7z+enEKQgsuTwp4Sy5stMEGMaDNzdLoXCY0rTU0tVgXZbirLhrey9pK4GpZyH7UFo14UwIVC8fw8osvtRBaeJ2bBbYtmJ6axstIhKavMYEMuBvAU088GS29FB8EfYoIzbW2gNZaY1Cr5eFcnXtS3khIhOY7+mflPH/+/s9je5XWJ61GCC1pqgFXUZ8kFwqhsawToVl8VCx2CJYVckp1W6r3KWWM3Gciof0okAZCE2qgNMtVnX666WPjupuOAPmmG2882fXnBrMAXYsjDjuseL50fcq44/bbozWffjvIiDSU5v+EfcJvlP4aq2jJ8B2xgjYP1wKScGO/YLmzFFldWrGqkQhN7DSBJehmyb2uJrTXX30t/Fb6F3fdcWcroQmxIErdFLom3HhdUzf5FSvFySzejI6joYQGzEwLj7V29BEt7SGnnHTKJIQWLZ0bW9QgALmwyOhYkfBxV/V48YUW3aoLKi5kLfkeixZZCConcPdYJsgOGS671FKt5MriWyVYi+PGnl48eP8DgQwXKl6pNBVzDwSKuQrVsBC5qlde8f3KM0WMn3AdWUICwGVLSE+j/SpXoRiB3JKVIC5IrpqSbDVeeemlSGhlMkF8MmksWgR18YUTeyKJHLo2LC0uMEs41SixZn0Pho9UY6+wTZZQsuZ++IMfFIuGG8PmwWrjajoG7mGCJA+r5p//989i1512igs9kQ7xSb2aG4YbhUV4TyVJwRLdfNNhxfBddo5/w7NPPxO3bTFTsO23wPzRRWWdaFTnopYVMhK4xhddcEFx4gknFMcfd1xw+SbVNAO/PdaX7YsBugmsFqy1OWaZJYp4BnaJ70tJIplkirniZqmxnOKrc1g3EBMgmJQoKePZp5+OhEZ8M4FqyXbBvdZqJtnC2k9uF2sXeT77zLMxpodQxeeUtwwIvyt9ozLaPAPH5Bg0npctwIz20RBCcxeq/tItliQBQ864LUI7c9wZ0VWVGaoFChgWbbJwqiEovkNp0AmVWvEex/XQA0hr4dbAsIU09xxzxsUqxiZLeHPlWH71y1/FbNMZgeyqYUGxNg4/tGVYih8qC0dJA0gOEBdMP2AuDxWOf4UF8cSECdES5DIDS3becIdmTVRD7EnD9zlntcRM/vrXv0QtNkkCBLLuOuvETGqC+NS2gQTglptvjgtFtgycI7f3qRqlC2cHK1hMMEkbORZul4X02KOPxWzv2Epwnvu3VnBl07lTpUCsSViRysgCwSrSXygG9HpJpJJkD/WOZDWyVt0YBIvFFFlo3E37PTRcMzeis8LvoStwXckHIZKbb7o5qpWY9kXrTYwPmSq5KCcFVN5r9k6lGOJkjkUpSVtwo2Itu2GCm5okATEAGH3oYfG8UxILGYt1SvK8+867wUKbp1g2nCslCu1imut5JkpDENn/BquRSGd1hjajbTSE0ARKWVRiZ2JMLC7qn5dfell83WJkwcQYmh/xPPNM4gIk64c09KMPP1zcW3E7U3r8umuvjW6KxVAtnwx333V3dDOoKbRIP/eLnwEN3ciVmylG58ctRsZSA/EdstQUIrgIKyyzXGsCoRq2vVBwRS4L58U6W2TBhYrHJ7RYUoL4jmFccDuVTCDtKy5vseZYKuJVyiRkHlk3Ske4FrXAcmN1kq9xLZdbeqnirTffjK8pp7A4L7rwong9HMNDD7RYUqSwuVGsOfuhdbbT9jvWbNoWn1w23ERYanfcfkeM8ZlURMdMtpLMEquSiCKpcseT3Kv3fvpe0T9YfqPCtSPL47vdI2yHnA1SKxdSmhNgO4cHN5H7Z+GOOaUlMwhGDCJDJDIbFYngln3wQdcmFLGQSUO9VLHsE2STbX/11VaPQoxuCkPC78HNY+lwDbYPrmW6EZ0QLEDvnX3W2aL7yxrdf99RNW+2spLLBSv85ptuimUrSD7VF775Rkum1U3Azdv1S+Uq6hWRqISIwcSugfik6UwLhd+NBMXMwWrcbuttosUprkgxxvedCa5tNITQLBjaWRuut34csuHuZyGkhSSeJGAu6CtOooaqPJEJpKS3D1YWORzkgzxSjMZC3T9YXSRuLr34kvhcGd4nHsPFUFph3+kHCu6IMnOUKQ4I1o3yjAQk627KNWHyc5/qgYXEchKg51I4r/9ULFP7Yw201LmtN1lxLxIQu3EMZIrKxb3VkFChfzYoLED6YoQME/ygueCCz0pV7g4kXbaO6XjtvP0O0eWSRW2rbon7w8UTuN82WNPKEnasWJxuJkjNMXDXyCSVoa6QRer104LFdmNYtOq2KEFU47577i02Ccfqup1/7nkxTJDAUttlx52KbwSXUyN4OT7YGYgLSmiwav5SydwmcKfXCtcLUXlsv9328ffl2iBwOm0JqdNh3cGDY0zM+DtlQ8mCK8MNSTmNa+BmXE7kAD2+YRtvEuOa55x5VgwFEGLUlM8qHRbWiWuPrPx+FaFKAiwZbhZqAt3M0kN9p3rB8m8qY3I0NIaWXM8UCO0s2vt8rVhGGT5X77Np2/XQ3rbLaOsYu3MM1WhrP+0dQ0f3471uPHovLeQTg5VT3m5Hz5Wr5PMsnPLNJKH83mqwYFlOPi9+lDoJGgWab2nknEdS+LglWG5qzB4OXgE4PplMWmfKWDqKjlwjN0PijKxYccrUsO2zLFqk6thWDJaaco2MrqHhSYGM3of3g8WqpUczMdnkzgIhkbWxIPUcdhasjjQhSIC8kVLWLM1BgwbFbXPl/CuTCYpWxavUCiYgmHqSR10Fi1uihAWLzFJxLriZmHDuuLj83//+xKRTRueRCS0jWg7cPQHqrrTWIA0yQKrZy10enQFXTKZTCUVZf6w7YCmywhC18getS4gjTTLn9hnQm4qLewLIUfZWWQYyq5bp1iGBVB0XPbmM7iETWkYcVGJBGf7RFbBwTPehXNtVKLhWi+Y4jMRrBLh5SIxlxMUzOg9pUrFA3BICspw9BbFfViC3VnysWs5bUoIckHMmS5SSYBldRya0jDhT0qKiKNEVSAj4vDhQqk3rChTk2o5G8JSF7g6UQ9ieuBS3Gqn5m4S2obymi9cK9jcCyExcEZkhK5nzcmxRgkCszvEgck3pZbLL6BoyoWW0Vsdzz7qCNPCWtE13QBeN6yuW9M4771Se7TyIC4pL0RJzXKkPkgKE7XtO2QT12Z5wN2U/kTOrlYIHt7NMVmKGyM55Og43hFQMndE9ZEL7ikPsKqlJkEymlX/XXXe1qaNWBouMtaPavrvKpILn3ED9oOJ6XcElJKLWXz+ej4cuBNOSgIS158SzjKJLYgGNBII0WAWZIrNyT3OC60vfzHlyeXuLJFBvQCa0ryhUycu2DRw4MKpLWOhzzjlnlNDxt8B5uUC2HmTpZBEF3btrZSjXSNYiC6azYCGussoqccSbAlXbocefilFJ86jz4uolfblGIsXsJEfE6WqVn+h7Vcjr2BBvueE9o/vIhPYVhHjNqaeeGgPk3CKLiyXDYmEZjRgxIj5HIrs9cO+QYFLL6C4IAjouswnaQ7n2yzkhCgTGXeVOOof99tsvunhiaIQTWUYTqoqEGwHEjiiRmTmUtcgd4Y0ZMyYel2uWel4zGodMaF8xUHfgbqnJ4mLSxzeDEiEl90jjNyvHNPD2Fr8CVFZPR8ivI7A97pr9a8+CaqKUrURejl3dm0LUww8/PJY/kH4GcTPEofIfEK8KfYNGGg3kNWzYsNh1oGi3XkLDDE1k7bh6o75Zb0AmtK8QkIVK/KjIGtxE2lv6cLma3LEy0gi3cePGVZ6pDYoRCO3ckh5ddyATiKwE7xGAzKsuhtTwTlMulTp4OBdWpmPgJqdM4oUXXhjLNdJxOT+j9hoJgX43ASUZMqduFLKbtaC0JY34875a3RQZ3UcmtK8IuFwHHHBADESzfmQUQUbO39UuHovG/EcDbpOlVAtHHXVUjLl1plWoPahDs/CnnXba+C+yMFIOlFmQqGZdpoHGHo6hTKqKc5Gd83SOCO3Oqr7X7sB2BPMVy7IMZTXrlYAQnUxxMy1eFE7qtUpldA+Z0L4CYIWdd955sUyANTZ27NhWC0E2E2lx2aohwM1SSlnCaohNaWZHOI2crclylIlMREWeO0EngmC6f5WLpISGc0tzDEAJCvcOiXM7xc8alU1ERlrEdBmwAo8//vi6pC9u5tpzR43AY3V2p1Yvo21kQuvjQDqas2UhLX4B/6RNBvomkQFLqwyLlpwNsqARVsuiECtChjKlaYpWI0CmiCVp3wbtlmNoLEEZRPtW34WovM+8ynIfqlmW3FCxQv9yQRsFGVJkpuH9zDPPrEtmrLjnn38+Zl5ZcRIxjbxOGZMjE1ofhxiPSUwWvbhZdeM3ElDcWavdiMa+hShGVAtcLAkFA3AbCRlLVp9jduxlOH61W2JVWoUMsvU+7md5DoQp7pQtvCbhUd1D2VVIkshmujko3m3L6kO6w4cPj8fgM11p/M/oHDKh9XEcccQRcUEhiFo1Ty+99FKMVaXgf9kSE+sRR+Mq1apJU0jLuuPWNTLILYvJlXPcu+yyyyQumuMrF6smyWzCkuX4mGOXLWXhNUrBQpmFNia6cddee21dgc4ErqZjY8USdczoeWRC68MQBJ+vogaLJGqRjkJPbpmJ59VAJKwbcbRahagWqW030p1jZWmSt10Phbbc5npgrXkfty6NmAPnKq6nTKURULSrx1RcTjN/2W2vBR0YLF+JiTR0OaPnkQmtj4JFtc8++8TFLnBfr82He4ewCDPWgliRbdRqa2pUD2cZ3DTxPJOQzCeQzewIoYnj9VQ/pHgcvTjWqHOtFU8sg2vJknNczqO992c0DpnQ+iiosApaKyZtS19MwoAVoe6sFmjeW5j6D6vBkmKxNLonEoFx58Tn9EO2ZQ0lpRCKGo0qySiDu6rAmNudSkfaAndY8J/LLP5HFikT2pRDJrQ+CA3SFriFLgbVFsTQZAHpdtVCqrgnUlgG8hDwFqeyaBsNrid9tTXXXHOSmFk1koUmOVB2ObsLLqtGd+Uj4nPc9/aAiPXHpunxVDS0RGVMOWRC62NANEoJWAjzzz9/65i6ehAbY8nViqHBaaedVtNCI7stsyjo3lOlCLKrLKN6rURQ1lBri/g6A/sTF0T0+jKT/n97YFUmpQ/dALlEY8ojE1ofg4HKFiFXELG11zCuaFbWrp7LmZqpq8seWFA6DBBaWzGu7kCpA7ezXjaRFaXDwfGx5pBsd6EURceBbdp2Z7KTyVp0zN3Rc8voOjKh9TGoqreoqLGmOZptQRbQ+8vV+JDiPiw0Ra5pMlICN1MGVX9kT7hVJH8QMyuwrfIIxb+ytILw3U0K6LfURSFJctxxx8UMcEfBvTS7gFXXkVhbRs8gE1ofguA8iwlBsc46AqQne0dupxaSBVQdQ5PJa8tVbQSQJWunLZdTJT4S6Yp+Whl6VwlAigmy0MpFuu2B9ZqKl1lpPTl0JaNtZELrI2BRkdJRHY/U2oudJSRCq5cUoM5hoSqlKBOLRcwi6eocgo6A8qvC3rbG2rHKdAV0R7BRXyjdNFZtZ+WFqH8gQladOB6CzfjykAmtD0ERLPLRHdBRN1BvJJet2uUEcaCk/KrVZ/z48ZVXWspCyG5Xu6KNgngYq0dsrCebubV3qdOTJe0smbnGms01nns0SkIpo+vIhNZHgGxYZxRTOyKdncA6oSdWq9qfcCKpHjM3EZvMaSqi1UYltqaOrScg0aD31KzQngIX3TwExbtd6XbQxykxgvApk2QVjS8fmdD6AGT7uIQWFhXXzmQd33777VjeUR1Dsw0ulG2yXC6//PIoPaRZ/frrr4+uFRnpntLEp6TBdR46dGiPEAXSV+M2ePDgLqvYJnecq5oHnTQHMqH1AdABE88S0O6sC0j4UXN6kqpOUFDredtMMaw0NcmUKPVWFFh7KgAuNsWlHTVqVOWZxoFSh95PLi3FjK5A7FBrFguWJZvRHMiE1svBekm1Yl2RmKblxeUsZwmVLyAvUteskFSwighS4aggOFf0d7/7XXyt0UDSXNxawpPdAXJW+c/6Y3V2BQbJ6B2VXZVNbisLmzFlkQmtl0PwXKyJNfPII490um9QPRlL67DDDqs8U8T2nSOPPDJutzxTwLZT8agHC6eR7UZl6KFEGOVERHfBjdUStvzyy8ftd6Ug2A2AXJLzJ6vNZc9oHmRC6+WQnZSltFB1CXQWFrnSiL322iv+zYKhakv+hrunFKQMMbM0+k5msKcULhS4yqx2pDi4PWgHS24m8nbNutJVIKupHk8XhrhZI8k2ozHIhNaLoa0pWQsEB7sChKTin0wQiKmJK9keAqjuR9QaJBlgnwMGDOgRd0tcTnbTDM2O1tPVg4SJY2ZtSn6QAurq/FD6ajTOuNvmCGQ0HzKh9WIgH64ma6GrhaXairQXqWEDrph4GkFIahPVkjziaSS3EZrG8Z7IcrISqbwqqegOHDsX0bkhItnZrhIwCaPUDeC4EGVG8yETWi+F+I+2IwtM4L6roMsvwJ00+QXKuVLqqqrdzQTDdO2Xq6uHsdGwTRlWlmJXtcR8Tnxwiy22iFlZmnBdjffZluSEJn5WXk/IJWU0BpnQeik0b2vItli1/nQHXEsZS+SGrFS9EymsBxprCM0Cp1rbaCgh0SfancEmGst1ACirEDNrq32qPSgmNl2KNtodd9yRNc6aGJnQeikM7FCp3904E9eJC6neTHGoTGm9RnVgraQiXg+k0cjCVy4tchXT60yDeBlKPvbYY48YvOc2d6e0xLYcC2tUS1m9YcIZzYFMaL0QrDNZQISiALarQE6yfdwyi19GsTpmVgtKOhKhqeeqR2jcYq/51zG3lxF1PFqpdCSog+sKEJDsLAIydakrmd8EhKrzwnnqmuiuJZzR88iE1gshC8iK4RqqGesuttlmm7hoO9plQI3VWDxxLuUiYkoSFAgRwUoqqFcbNmxYDMgjTLMB1lhjjRjva0tySNZWAF+nQGeBzA455JB4Loiou9aU6yGjKfGSJzf1DmRC64W49dZbY4wJQbBquos0DLej8yv33nvvYquttooiiD632WabRZcVEXGBZV0NFjGghVvM+jOIxXu1Cyls/fDDDytbmwhFquJ5LKzOZiN1NyRXmHXXmQb9WvjFL37ROpXd5PiM3oFMaL0QqvpV0bMaukNoPuuhkNbCNeGpPajh4mayXpR2+JyHoSASBGJy4mAKdpECC1KRrpIJhEnyu54S7AMPPBCD+HfffXflmY6BhXjiiSdGN9M5dLd2TXJEltd5cTWzYGPvQSa0XgbFnWq0SAU1KqbDArF4O1L+Ia6k6FUiQWFtIjTZ0e5ALI/lpp1IvK2jUGdGJpxrKBHQ3ZF69i32phvC9CZ1dh2JK2Y0BzKh9TIY2sGKkXlrVHGnqnek1JFRcDoIvFf8jrSPBnLW4sknn9xla9Hnbrnllrh/VlxHtyPgnyZcIdTuDiaxXxakujzlMN3pKsj4cpAJrZeBogZCEXjvKoFUI42q0wLVlq4XNzLtX7xKnEpvpL+VR3QVzkMvqfhbW0OFy1BXZkAK4tlggw1i/K27lpSuCTMUuK6s1lpxvozmRia0XgSZP5LUtM9kFRuFNLZNHIwLVw/KLlKXQFLnSOob3SmwVawqocA66gjEuHQ0zDbbbNGa0vbVFeWMaqTrQCLJAOaM3odMaL0IBt5acEOGDOlSWUM9SC7YrmzkhAkTKs9OilRrZn6ninnlFYBYfJZ71hWIeSnrMDC4IzVjYnhao/SR9u/fv3juuecaUrnvvFl7WpsQbEbvRCa0XgKEksoSGj067qabborb9ajVm8kyU1/GzfNAJqmUQQYzVeR3FshJj6VSDaUo7UHA3gR3yQjusa6GrnYTlGEkH0tPSUlHx/9lNCcyofUSIDRZQO4myedGxc9AM7p6MbGjq6++uvJsC8SlZP1OOOGEmIlUkqE+a+TIkfF1bUWKbHUPdBbKLZZZZpkOyWw7DkqxMqwykIitEeUU5JFYm+r6xM8yejcyofUSqPtCZko2kiR2o4AoEBoLTUtVGYQR99lnn6hcK6uKSC183QLAYqOP1llCsy1ZUjVtHSmiffHFF+P705CWRijlukkQbBS/MzAl15v1fmRC6yUwmQjhcDsbVa6RkKaP2351ca3iWSPsymoVEgE6BZAbMmI5drb3UswMObM22wvoq72TXeXaGjfXiDkGLD7bVSri/BT7NtLqzfhykAmtF4A1ojQB4VS7hI2ALCG30fZZYwl6IUkUIZG02P2LjDbddNP4N5hrqR+0o2UTyi2QmXIRpRJtQWnIoYceGgnXMJhGlVKwzpCkRIAOhZT0yOjdyITWCyCjKQgudtXdtp5aMD08yWrvvvvurVlDZEL4sVrokfCiZvMECq4ItyOlE+J14mYKgzWTtwWuNSkjx6XpXL9mo0BzzcwCJKm+LqNvIBNaLwACsajVoPVEnEftmTiSfWg0T5aWroBaLU0ITmaSdcX93W677eKjvZYlWUnnIKPYnkoIUpV9lajYddddi9dff73ySvfx4IMPxsb5TTbZJE6Oz+g7yITWCyDDiGy4aj0B3QFKMexDUWkiNHE71lQ1iXJ7lU4kfTM9lNzOtkooxOm8hxIHBdj28NRTT8VEBfkhGmmNAqtQHZ8i4jy1qe8hE1qTQ5Zx6aWXjmRz2223VZ5tLATZWU72QcMs9S9qr6o12UnN2MILL9xKdPvtt18kRBX8taDBWzbTZ5Bke6DSQeSRu3v77bdXnu0+WJRUObia4nIZfQ+Z0Jocsm9afJBao8s1EtKgFITGekn9lDKcmtCrhR+VUNA/SxOfEJo+zFqlFG+88UYkRZaZuFV7U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13:19:32.695732 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:32] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:32] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:19:32.719263 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:32] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:19:32.733264 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:32] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:32] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:19:34.749462 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:19:34.754574 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:34] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:36] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:19:49.504733 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:49] "POST /myclass/api/Get_Session_Nb_Sequence/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:19:56.137020 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:56] "POST /myclass/api/Decale_Session_Sequence_X_days/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:19:56.361776 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:19:57] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:24.427447 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:24.434005 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:24.437165 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:24.441806 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:24.447447 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:24] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:24.454798 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:24] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:24] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:24.462036 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:24] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:24] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:24] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:24] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:27.150028 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:27.154051 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:27] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:28] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:30.383109 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:30.386112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:30.390112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:30.391110 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:30.396536 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:30] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:30] "POST /myclass/api/Get_Given_SessionFormation_List_Automatic_Traitement_From/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:30] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:30] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:30] "POST /myclass/api/Audit_Session_Action_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:32.580452 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:32] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:35.031237 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:35.035401 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:35] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:35] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:37.184078 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:37.185081 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:37] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:37] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:38.470703 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

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Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

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xddd   qsdqsd   mysy1000formation+04@gmail.com
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Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 06/11/2025 

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Pour l\'organisme de formation
prenom  nonn

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Pour le client :
Nom & Prénom du Signataire

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\n

 

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Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

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' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_73754.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:38] "GET /myclass/api/Prepare_and_Send_Convention_From_Session_By_PDF/PW5CxmVrXwZklUBdG1N5wMt5bNONwYtzJQ/68e419c2e5fea6f5328c2007/65f05a36c544f77525a3062e HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:38.787729 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:39] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:51.379955 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:51] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:53.038453 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:20:53.040697 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:53] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:20:53] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:20:57.038848 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 06/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_40895.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:06] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:06.142696 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:06] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:40.475549 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:40.478546 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:40.486545 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:40.495563 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:40.499651 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:40.511643 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:40.519565 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:40.537681 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:40.551295 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:40.566309 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:40.572306 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:40.589304 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:40] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:43.236883 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:43.249920 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:43.263541 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:43.282687 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:43.317856 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:43.333886 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:43.349431 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:21:43.371025 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:43.390013 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:43] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:21:45.952979 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:21:46] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:25.388988 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:25.393371 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:25.396745 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:25.401195 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:25.404750 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:25.405259 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:25.413418 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:25.416420 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:25.423926 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:25] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:27.896565 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:27] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:29.613405 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:29] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:33.428887 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:33] "POST /myclass/api/Add_Update_UE_To_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:33.614475 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:33] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:38.903545 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:38.907169 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:38.910269 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:38.915861 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:38.921861 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:38.922858 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:38] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:38] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:38] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:38] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:38] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:39] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:48.704957 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:49] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-06 13:22:49.418554 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:49.422852 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:22:49.425854 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:49] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:49] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:22:49] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-06 13:26:00.660607 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-06 13:26:00.660607 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-06 13:26:00.660607 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-06 13:26:00.660607 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-06 13:26:00.661760 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-06 13:26:48.204409 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:26:48.204920 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:26:48.211758 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:26:48.215764 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:26:48.220758 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:26:48.224766 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:26:48] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:26:48] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:26:48] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:26:48] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:26:48] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:26:48] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-06 13:27:29.395654 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-06 13:27:29.395654 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-06 13:27:29.395654 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-06 13:27:29.395654 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-06 13:27:29.395654 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-06 13:27:55.834609 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:27:55.838609 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:27:55.842032 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:27:55.845954 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:27:55.849000 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:27:55] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:27:55] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:27:55] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:27:55] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:27:55] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:28:03.245599 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:28:03.249353 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:28:03.253692 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:28:03.256721 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:28:03.257716 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:28:03.268190 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:03] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:03] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:03] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:03] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:03] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:03] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-06 13:28:08.685744 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:09] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-06 13:28:09.218336 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:28:09.221344 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-06 13:28:09.226344 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:09] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:09] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [06/Nov/2025 13:28:09] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 09:24:03.950909 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 09:24:03.950909 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 09:24:03.951921 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 09:24:03.951921 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 09:24:03.951921 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 09:24:31.824260 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 09:24:31.825260 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 09:24:31.825260 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 09:24:31.825260 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 09:24:31.825260 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-07 09:25:15.492478 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:15] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:25:16.163191 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:25:16.164192 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:25:16.167710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:25:16.170709 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:25:16.177713 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:25:16.195234 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:25:16.217235 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:25:16.219257 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:25:16.223244 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:25:16.228245 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:25:16.235245 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:25:16.256797 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:25:16] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:36.193939 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:36.196938 : La session de connexion n'est pas valide +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:36] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:44.708483 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:44.710483 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:44.713521 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:44.717484 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:44] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:44.727484 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:44] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:44] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:44] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:44.752517 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:44.755500 : La session de connexion n'est pas valide +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:44] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:47.304662 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:47.306659 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:47.309668 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:47] "POST /myclass/api/get_all_class_Given_partner_owner_recid_No_Login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:49.682960 : Get_Partner_Data_From_Subdomain Sous Domaine invalide 11 +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:49] "POST /myclass/api/Get_Partner_Data_From_Subdomain/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:56.332522 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:56.364559 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:56.369561 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:56.373561 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:56.387115 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:56.389081 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:56.398601 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:56.406597 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:56.414596 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:56.420601 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:56.422595 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:56.432597 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:56.439613 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:56] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:59.449950 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:59.485463 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:59.486466 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:59.491464 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:59.493465 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:59.495465 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:59.507980 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:59.513979 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:root:2025-11-07 09:26:59.514979 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:59.522304 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:59.531813 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:26:59.537812 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:26:59.540812 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:26:59] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.379157 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.380481 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.383471 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.385602 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.386599 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/get_List_domaine_formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/Get_Suggested_Fr_Cities/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/Get_Suggested_Word/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/get_all_class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.508951 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.511055 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.513459 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.521519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.525519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.528502 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.536079 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.542078 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.553138 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.560277 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.568271 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.569155 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.584153 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.587229 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.594145 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.597144 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.603179 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.604176 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.606184 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.610178 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.611179 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.615744 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.618743 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.621744 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.624775 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.627749 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:06.628774 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.630750 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.634750 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:06.635749 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:06] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:09.904135 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:09] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:09.961956 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:09.970947 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:09.977938 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:09] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:09.987931 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:09.996984 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:09] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:10.002982 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:10.015519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:10.030084 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:10.040127 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:10.054650 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:10.073666 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:10.086667 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:10] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:27:11.962785 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:27:11.967676 : La session de connexion n'est pas valide +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:27:11] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:33:51.411013 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:33:51.414013 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:33:51.416013 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:33:51.419012 : Get_Partner_Data_From_Subdomain Sous Domaine invalide 11 +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:33:51] "POST /myclass/api/Get_Partner_Data_From_Subdomain/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:33:51] "POST /myclass/api/get_all_class_Given_partner_owner_recid_No_Login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:37:55.694847 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:37:55.699852 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:37:55.707847 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:37:55.711851 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:37:55.722851 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:37:55.751361 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:37:55.755360 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:37:55.758363 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:37:55.761362 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:37:55.770360 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:37:55.771360 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:37:55] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.251145 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.254149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.256149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.260146 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.262159 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/get_List_domaine_formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/Get_Suggested_Fr_Cities/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/Get_Suggested_Word/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/get_all_class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.592483 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.595482 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.599825 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.602825 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.607849 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.616850 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.622850 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.625849 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.630851 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.637871 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.640866 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.652872 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.661849 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.673865 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.678851 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.683863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.687860 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.691859 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.715792 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.733792 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.735791 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.743792 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.748793 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.759793 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.763800 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.770793 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.775795 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.783824 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:20.792799 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:20.796803 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:20] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:22.913690 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:22] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:22.943674 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:22.944675 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:22.947676 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:22.952683 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:22] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:22.960674 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:22.978690 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:22] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:22] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:22.981689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:22.983705 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:22.992745 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:22] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:22.999757 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:23] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:23] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:23.009252 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:23] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:23.014256 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:23] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:23] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:23] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:23] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:26.354949 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:26.358951 : La session de connexion n'est pas valide +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:26] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:38:33.648513 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:33.652480 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:33.655482 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:38:33.658477 : Get_Partner_Data_From_Subdomain Sous Domaine invalide 11 +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:33] "POST /myclass/api/Get_Partner_Data_From_Subdomain/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:38:33] "POST /myclass/api/get_all_class_Given_partner_owner_recid_No_Login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:11.379156 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:11.383157 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:11.385158 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:11.386157 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:11] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:11] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:11.402289 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:11] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:11] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:11.417987 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:11.420988 : La session de connexion n'est pas valide +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:11] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:16.783512 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:16.786511 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:16.788515 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:16.790525 : Get_Partner_Data_From_Subdomain Sous Domaine invalide 11 +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:16] "POST /myclass/api/Get_Partner_Data_From_Subdomain/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:16] "POST /myclass/api/get_all_class_Given_partner_owner_recid_No_Login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:23.124039 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:23.129038 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:23.143035 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:23.149038 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:23.152048 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:23.162045 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:23.166044 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:23.170557 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:23.175555 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:39:23.178555 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:39:23.189070 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:39:23] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:40:03.270685 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:40:03.274685 : La session de connexion n'est pas valide +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:40:03] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:41:01.894689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:41:01.897701 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:41:01] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:41:01.905692 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:41:01.907691 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:41:01.915695 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:41:01] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:41:01] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:41:01] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:41:01.932690 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:41:01.935690 : La session de connexion n'est pas valide +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:41:01] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:43:17.348112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:43:17.351113 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:43:17.354112 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:43:17.361112 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:43:17.369111 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:43:17.392621 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:43:17.395622 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:43:17.397622 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:43:17.400623 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:43:17.403623 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:43:17.411630 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:17] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:43:19.524063 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:19] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:43:22.861373 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:43:23] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:12.318035 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:12.325544 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:12] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:12.333545 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:12.341545 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:12.346544 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:12] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:12] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:12] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:12.358544 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:12] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:50.699799 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:50.700797 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:50.705798 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:50] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:50.713799 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:50.720799 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:50] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:50] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:50] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:50.752838 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:50] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:57.990704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:57.998720 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:46:58.007865 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:58] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:58.010898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:58] "POST /myclass/api/getRecodedParnterImage_from_front/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:58] "POST /myclass/api/Get_List_Theme_Catalog_Pub/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:46:58.963080 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:46:59] "POST /myclass/api/Get_Partner_Catalog_Pub_Config/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:06.487923 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:06.488933 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:06.491948 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:06] "POST /myclass/api/Get_Partner_Data_From_Subdomain/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:06] "POST /myclass/api/get_all_class_Given_partner_owner_recid_No_Login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:09.473975 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:09.482976 : Ajout Token OK, _id = 68f23fd115d6ff1cb9f4ec72 +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:09] "POST /myclass/api/Ent_Student_login/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.393924 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.394925 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.399926 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.404928 : {'_id': ObjectId('6906220dd3d7adc37cb3fc93'), 'apprenant_id': '66432a8b41efccf7bb038fe4', 'type': 'student', 'email': 'mysy1000formation+02@gmail.com', 'partner_owner_recid': '43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89', 'active': '1', 'adr_city': '', 'adr_country': '', 'adr_street': '', 'civilite': 'neutre', 'code_postal': '', 'creation_by': '65f04934549224c14c3f6039', 'creation_date': '2025-11-01 16:06:53.957236', 'firstconnexion': '0', 'locked': '0', 'mob_phone': '023456789', 'nom': 'ccc', 'notification_send': '0', 'prenom': 'sss', 'pwd': 'Sdj3X7hCbFo', 'lastconnexion': '2025-11-07 09:47:09.482976', 'token': 'lpd3vw_C5_JTNIN87nr7db5lS2vmNMb6Ew'} +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/get_user_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/Get_List_Ent_Alert_Message/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.430444 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.496813 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.499811 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.503812 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.507811 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.511811 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.514816 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.519817 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.522834 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.528326 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.542334 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.549334 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.553351 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.560339 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.565336 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.572353 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.579336 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.585334 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.587335 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.593341 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.604335 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.608358 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.612338 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.616339 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.625360 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.627339 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.631673 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.637679 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.641672 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.645676 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.656683 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.659682 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.671187 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.672192 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.676198 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:10.677196 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:10.681197 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:10] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.516843 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.521847 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.526845 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.531845 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.534846 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.537843 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.541878 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.546844 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.554876 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.556843 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.561846 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.565874 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.568850 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.571870 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.574864 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.583347 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.586348 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.589346 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.593347 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.594347 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.606346 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.607373 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.610348 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.618381 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.622348 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.625345 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.628346 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.630363 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.635346 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.637362 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.647368 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.651348 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.661352 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.665350 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 09:47:14.668350 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:47:14.673351 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:47:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:51:56.940331 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:51:57] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:54:32.703078 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:54:32] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:55:57.447225 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:55:57] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 09:56:05.017184 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 09:56:05] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:06:12.387184 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:06:12.393689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:06:12.397696 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:06:12] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:06:12.411208 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:06:12.418209 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:06:12] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:06:12] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:06:12.423210 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:06:12] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:06:12] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:06:42.491492 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:06:42] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:11:54.356708 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:11:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:12:00.109011 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:12:00.113065 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:12:00.116586 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:12:00] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:12:00.124104 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:12:00.132616 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:12:00] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:12:00] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:12:00] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:12:00.164175 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:12:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:31:48.170270 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:31:48] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:31:48.216272 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:31:48.248309 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:31:48] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:31:48.267300 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:31:48] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:31:48.294035 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:31:48.342022 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:31:48] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:31:50] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:46:47.561036 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:46:47.566048 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:46:47.571048 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:46:47] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:46:47.585053 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:46:47] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:46:47] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:46:47.600036 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:46:47] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:46:47.795013 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:46:47] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:47:35.783321 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:47:35] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id//690626cfd3d7adc37cb3fc94 HTTP/1.1" 404 - +INFO:root:2025-11-07 10:47:36.834524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:47:36] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id//690626cfd3d7adc37cb3fc94 HTTP/1.1" 404 - +INFO:root:2025-11-07 10:47:49.201826 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:47:49] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id//690626cfd3d7adc37cb3fc94 HTTP/1.1" 404 - +INFO:root:2025-11-07 10:48:45.145061 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:48:45] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 304 - +INFO:root:2025-11-07 10:54:38.602488 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:54:38] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 304 - +INFO:root:2025-11-07 10:54:54.392507 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:54:54.396507 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:54:54.399507 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:54:54] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:54:54.407513 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:54:54] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:54:54.418649 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:54:54] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:54:54.422159 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:54:54] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:54:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:55:34.593154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:55:34.599154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:55:34.604161 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:34] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:55:34.615154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:55:34.625234 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:34] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:34] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:34] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:55:34.635668 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:34] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:55:42.221940 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:55:42.224938 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:42] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:55:42.230962 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:55:42.232938 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:55:42.240938 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:42] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:42] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:42] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:55:42.276633 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:55:42] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:56:06.044103 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:56:06.047103 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:56:06] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:56:06.050112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:56:06.056108 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:56:06.060111 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:56:06] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:56:06] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:56:06] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:56:06.088131 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:56:06] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:59:11.853246 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:59:11.854248 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:59:11.860245 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 10:59:11.866246 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:59:11] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:59:11] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:59:11] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:59:11.892246 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:59:11] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:59:11.902249 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:59:11] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 10:59:15.006613 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:59:15] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 304 - +INFO:root:2025-11-07 10:59:19.134768 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 10:59:19] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe06e779119ff4d421aeed HTTP/1.1" 200 - +INFO:root:2025-11-07 12:13:43.644177 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:13:43.646177 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:13:43.652176 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:13:43] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:13:43.661176 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:13:43.667505 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:13:43] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:13:43] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:13:43] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:13:43.685017 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:13:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:13:46.308085 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:13:46] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 304 - +INFO:root:2025-11-07 12:13:49.786943 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:13:49] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe06e779119ff4d421aeed HTTP/1.1" 304 - +INFO:root:2025-11-07 12:20:56.003641 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:20:56] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 304 - +INFO:root:2025-11-07 12:21:21.802999 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:21:21] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 304 - +INFO:root:2025-11-07 12:37:19.600180 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:19.605187 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:19.611186 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:19] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:19.618184 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:19] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:19.630700 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:19] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:19] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:19.640699 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:19] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:22.300656 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:22] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690626cfd3d7adc37cb3fc94 HTTP/1.1" 304 - +INFO:root:2025-11-07 12:37:24.043343 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:24.048343 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:24.051344 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:24.055352 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:24.064351 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:24.080877 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:24.118406 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:24.122405 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:24.128923 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:24.133933 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:24.141932 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:24.146934 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:24] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:30.324414 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:30] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe06e779119ff4d421aeec HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:32.011584 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:32.014584 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:32.017102 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:32.022095 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:32.027095 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:32.040096 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:32.097610 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:32.100609 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:32.103615 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:32.109615 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:37:32.114614 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:37:32.123134 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:37:32] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:38:28.073081 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:28] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe06e779119ff4d421aeec HTTP/1.1" 304 - +INFO:root:2025-11-07 12:38:32.049863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:38:32.057862 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:38:32.061864 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:38:32.064863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:38:32.067867 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:38:32.078866 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:38:32.112893 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:38:32.116893 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:38:32.121904 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:38:32.127903 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 12:38:32.131903 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:38:32.139084 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:38:32] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 12:43:43.059966 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:43:43] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fb7dc779119ff4d421ae9a HTTP/1.1" 200 - +INFO:root:2025-11-07 12:44:58.292208 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:44:58] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe06e779119ff4d421aeec HTTP/1.1" 200 - +INFO:root:2025-11-07 12:45:04.484271 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:45:04] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68f4d3e5d12201e20d8b6dad HTTP/1.1" 200 - +INFO:root:2025-11-07 12:45:27.080595 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:45:27] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe044d79119ff4d421aeea HTTP/1.1" 200 - +INFO:root:2025-11-07 12:47:11.163602 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:47:11] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe06e779119ff4d421aeec HTTP/1.1" 304 - +INFO:root:2025-11-07 12:48:08.226397 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:48:08] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68f617bfd12201e20d8b6daf HTTP/1.1" 200 - +INFO:root:2025-11-07 12:48:13.802759 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:48:13] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68f4d3e5d12201e20d8b6dad HTTP/1.1" 304 - +INFO:root:2025-11-07 12:49:07.876456 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:49:07] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/6847f02297eb82bb3be50aea HTTP/1.1" 200 - +INFO:root:2025-11-07 12:49:10.609556 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:49:10] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/6847f02297eb82bb3be50aea HTTP/1.1" 304 - +INFO:root:2025-11-07 12:54:19.450027 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:54:19] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68f61709d12201e20d8b6dae HTTP/1.1" 200 - +INFO:root:2025-11-07 12:55:04.466271 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:55:04] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe04a179119ff4d421aeeb HTTP/1.1" 200 - +INFO:root:2025-11-07 12:55:09.760545 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 12:55:09] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fb8f5979119ff4d421aea0 HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:30.971488 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:31.015487 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:31.019504 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:31.021487 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:31.029502 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:31.034488 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:31] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:31] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:31.054999 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:31] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:31] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:31] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:31] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:31] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:32.255325 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:32] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:33.695664 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.697664 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.698665 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.703663 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.706664 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.714664 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:33.735639 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Class_Niveau_Formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:33.757643 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:33.774159 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.784157 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:33.789158 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:33.799159 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.802159 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:33.870692 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.875202 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:33.879204 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:33] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:39.524513 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:39] "POST /myclass/api/Delete_Stored_Downloaded_File/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:39.586511 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-07 14:23:39.588513 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:39] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:39] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 14:23:56.975158 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 14:23:56] "POST /myclass/api/Store_User_Downloaded_File/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 14:25:53.317236 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 14:25:53.317236 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 14:25:53.317236 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 14:25:53.317236 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 14:25:53.317236 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 14:26:11.651985 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 14:26:11.651985 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 14:26:11.651985 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 14:26:11.651985 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 14:26:11.651985 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 14:26:49.858129 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 14:26:49.858129 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 14:26:49.858129 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 14:26:49.858129 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 14:26:49.858129 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 14:35:27.633321 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 14:35:27.633321 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 14:35:27.634322 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 14:35:27.634322 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 14:35:27.634322 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 14:35:34.238789 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 14:35:34.238789 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 14:35:34.238789 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 14:35:34.238789 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 14:35:34.238789 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:01:23.918797 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:01:23.918797 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:01:23.918797 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:01:23.918797 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:01:23.918797 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:07:27.276359 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:07:27.276359 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:07:27.276359 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:07:27.276359 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:07:27.276359 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:08:30.774480 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:08:30.774480 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:08:30.774480 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:08:30.774480 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:08:30.774480 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:08:54.830168 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:08:54.831168 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:08:54.831168 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:08:54.831168 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:08:54.831168 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:09:29.317388 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:09:29.317388 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:09:29.317388 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:09:29.317388 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:09:29.317388 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:10:12.126281 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:10:12.126281 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:10:12.126281 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:10:12.126281 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:10:12.126281 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:10:41.514990 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:10:41.514990 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:10:41.514990 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:10:41.514990 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:10:41.514990 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:10:55.843881 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:10:55.843881 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:10:55.843881 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:10:55.843881 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:10:55.843881 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:12:08.982670 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:12:08.982670 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:12:08.983670 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:12:08.983670 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:12:08.983670 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:12:31.232894 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:12:31.232894 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:12:31.232894 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:12:31.232894 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:12:31.232894 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:13:00.142737 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:13:00.142737 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:13:00.142737 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:13:00.142737 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:13:00.142737 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:14:26.656893 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:14:26.656893 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:14:26.656893 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:14:26.656893 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:14:26.656893 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:15:27.638592 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:15:27.638592 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:15:27.638592 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:15:27.638592 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:15:27.638592 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:17:34.040155 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:17:34.040155 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:17:34.040155 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:17:34.040155 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:17:34.040155 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:19:12.629094 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:19:12.629094 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:19:12.629094 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:19:12.629094 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:19:12.629094 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-07 15:19:19.207283 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-07 15:19:19.207283 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-07 15:19:19.207283 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-07 15:19:19.207283 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-07 15:19:19.207283 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-07 16:42:00.069525 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 16:42:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-07 16:42:03.835220 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 16:42:03] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/68fe06e779119ff4d421aeec HTTP/1.1" 304 - +INFO:root:2025-11-07 16:54:49.747169 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 16:54:49] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690df2ec995b26cde9611890 HTTP/1.1" 200 - +INFO:root:2025-11-07 16:54:52.464197 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 16:54:52] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690df2ec995b26cde9611890 HTTP/1.1" 304 - +INFO:root:2025-11-07 16:54:55.809017 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [07/Nov/2025 16:54:55] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/zFkN2PICvlk896szbnhZgOaL8Pfnm3cLKQ/690df2ec995b26cde9611890 HTTP/1.1" 304 - +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 10:58:11.193624 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 10:58:11.193624 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 10:58:11.193624 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 10:58:11.193624 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 10:58:11.193624 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 10:59:17.199435 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 10:59:17.200434 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 10:59:17.201434 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 10:59:17.201434 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 10:59:17.201434 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 11:19:07.753636 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:07] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:09.629084 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:09.635083 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:09.639082 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:09.648579 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:09.650578 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:09.677072 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:09.680071 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:09.681071 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:09.686072 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:09.689072 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:09.694071 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:09.711301 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:09] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:12.583730 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:12.585731 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:12.587729 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:12.596736 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:12.606241 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:12.626954 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:12.628953 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:12.631956 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:12.636955 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:12.640955 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:12.645955 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:12] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:21.089992 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:21] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:21.131998 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:21] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:21.155540 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:21.979243 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:22.015582 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:22.135251 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:22.639375 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:22.658403 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:22.663391 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:19:22.673385 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:22.691419 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:22.732774 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:22] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:23] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:30] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:19:43.155325 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:19:43] "POST /myclass/api/get_Class_From_Internal_Url/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:05.699749 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:05] "POST /myclass/api/Add_Update_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:05.818641 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:05] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:09.997089 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:09.999089 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:10.002104 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:10.006618 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:10.011634 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:10.013636 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:10.015635 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:10.029651 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:10.035635 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:10] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:13.310878 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:13] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:15.067718 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:15] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:23.446037 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:23] "POST /myclass/api/Add_Update_UE_To_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:23.615384 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:23] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.246227 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.247227 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.251735 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.255735 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.269737 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.298735 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.304738 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.312736 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.321738 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.331736 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.336744 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.340742 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.346743 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.353255 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.358256 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.365290 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.367257 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.374301 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.385257 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.388256 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.398255 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.401256 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.403256 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.411258 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Class_Niveau_Formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:33.474922 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.477921 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:33.481923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:33] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:35.775035 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:35.778028 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:35] "POST /myclass/api/Get_List_base_calcul_note_class_and_ue_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:35] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:38.604331 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:38] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:41.849811 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:41] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:50.172067 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:50.174069 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:50.177068 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:50.178093 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:50] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:50] "POST /myclass/api/Get_List_Type_Cours/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:50] "POST /myclass/api/Get_Competence_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:50] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:53.034695 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:53] "POST /myclass/api/Get_List_base_calcul_note_class_and_ue_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 11:21:53.065715 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:21:53.068719 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:53] "POST /myclass/api/Get_Given_Unite_Enseignement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:21:53] "POST /myclass/api/Get_List_Unite_Enseignement_Planif_lines/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:22:05.226467 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:22:05] "POST /myclass/api/Update_Unite_Enseignement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:22:05.333735 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:22:05] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:22:09.393991 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:22:09] "POST /myclass/api/Get_List_base_calcul_note_class_and_ue_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 11:22:09.428987 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:22:09.429988 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:22:09] "POST /myclass/api/Get_Given_Unite_Enseignement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:22:09] "POST /myclass/api/Get_List_Unite_Enseignement_Planif_lines/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:22:32.070183 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:22:32] "POST /myclass/api/Update_Unite_Enseignement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:22:32.140298 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:22:32] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.114148 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.117149 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.124152 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.130149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.134155 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.161153 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.163154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.166712 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.170709 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.178711 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.182746 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.198707 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.200710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.204711 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.210709 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.220710 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.229752 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.234709 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.238710 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.246750 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.253744 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.261745 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.262747 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.270865 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Class_Niveau_Formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:12.786300 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.787301 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:26:12.793637 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:12] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:26:59.309273 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:26:59] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:27:10.727045 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:27:14.277224 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:17.535484 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:20.725053 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:24.908926 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:28.625720 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:30.956528 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:32.947055 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:34.467671 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:35.974840 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:37.456588 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:39.466442 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:43.483527 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:45.309489 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:46.923394 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:48.452969 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:50.069556 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 11:27:51.522765 : L'utilisateur destinataire de l'email est invalide +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:52] "POST /myclass/api/AddStagiairetoClass_mass_for_many_session/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:27:52.010057 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:27:52.013064 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:27:52.015060 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:27:52.020057 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:52] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:52] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:52] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:52] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:27:56.231359 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:27:56.234375 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:27:56.239366 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:27:56.241364 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:56] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:27:56.250377 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:56] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:56] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:56] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:27:56] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:28:01.092066 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:01] "POST /myclass/api/Get_List_Sequence_Planning_Model_Header/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:28:06.311185 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:06] "POST /myclass/api/Get_Given_Sequence_Planning_Model_With_Option/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:28:20.927501 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:20] "POST /myclass/api/Apply_Planning_Model_To_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:28:20.970016 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:20] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:28:41.710577 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:28:41.712568 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:28:41.716084 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:28:41.719113 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:41] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:41] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:41] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:28:41] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:29:50.992873 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:51] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:29:51.008875 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:51] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:29:54.155762 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:54] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:29:55.083662 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:29:55.085660 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:29:55.089678 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:29:55.091663 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:55] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:55] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:55] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:55] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:29:59.853344 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:29:59] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:30:03.875899 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:30:03.877900 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:30:03.880901 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:30:03.882900 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_Competence_Domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:30:03.885381 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:30:03.889903 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_List_Partner_Basic_Setup/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:30:03.900907 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:30:03.905906 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:30:03.907905 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:30:03.913438 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_CRM_List_Opportunite_Etape/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:30:03.924437 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_Competence_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_List_Partner_Basic_Setup/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_List_base_document_automatic_setup/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:03] "POST /myclass/api/Get_List_Partner_Basic_Setup/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:30:07.372128 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:30:07] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:32:45.702516 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:32:45.712514 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:32:45.722513 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:32:45.728547 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:32:45.732559 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:32:45.759534 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:32:45.764516 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:32:45.771515 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:32:45.777514 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:32:45] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:15.573033 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:15] "POST /myclass/api/Automatic_Creation_Groupe_Member_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:15.641130 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:15] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:20.914113 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:20] "POST /myclass/api/Get_Given_Groupe_Inscrit_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:30.220757 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:30] "POST /myclass/api/Delete_Groupe_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:30.283758 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:30] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:42.307569 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:42.311586 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:42.315569 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:42.319569 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:42.323569 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:42.331569 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:42.349587 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:42.351569 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:42.361594 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:42.368595 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:42.375116 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:42.381107 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:42] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:44.003178 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:44.006177 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:44.009179 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:44.013178 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:44.017218 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:44.028177 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:44.032207 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:44.039179 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:44.048183 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:44.054183 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:44.059183 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:44.066579 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:44] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:45] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:46.148704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:46.153707 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:46.157720 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:46.163719 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:46.167717 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:46.172245 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:46.177254 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:46.184252 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:33:46.191784 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:46] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:48.013517 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:33:48] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:33:54.276546 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:03] "POST /myclass/api/Accept_List_AttendeeInscription/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:34:03.313511 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:34:03.315507 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:34:03.318510 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:03] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:03] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:03] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:34:45.437473 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:45] "POST /myclass/api/Automatic_Creation_Groupe_Member_Inscrit/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:34:45.504991 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:45] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:34:49.074514 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:49] "POST /myclass/api/Get_Given_Groupe_Inscrit_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:34:51.429810 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:34:51] "POST /myclass/api/Get_Given_Groupe_Membres/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:35:06.607314 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:06.608313 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:06.613313 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:06.617358 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:06.620313 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:06.625342 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:06] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:06] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:06] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:06] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:35:07.345013 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:07] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:07] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:35:16.263149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:16.265149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:16.269147 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:16.273149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:16.278156 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:35:16.283154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:35:16.298670 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:35:16.304350 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:16] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:35:44.083931 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:35:44] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:02.008518 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:02.011547 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:02.014534 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:02.017546 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:02.025519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:02.031522 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:02.038519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:02.048519 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:02.052519 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:02.056546 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:02.063553 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:02.072521 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:02] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:03] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:05.107594 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:05.113619 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:05.117596 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:05.122117 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:05.126161 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:05.134119 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:05.140627 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:05.141635 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:05.149768 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:05] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:07.924844 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:07] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:30.708537 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:30] "POST /myclass/api/Add_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:30.792111 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:30] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:32.690412 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:32.693414 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:32.697410 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:32] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:32] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:32] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:35.445294 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:35] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:39.183138 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:39.184151 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:39.187702 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:39.192704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:39.198704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:36:39.202704 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:39] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:39] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:39] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:39] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:39] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:39] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:47.571166 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:36:47] "POST /myclass/api/Get_Accepted_Insription_From_Session_id_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:36:52.501344 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - 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CONVOCATION EVALUATION
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A l\'attention de part 17   part nom 17

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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CONVOCATION EVALUATION
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A l\'attention de part 16   part nom 16

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 15   part nom 15

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 14   part nom 14

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 13   part nom 13

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 12   part nom 12

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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ttx9kB7oARSbstqdiAxrubiiy9e/KDUZTFixIji29/+dvF6jWLljM4hE1onoKCVxNCJxx0/ScGtVqTRhx4WJbhrtTvVgtalVGw6paH3lNS1R+pDbRaYa6Atar11BsdrVA+6GlZefoXYa/vUkxNllZoVujSOOuqoSGijKnLkCfvvv3/xjW98o/jZz35WeSajq8iE1glQztASpSUnyXHDo4+0NKuvudrqHRq/pnKdvlnS2Z/SoCqywrLLxof/byboAhi+8y7FSccfP4lkUzX+/Nlncc6Bxv33ewER6AoZOHBgJLSzzjorxtMSDjnkkGLqqacuXnrppcozGV1FJrROwI/wwAMOiD2KZH0S6OnrdTz7jDMrzyCND4rbbh1fXHnFFcWEUrsQa+7kE0+KzeD6ObUBUYRQXElqm+UxYcKEaKkYywavvfpaVKEw0ehnP5u83Qe4alq27r7rruLKK6+IY/fKI/lYO3fdcUdU2zBoheDhisstH+cI/Ptf/4ok+2awQB3Hddde26qDRrXX5+iJaWn6vBLI9pnXX3stNpub5JRalCxcLUvXh214kBdK8J4bwvtJCHEra8G1oCHHGk4QZ9IOZrbCtddc0+pmagV7/rnnw3WqT3zNAq1uCyywQIyVvVU1ZpDLOVP4PRhhmNE9ZELrJMhVa9bWGI5E9COS8SHmaCHDhMcmFCuvsGK02jSLU+7Yfdfhxd8DqVGw1VitWdpnNGOLBZ195lnxOWqxpLtJ5OhL/P7ll0cXTEO756nIvvTi5HdylhapH83xmsM1zO8xfLeosKFUgGoF9RCvLbvU0vF9SE2sSo/jyuH//T14rbWKmaabPpDHNTHrRh7J+bJK7Z/8ESAXTeaOy3EfHlxuIM7ovc7N5whTgvM2Wcp7nf+Siy0eruXEsXkJelldky2GbR7/1iR/4nHHRRWT+eeeJ/6b9uXYqH78pIaqbbPBTYp1Nm+4XtV9uiNHjoz1aO/X6E3N6BwyoXUSMlXkghDCRx/9KloLCGvYJptG6wSBbLDeesWcs85W3HLTzTGmRjfMTMlLLrooih8efcSRUWLHSLaHHngwWj2nnXpqVKhYZsBSxeWXXlY8+cQTMWhPOYJkkB87i4c8D6KqbmwXj2PB0QD7RSC3zYcNi+oYXGMqE/6f/I/Xvnf++ZHwBq64UiC0X8XPIhuqGCP23CsORmFZcYmJNl595VXxbyoXSIXFSdEDuTjHX/z8F9FaYgUOXGnluO1HH300Cj9yIQ0Kds2WW3qZcE4vxqG/yJCqSXUxKcttgfnmLYZuOCT+fd+99xazzjhTsd7gwcXLwYrUkG8bdOLWXXudYsnFF49Tqpod48ePj4Q2dOjQyjMTscsuu0QLrZY6cEbnkAmtCzjogAMjsXDfLr/ssijYaI4lICFWkAWZ1CQeDKSFLJIg4p2BMPxtelLCmFNOjduhFptgAPJss8wcR+VxXU864cRIcIazfPy7SWcZiN3df//9USNss0CurBykSSljv2ABcJMfCK8Dkl1p+RWiy8lC+02F0Ej4fPJxy/g5U6XE2FhaZKyd57CNN4lDfa8O7ue++4yIIo+sQgSJqFmsW262eSTPDdZdP36GC/lEsE642OsE6+/SSy6J7rp9seCq41801hZaYP5i441aFr5hKa71NcFiLEN8jTqu7SDxZsfYsWMjoW233XaTxM+cx3rhhjVPsFw7Ip2e0TYyoXUBjz3ySCQfAobbbr11scA887beXZ995tlIOttvs21rgsBAXuSy1x57xL9pdtUjNPGohNPHnBbft8aqqxXbbb1NJLYdtt0uZlSrM4AmMbGmNg9kRrrH+332xhtuiJLZYnzPlSaVs6S4a4nQjNwzET3Fo8waRXJcym222iqO5nNOtvtksLB+99vfxalMhq0gK8fGajLUZN999okWmOf3G7lvMT6QqmMjUrl9OH7bMh+UG55mmiZUExphyLlmm32ycXrNRmi+D+RdD2PGjGlNCJQhPjhkyJBi5kDauUm9+8iE1gVE2erVVy/ISLNgtttmm1byQhaIAhmkhXZqsLpi0qDyYzb6zQLfdaed49/A5URorJ8EwXiksMduu7daeyynJGedoIREHE98Kk2Gop5L0lrMj7ouCw3pgcQB62iV6HJOJLTVVlk1LMoWQrPQuHTzB7KWDACEJYngWIzYA0Tef/El4nVARmkmp1kFpsdTsaW/xj3lOqf6sj9/9ue4gFl1ZVQTmilS3PX9R+0X9+/x29/+NsbWmoHQJHuQFCvrimBFp++pGgcFSxOhfa+UTAJS6msEK3f2cMPraMlPRn1kQusiTCufdqqpopw2kcQyDAMWR+LSDdlg/Sgtve5a68T4Fbzx+hvRimP9iLdZ5CZMfecb34huWoKMKAlw2zI6b9gmm0Rp68sumfgeQD5mTxrB53XurvosJDr+1ltjhnDxhReJpGLwC3dTgmDpJftHUpFZXbRfvxjjKlsZ3FXzNpWqbDJ0aIxjsUgJK7KyNlx//bg9x7fNVlvGshZxQc+T3W6xQveMi9z18rfkA8VbNXBp/mkZYm5zhvchU3B86wXicgMwf9TjhOOOj27boGC5LjT//F9q7Omiiy6KROUx11xz1SXX4cOHF1/72tci6ZXBsps/nMOywb034T2je8iE1kWYiH5+RZG1LF0NAvasK3LXpjeR3U5kBqySG66/PtZQkdqmIvvC8y8UZ5955iTlCkAvi5Ui/mbOAGL4wdsTq8wTLPwTjjsuFv4iWMkGUt1KOeCxRx6N+9p3xIjinrvvjllKcTlkIzD//UCkV1919STJBqQx4dHHomu56847R3IyYZ5Vctkll4Rj2jUeE+vSXACquo7VOZtZYEpV6k/0GdanbdiWbZbnjCY434suuCAmGxIkRJS62JfPG1IDYpimv9cadTcloG5szjnnjGQ2SyBc/54SrPFqqxNYaF//+tdjtrMMvx2Etnqw+DO6j0xoPQg/7OpsZBksq1o//lrw3ra2BQjI++qhM/srI51H9WfrHZPn6x1H+kw5MN4ReH+tY/iywJo69NBDi//3//5fzFzec889MQ4mY1kNx67W7H/+538mIzRZ6GmDS7399tu3WUjcFbC2kT2r0X6Ui6RuhGa5jo1GJrSMjC6A5bnEEktE5YzzzjsvFiCTBRo0aNBkxITEEZai2meeeabybAtYeSw7WdBGgdV9d7DC991332LuueeOGVT6a/avuNexsCRZvm0lMnojMqFlZHQB48aNi0SEKCSCAFEgEEmLauy3337RQqNUW8aNN94YXdHLSrHTtvDQQw9FN7WeheV1+3JsCy20ULHFFlvE1qrRo0cXu+++e7QivcaylIi49dZbY6KlryATWkZGJyGjvddee0Vi2GyzzWJgH8HUIzQu5xFHHBHfX22hHX/88cV0003XocZ0rVEsQJahAu9qIEey3gsuuGBxzTXXxOlf1VC6s+WWW8Z9Oh4Ep+Wtr+ArQ2iamX//ySfdmp79ox/+KGYNywN2O4zwo/bDTo8vCwYC6zH99UeTKn04Jouy3rGl41bWIZifejctRNckyeFwoW4bH7b/655TEknHUu9YexpctSShzfqBRGjUZ6trBEEMjXta3YDOLURAHalBe+KJJ+I2ZpxxxtiJUcbDDz9crLXWWsWGG25YPPvss5Vna0O3hffZlsc+++xT85h7I/o0ofnB+6IVoypRUD2v+t0C7Apk7VStK3jtLE4/bWwsVzCIV8X9LjvtVFxy0cU177SdgXPkggj4thfotfxV3pv2/nBwTcrgdiiHUM+meb0M2USlGIp+773nnmK2784clUXUnN1w3fWxpGLsaS3XxKR0RcTV228U1LRtPmyzYovw2HTjjWOhrwzolCzdYGVpVeJCnnNOS4cIcOtkO2uR+WGHHRbdvHIDuljXkksuGcmuPSCh1VZbLRIQIj399NMrr7QQLJFIMt5+7x0Bq0yZiW0Z0tJXauD6NKFdeP75sfZqrtnniEWYKtPXWn2N4uILL6q8o3M48/RxsfhVmUJnMXznXeNntSXtstPOxYDwQ1Y0O3znnTskOVQPWq2WX3qZ4sD992+X0EC5hJalatICbVczTDNtsdfuu1eeaanId8yzByK/9+67I3kedsihsbQCkJzzGFO5JvuOGBkJrtb2G4ErLteXOmPsA9XTukb413VdbZWBxU+mUIEtEkME//3f/92atXTtDz744OhyKmGphsSBz2hPS2AVDRgwoDjppJMqz9QG8uFmUrq1DY9jj20RCXBDu/fee6PVZh+dwc0331x85zvfids74YQTOvT7aXb0WUKz0FWvq54nfZO+LI3gZfPa+8456+xibFiQquqrK70fDz/YscEiI5Nz7NFHRwtt7JgxlVeL2BhtqrjnNFLXm5q+x/Dd40J/qjKujFQQi1FRapJe1sytgZ0ckXqvcixG07v6sdODJcRStHg1fas9m37qqaPVd/+998Vzk7nSbqUX1Pu1WlH6AL2eswYL66EHJ7egxFwU+660wgpx2/Dee+/FImAFuwp9dSUgq6Qscs1VV8em+tMq10StmwJawekE21Wf5lhYbu2Vn7SFq664MvaKnlGxUNSt6UCYcbrpiksuvjiGFB4O56a42f7uDt8pUlYHR/HDsafv343E8Tz22GPx/5U32MYpJ54Yrfh6GUBzAZCAYL4hJwk77rhjzCLWKr84++yz42fuumuiwgi3sV+/fm12OigPETdLRJYepLwdn/Nl5Rm4Uq9Uph6ECyQNbE9crS+gzxKaRm4tM/oY6y0g0jwayRdbaKFi6f4DotyPglDkAdddc01c4Bb0CssuV/RfbPFIQInQnnvu2agiQS6HxTXXHHMUxx97XM07XSI0Wl+AKFZcfvm4PcW0T4fntQnZH7d47mBVbrDuulFayF34iMNGx+PTAYAIL734kkBg9xaLLbxwlONxjI5FfI9G2BKLLBq3M2DJJSLBkNz54ovPo8tZj9Asjs2DW2x7yBn0hSIsVhm89eZb4Zr1i/2dzhPx1iK05HIiVm1gi4TPkAyy7TPHjYuvVcP2tGElMq2FRGga5sGi3mmHHeJ3rVD48ccmxK4I595/8Zbvy3eCjEkzcZfTudFz87pC4FdffiV+x66j72Hw2mvXdMO45mJlSEA5RDn2tffee8fMYtK+KyNZaLfffnvlmZa4V//wffqO60HMTVwuEVlyOREneSnJBoQn2N8VCyupgLAs3+kFqiXtoc8SmubnmYNrckZwE2vBj8iit9ieDz8GdUSar7lPN914Y6yetygQhsWpiVoMzOviYbDJRkMjmamm1wmwblgE5HVqVfLrx0RoiPbmm24KbueOYVszxnYmlhi5n9lnniU2ctt3tLymmSYsxmMLEj8Dllgy9o7qq/zNr38TBSQlOqh8fHf66Yvttt66ePH5F6KlQRvt0YcfidvVZsUdcx7iTDoN6hEaiOul/QKCd84C0oB8+803f7FVRQ+uHqEhMpbKWmsMig3sSJZuGUtvkWCV1FrE4nP03tYZtGZdsUOEZn/Dd9k1Xqtjjz6qmHuO2SN5IXPXhbyR75NopTYvRCoJQkZp5hlnKA4LriGwdLmrdwQL9sxxZ0QrTwzwD7//fbC8351M2ihhq0DmSIC2WYqBummaraniv1bnwh133BE/k9xC7xeM10HQFi699NL4OQ8WoX3PEW6c3F3kuUK4iYnP1TvW9uA34pgRZXUGtjeizxIaGecW16Q2oZHSsXD3DAs2QTvSjNNOF9UsLA7upR7GhPPPPS8ubtvUIM66o8d1wvHHx15M/YnkdR4sxUkSEJqFznrwWHrAgKi+odnbnRG56lPkQgEl2/kCOZLj+ehXHxVbb75F3DdCOOuMM1sXEjdquuByWogp6/dxWMxcPFYUzTNWR7/5F4gDbo8cPbpNQnvzjTejBUjT//XXXg+EsHyxViCYdFwIbaGwra2Di9IWoSEVmVBWJYvn5ODGnXLiSXF7ekw1r1djmy22LGYJBON7ExOsBYQm6cBKdM2QFXf7kUownIXHeqP+QWSTxbvQAgtGtw7JacJfdeVVohXuBoUIJTeQKVUPN6idg+tIj64WEJFuAATD1StbcRtttFFsNK/l+pmM7jPHHHNM5ZkiuntiV21BfC0RmrkDJ4breOSRR7bGvlhn5ba6rmDnnXeO23rggQcqz/Re9FlC0z9JedWP/U9/nDwlTaMMoY0IbkICqZ2ZgrWjaZpgoYW6RXBTEhBJIjQ/ZISmcVt/pB5DUjkeb4dFX41koZHS1l8pfpFcYSqtSyy6aJwzkNQqIqEF94ySB1fQMBMa+sjBMe4ZtgeIGaEhksBoLVXpwdKcMyxO1thdd95RDB3SIsbIxWqP0GCbQFZij9RmHbPsZ0JnCE0pB0JbKrhVnneN9t93VHHAqP2Kn747ucqsZIv3k2MSm6sFhDbLjDPFa+G6vfPjd1pDBNzPLTYdFrch3nlnsIo01FMMSVnQg/Y/oFgwkJYe3KUCIR16UIu15magnEVzPbcYEdYavsICVvKAADSUp+8L1g/fn0yk76saLFyfkTgArUg+X61eCynG57uk4rFpIN5dd901fv6SSy6Jvz1kuEq4uZVnW3QW6QZ4dLhWtn11Sbqqt6LPEpp6K9LVCMg0ppdeeDEG0h8JrtAbb7wRhQUXCIt2zWBuc3+4R2Ip3i9wy0Xx+vLhRydlLjhL8tnr44LLiYxIViM0ahZgJJzt1vpBpxharYZsP+D1w8JjSaUgs6A3wj0p3JHFbd6vzBIQg2OhDFxppThzQJDb+5SBWGyykJIhLBHWigVD4QJJdJTQiDCKLYnXsVhS3A86SmgC3q4ZeR8k/Ga45vC3QD6uUSLzMsSeSBvRmytXr1vYyMr3EF1sMbTgLlaD2gcy42ZyG1nZNNgWDC5ymkPA8nJ9VgnWmxtSivX5DUgI2RfLeZqppoqkVw3freJVBLBouAmJzYFz5f4puK11bo7dIJRhw4bFvyUilg/WarV1Ja6mNi2NtNMnqk3pwgsvjGUfKXiv9er99xsj2W0KVSLL3o4+S2hA/sZdmEWDLFhBFpusJpw1blwxb1gA3MYVllsuvkbRATFYrEcdcUSU2Vk8fA6B9F9siWKGqQPJnHBi/LxYm8Xhjr9quFsikR223bZmPGOn7XeIckMsl1oQYxFbsshWWWnFSFrcvl9++Mu4UO0fgVqgSiiOOerI+DmLltvl2EkMiaMZvoJkxAfFo7hm4nPabmQ5p/n2t4OrOrlbnCBhgcimm/o7xbprrT1J1o7lSt4HubtGAvG2l2YHSMLIuiZ1XHJIrD3nxV32fXhPrUxgLXifwDh3Tu3XOuusU3zra1+PmeBqIMT11103hgqQ6DprrhVvauruqKOA70YNm9gZiaMUwLe9/oF8HSPrbNmlBkQpo2o4np3CzQMB6N3kxoLtiGkho1pAloL7Jqa7bty8ZK0lKPcQVyMzxKJDdiuF712h7PXXXx/3SZkj7bNRcCzc2epi3d6IPk1oYMGTfD76yCMjQUnnlxUHHnrggeLYY44pjgiWiwLSdMcFP0Iu4ujDDouTkLiBSLL8Q1d+wYo6PLyHq6rMw3ar8dwzz0bN/+q2mDJefvGl4pSwsLhTF4c7stgZWCykd0YHF/LoI4+KRJoWIogfOT9lCuJnrI3Tx44tjj7qqJiweO7ZZ4rxt9wag9VKRCQl0rZrgRXix+19r7w8ae8hF0sZCEuHy2LWgPela6IMxnkmEUrvMUNAnNE1OuWkk+ICTe5OW2AtcanEpSxmD8FrNW/lQb1lvBOs8NPGnBpczmPCMT4ZLWKuZPl7PSZcFwmAcWMnFqe+EazX9D1K+ogl1gLLMcWcEFqKLSIZMTV9lLW+f/tfKtxgEBKXUdlFuTgWXHPEMn24AZuf4H3fDTcmNyLXwTBipN5eJ0Bn4Hw2DzdACYdarVK9DX2e0DJ6JxAeC2XjjTeOE5Fk8rQbLRcs6a7on3EDufYkwk22Yg13tUxhhx12iITG4ko3KC4lIqrntrHsEAfFC1YY8itnet081w3Wpe2Krflb4Ss31j64oMjc5xqZjXRdJBrEz2qFSnobMqFlNC0ODO6x9iJV8SrsVcuLKdUreG0LssISLLKaEiQXBQu4K2B9OS7EoxYsdQUgR5X8bQXWkbLPKfdQf8a1T2BxLh6OzeusN7Afz7Gi1LtdcMEFxXXXXddhd72jELftyjVtRmRCy2hKUI7gfqm7Qhq3BTfXYi+3DnUGLB6zHYQPlLp0B6cF116AXlIgWVl33nlntCAF++shFdd6kOQuw6yB9BpSRFqSD8o2kgvLmuKGNxKSDY6lrVBIb0ImtIymA2tF8Fz1uhYqrqISBQHyerGzKYk0wWmGGWZoPZ4rr7wyWmhlq6saYl/UaX12/1KdHfc6WX3qy9SscbdtXyV/T8GxmzilqV12vC+gVxKau5dslfqj6ocMZRnubuRsBPxTjEBRp6D7ezVqgHoC+juVUEhGSO9XB8QdswLbX4S7vXPoCHyG1ZG25ZpYBJQevqjcxZ2795RLIMrwuuC9EoD2gvT/CPtTha9jotpKsB3STIan/CXsrz189umn8b21YmG+VzEd8aKUBZTxQwTVWUFwPSUmJCuqz+E/8bh+H/flOrSHzz79rOW4KkXL1eC2KjlJfZmykYL3wB1sa0gKqIVDUqw7emUJEjzI2jY1q/tujzrqqFjiUU5mNBo33HBD3Kfe1L6CXklo2oL0La65+hqx586EIANvtc3svuuulXe14MLvXRBLBR4ouRlqsRTd3nHbxL66ngKi0bWgFKClRmr5SWZvalMauuGGsZjTQylBvSr1BPV0yiZSg7b4zRabbR4/r4zkqCOPjMT4+Refx7ow6h7lUhKEJPsr46iOTnFxrdqpBIvUlKe555gzll+Y/K7mDpCIYTFKX5SaDF5r7djmVA9333lXHJ9njJ7SiptuuLHySkvGjYv1ja9/PT58n5r5JQYE4KutH9X9A8N77Ne2ZKLL8N0rxfD62oPWLJ55un4wXX+nbTku5Tfq6xJcm4svuii2n3ld3y53mDWlrhEMEBbAr76hlqEmkEosEilbXsg2ZXIV5iJnbiCrrdEuZoJ9LLbYYrGNqiwk0NvRKwnt5PCjJxuj7kp9mYWs7cjfqtETWAA6BqoJwoJXh2SCeU/Dj1V1vMr37513XhzAq68SoYBU+SEHHVzcctNNxbHhrmzBkMZhedQCK1MRrXo0Vt3nYbFtV+kMOPOMM2K9mx5WjfeggV0NGhWJBIXF/cJ1U0+mfk0haT0rDiFrI3KNFbPusuNOsbDVtCVQCKsIV0eF81N0SystVbuXIRMoKK/Ql6qIurqFF1gwNryD2ripvv3tmAhQCa8vdkD//nGyksxg+ZogdfNAjQrUo+lGIXPp3ECczLXcbJNNohqK5ng9rX/4/eRWIcJeasn+cZ7qJRdeVKy28iqxX1UhMjz80MPxHDcZunEkyTlmnS32UiKgq666Kr5H98Cq4TdY7zqCmwrtMedXJhFEJx5nexrfxdpkM9PErEYDSbIov/Wtb8VOhBSj6wvo1TE0agOan1lg1GTLcFe97977Yk0XAnM3T1+cmi0V/x0htFdfeTXWVdUjmAR1TPoVq3/QLJiy9aOo00J7tmIteC25SgKzrBJ9is6tFhTmKppFHsAaYvkRsfRDFX+RxdOnCCrzNx06NJJk2uYPAomOGjGiGHvqmNgvitCMoKsFtXcsHJ0BwF1HkPZn27TT/K3mC8ztVNiqHq8aaWjw9wLBgJuNvs4LK8N31193veJrwdWUBZQIoKLxnammirGpai1+zeQKpkkkgRo8f6cOAiMCKWs89mhLkH7HQPS+89TzWcaFYXE7rjQIetzYsfFvXQmgQR/xp66CocE65jYiIEF1GUKERE67LXAfZWrVfJWLWIUi1JfZHrJToCsp0hY5dgdq52RSdS4k0YG+gl5PaNxO7TWpEjzBlHAL252bNYNELr+0ZRBFRwnNHXVQsDbKFk890N1yl6+V/v5dICrKDwpQWRVbBvetXBgrLvPKKy8XZ59xZnAZ54/HV8/VINCo8p5yBeg/1RCf1DFYbSxA5532wTUtt10lYvc3y6stQtMJgKCOqzRVc29db430iFFNl46EdDwtah7fbb3WZSAG+3uw0gTNrUMUhxx4ULQE5w9EZlGnWq69grXt702Cy1kNljgyTMSp2FcLmOvDKnZcWrdSD+exRx0dJ8mLnVaDy+2mQMASbg5kwiLbf9SoSCprB8vfNU9SQYeFm+R/VwhNszlrlPtp6HBb+OEPfxhjaD53ZkX+CLTaIRfPe5D1TtezJ3BxsNbth35bR6S/0w3ZemMBs2jFalNjfnvx1ymJPkloRBcpWmh9kb15JVgZJoP7mxtqcXaE0Cx8VeNUIF6riDCW8Z/wn1Yg3QJIQ+zFEFxEIXieYIjv/IFcuWqIJok8JliE+kZnDFYBWWkEVwviMyaVrx3I5I+VgLouiOnCYkq9lGJn3DrSR3/6Y0vjNLfTAtWjWYbm6/YIjcVDASPF60gZaQ9afeCqxUsvvhTdNFYlIoWzzzwrEtqF57dYXQmuJetUS1UiVsSGSDT0s8BYZ1xOC9/NRIznf4Jrd3CVxA63e4fttovXKwlN2iZC23/ffeMNxPlT20hlFUkpJVldZWyz5VYxxvn4hMfj36SP3AxH7LV3/I05X6GNlCw45+yz43EhBS1ZDz74YAzqJ3e3Ht56661WlYwDwneeQD3Dc1xrfZupj7Mn4BjVwBmSUhabrAXnLkwgacCi8zlFzrOF35Jj5WIjX3HE9jyYKYU+SWisFgvFoiNDY8EKZrOOkJ0WpY66nG2BFbXzjjtFy0zA2I9+uaWXiWKRt958S+VdLfEebqsYF2sRqVm0CbFd6KabY1sT62rjIRtNouKQ4HwHrb56se1WW7VaggQYWWiJ0Fgn5H8QTcqYandiYTjvMjpCaGJGCCoRmju6vlJJmDdeez0u9oErTSQ07/P+6sZud3FuqmuUCE0gXqKBJcRd427NFMiTa6aui6z01wPJiZGVgRxNX+cWJkITJ6U6cmAgCkQuDiZxlAhN/24k2op7W4aYpOuTCE3Dv+uy38iRMWsrXovwEqFpWSoT2rXXXhuPleVDv+z555+vaWFfHr4r7Us+p1RCVlrLlMlRMpopY9pTYEkmOaI03KUWkJPeYhbczME69/62Hm48ZhqUOx++LPRJQuPaITQW2fHHHBvdDYtZDIcaakcttPZgkYp7Cd6StVl+mRY5GHMa//Ln2oJ7p5x0chRklBmsBdI9Fl6t2IYFJfGx9RZbtGbTxAann3qa2KcKXELkPXSDIfFv0AdogSaV14SOEBpXjlt4eEWx9u0334qBf1YNt0N8jpLvjyrXn7XFRX3ogclnChx68MExHndX5bojPcmZcYEgiAyKl80XiIWFqk1omkBQ3P1ajfQHHXBgtMjS7ALqwjMFq+P0MS1KKGSANOWnhMPBgehc1/vuaVGrLYObzILV7wpXBgL1+0i9ngbEuE7KQ0CWXBbWYpa1TOobYn/+RW612qoSmSBucTQqxeJnMrgmr/ck/FZZfiwr06GQT9lVTP9/U1g7FENSjFDygzKvJAXilc3Vw5qsPO/x4DKrHaS592WiTxIaxViLWuzDD8tXpQ4sZRZTDE2Gzt2eW6WCXGN3NcTOWHlpbFs93HP3XcWywTqrjqEpyxDIZy1RmmWlCFaL0wDrSeCdFBDzfvWBA4t5gtVSq4A0LtRg+rOKUlO04+JiyuApa0DaXFuB7QTlKWJorMQyOkJoZIuiUkY4rth+c/750TIShIcjRx8Rg/FaicRUWEWs1VqV55rqvZcYpePfftttoxLGcccdF12xdcJCQ3DbbrNNtGT6LbBAvEmkWE0ZZjz4DvfdZ0Qk+h222zbGSZM776ZlX+efd15UK+EWU/z9qNKqVIY6Re8VS3NcBB7LiQ7bck1ZeYjAtr4b9p0Ws3o0bVAyscogZA+rG8hZnVtvvXV8r8wiUmOlSQBQuu1psBjXXnvtWCunZKTct+k1cTFlIsjYOSErQpasTjdoay2B9+B8JC5YekpYfEbtoHOqpzY8JdCrCc2PL6b+w4IToC6Dbr3FKnZFNsj/c+ngsPAlTP3tqQKh3R1/oFL6U4cFVJ2Z++tf/hrcwxWKb4cvrL3eP6KN3LNyRhPosokbKddYOPzoSf+oS0uFnldfeVU8NvVgguIsS1I89ZICxx9zXFxs5fmOyIVVZD+xvCC4QeUYHit1vrnmbtUkS6CCgRS4b21l1Iyos13uon+5xKmkgOuMYFlx3LIF5p2vuPbqiUWjZShMlQWddabvBisvHOusswXraHRx6KGHxmA5a5O7znphrbHmWEu14PqxElldvv+5wnGxnJKl4UbGVUSYjpvIowRHLVigJNvTcfmM40okzzJL5+gai69tWLHK0kOLlkWPoFhq1STseJEJC8e1o4XmcxQ4zBkoW0s9AXE67qN+0nI4w34lMwYPHtxKSuJ7XE5ICaR6EJOmdEtFxOd9d7aVBv9MafRqQrMIxR0MiKiusPeaEgOunXQ8GaDk43MLLeZPPv4kEscd4Qfl9XLxacKERx+NmTGB5q7AtKX7wkI99+yz40PcqLwfx8ByOTu4g0oxxJdYa/WAlJDTAftNbJ1xrlwvweprg+vFGk1w3BbjFsOGTVb0+cc//ilaaZRf21pQimhNUpI5vj5sv/payMixZFmH5jO0tQh++5vfFjdef33clmJn1hOJHHd6NwOzLalW7BSsJN9fPWIHBCleSknYxKty5hje++l7McbouGyrreMSy/I9OC7fUfW18tsRy5NU8B2xXFItGgUNPaaORzO5AtvqCn+Bc9aPLgjHecstt8ShKsikpxvDNbRzGal5vF8RhXStERvrENGxHLn9yLX6OnYEkg1KUlwP7qeuDpbdlEavJrSvKk46/oRo1cletgckN0dwN5PgYjMBiWoBYtGI3XB7NHhb6M0Ox2vxeiTNMgtYPdm5NeKjEgmIL2nxKVNBsD0t2SMWK8bHgpKsAIQlfpesMu7+2LFju51djcmniqUmG0pQYEojE1ovhLu/MoRrr7q6+FeVi1uGH66snoB5W5bOlwlTwzWhy6yJ8Sh/EKvraResu2CRJUJbc801I0EhBLG05K4lODfS2Yilp6r/a0E4YM8994zkwiIEvwmdCMsss0w89oUXXjgW+VZblF0Bq5ayrrIO23ajmpIT7SETWsaXBmULYkksMg/V9kQNkUOzg0XGNbZwZQ1BUF1tVjUZc0W5m+11EjQSrEUTpbiSSRnXdXUDkZnlFmqzarR6iZuRoS6ui+SIUEKKF08JZELL+NIg9iYZ4CH2JBhdzqY1M7hXSQpIQkCMjRVmpkC1G6nzAVlz86aE5SlQrx4OoZApEmNFqmrdlGNwkVlpyf1tNLTfpQJicbVafb09hUxoGV8KLGyxJlk1i4xlU6t2q1nBQnPsFq0yDJal/2elQZm41HVpSq+VdGo07ENgH2kpE1ErSADB/E7Hx72XoKhVuN0oSLAgd98rd7faBe9JZELr4+B6dNXkl22lXdYRq8J77EdWt6NgPVhkiKGrSrRfFpBEqtlShyXg7/+5cqrm77vvvujOSXooZdDE3tOQLaWYK44nrucYXdeBAwfGY3PTaLSLWQ9uVvbpMW5c7WHfPYE+S2gffPCLWAahH0/B5A3XXT9ZYPy1cJclq6PHrhralQwU1gSteNPQ2t4Gpr72r+qWp47GqC677LLYatVWGUkCy0DRr2HBHcGbb75Z9OvXL/7glQ7oGrg8uElkidT8/exnE7XP1BsqvTBcWdkE9ylBkJs0k+Jg9XvicmUoc1E0PWKffVoKqdtJjljwBivbl33WK2EwqCQpZKRHUtLw/wpTUzmE9+n37EmkEiZDZByHQD+3099cY8mBVLIxJTBhwoSYsVbaooF/Srja0CcJTUP6umuvHfsm/Zj323dUMTL8oMndJFjU22+zTfGdb32r2HHb7SrPtkCRrILdVVdeJbYUmSM5+tCW1p/ehM//+c8oJpmmaztnEkf12q6qoVVK0Sq12vbAOiPceMRhh1eeqQ81ULJh3BGxlpNPPikWBtO0Mz1eh0fSsPOdGQA9MGzbsSu83WfPvYp//buFmLS16ZRA2muusUax8ZAhrUq4b7/1drHsgKVi5b95pAp/6c7VwzPPPB23v9kmm8baxX1HjqyrasxtS+1BHuJTfndqImVrk6qGh6nnPQnlH7KJ6sxkGPWWarNCbFxP8wo6oqrRSIiFyqA6f9p2PV1rl9AnCU1FuIWopSjBHax8l9BYrRF8k6FD47/lWZt+zMQCSWInWIT17jKsk5dferl45qmnJxkC60tkTaSCTp+32KqLNstADBqun3v2uUkKWOmDKegUjC5/XiO2/ficCe7Oo1xAysJIVobz0VjO6vzzZ5+1djW0HP9Lkx2/GrbFFlmk7o/x88+/iNfRZ7U6qcw/UoV9ZbvOlxiAyetiOQmuQSobECzXoaED4a1AQMCSTteaesm8c84VC3ZBCYpeUh0YrGhtVoqiQZM/ocs7KvVPWta0U7letklfbYN116t5Pq7RBuutV2y52eatrzuGet85YUdBd+fAAipbYM71oIMOil0AylDcUNoq6u0OHJ+uhG233Ta2i1HrkFxBZixEQpKJ4KckeAfG8bk+1HinVOa6TxKaim9yPONLihfVoB9G7VTHwJKLLlaMCT+EBJ0B7ub1ppyXoa4IKZLRXnuNQcHFW63Vurjt1lvDglozkEQLMalH2mjDDeq24JCI3iDcZVX2rxlcPVYljA/bMUV9ow2HRKUOFougrh/zDttuH6yPgwJJ7RU1yohdanVKmbZ9gst9zNFHR8LjlmkDog6yyUZDY5aLO+f/0/GvEY4/9UO2RWhI8KAD9o8WENlwZEHlY7NgqZwTXDV3aD2yrK71Bw+OPbcEN0GMiSvGwjGFnCuItBCj7ZZJhEw4ee1kXUscaCPTIXDn7XfEljE9sKBbhGyQodHAyj42nHsCYUnXp7o2yndI1n2eOecIVvu2sVuA+KSe4HrQwmSxejgX7T9lIEj7EcPsycXsBjRq1Kh4HLsHT4I1aKAMQhND+7LqD/1m0kBmZS1TKtPZJwkNcey4/fbhBzpXbISu7vNEBiutsELrD596xeqrDIwDNeDXv/4oLnCkpvm6rfS2xujbb7s9Lrhf/eqXMWZFMQPooOn7Sw3R9msB6jOthrv6issuF6WsHa8ygEQs3JjXXn0t3uXvuvPO2MBNBQNWX3W1KIukXeejj34diVmTNqKGoYEEd9t1eLSaPKc3dYdwN9cKhADcvTWvx+MPi0+TO3kiaIvQLrvkknh9rrv2umidmWae1GWpM1CBXaTfQsUjwUJgHY8aMTLq+h8dCEaJRpKcViN1+/jxsfMBkVNIMW4OAYNYljkF6RjowNGdcw21ktH3TxOLEIc+1t122TWqqujhRU4J1DRY4yy5MpAC8UnflanqPiMWWP27SfA9yhpqME+KEwaOTGk4DrVt9s8KMnuBFLg6sCkZL6uHpPMmGVGOe/Yk+mxSwJ3+/HPPiaqlLIdEAHDrLbfEYSLcGTAAQwzngQcmZtpMMTK7gDTOMv0HBGttcknpBNYIkcdbb745WljkrkFjtf2kRnHuIWUQfZvV0INpQb1Zo/0EkZn4/dgjjxYXfO/8qN2VpKfXCIS274gR8f/BPpDmGRXS3HTjTWIMEBA9cjikSjCxfPzrDw7HH6xDqEdorD9ijUmW290XUaWAuMfAQE5ianpFCUGedMKJxcwzzRS1s5CBhAPZHPVQXCaiio899mhsMNcEfkFFIBI5lQnN9yo2yvrzYHGlGwbi5DLuMXy32M+K0MrX2oAWv4WkoZZgsbmGZhiwCAlhUul4553aVe7cfllNyYx1gnXqfNWfJVd7SgDhnx8sTvsWi3STEMejXJJ6lr9MsLKvCJ6IpIDvPFtoDcKHH3wYXTeL3F0LOVCXmHv22aMVZlFKIFBt2Gv3yWVcBIW33nKrYtWwQMsKFgm0uijIGsZh2Mn6gdC4izAZoYUvlUVRi9BYBAOCpVWO24FFcuzRx0TiIkRIKcRgkURoLMKyW8VKWSa4gawcqCY0FhAXNUFTd8vxb9py/NzDcLeHeoTGsnOOe4cF7YdL+cOCSmTmsXBwC5HHtlttHVUxVllp5RigZplxxfQVKnFQM1WG89106MbRjQdJHTeIFDdEVJIA1197bXzYRxKXdJy+S5+REGHJlWWUJEiWW2rpyeZPsI4PPfiQqO4hgcDKJRlUrU6SIF7GOlOOcNppp8XznZJxItfCMGLHkK63WJ16r3Ks8suGUIA4nlhattAaCMFyMjliW6RgxJHIxSgBOOP0M+KDAmuMr/xo8ruymZ5kcapluFkEKX6UYhVcF5pmIFZmX+mO6V8uT9kNSqDvNe+cc4ZjndQdejpYOCYQja/04slW2WbZQhuxd0usDbhJ8841d+t4uEkI7dNPo9uXLDTHjwAs4hSI33348Bj3gjYttOAaI3FIMRwxsVSbNcsss0QLzXuRljgKUUDV8kAvzPs0eZfhOCiDbLfNNvHvq6+8slgwXHvuMLBSF1to4eKF556PSRLxtBTrdPNaMFyr64MbDIjRTSBh9GGHx/NP7mwZFtySiy4etfLaA7kjpRiC/WJnMrVqv6ZElwPSpObLtU9ZVseiCb1eicmXBao22sNkfdtKhDUSfZLQKNFSpHgw/NjuufvuOAHJ3dqPlmIsscNXX550ipCxaiSc1a4R/DvtlFOLh8Od2P8L7K8XLBdxmTJYEzGYHiwcZEcWh5sjFgQWr7s+RVSketD+B0QF1mrlWBDHYW0hVlJATz35RFyYMoT95l8gBq2Vkxx2yKFR4/+8c1pKLyxQQX66aq+++kosRVlx+eVb67E22mDDqL8GfvCOd/11BgdCeC5aO8ocZAId/w2BVJcIBJYImWQ4/a9aP0a1YoQouWjkciysb37jG9Ei4/ZwNWafZdZYrU66RqW8vr5E/ApPZQnFnq74/hVRspzb61qRR0ozU52H2CIrW6ZTAsOMUAvb+Wy80Uax/u2F55+LiRHXXkYYyJoj/2uDNeN7XHyRReMMhnpgmSFPSaE3Xn8jJh4E9ashqcHa9J3ZF0IXN+xpCW03B/VlLFtupvgdMiVlxPpuNrBkHatZoylJ1dPok4Sm5IE09LLBvfDYOVhQLwbLh0Wi+PK4Y46NsZgyxKgU0HIHSe1sMHjdmMGjmMrCqed+KDngprFGjguuH3WLo45ouctze5SA2MagYEmx2OiYIdlaeCdYh9xhLqM4EWFFpHnm6eOKFcKiHrL+hpG4uIySACB7KHAuBuRzCKo8hGVMIGbCkylzKPOqvs6De6vvDlnH4w9ultjVURUhTMc5auTkvYnA7TzpxBOjm5xiZ6sFy84kJxaZUoZvBStCBnC68P9LBNdQoiBBRbtFKYbm+Fwjx29otEJZ31WCZIb6NLFMbm6Swga1ZkIC6seED5RzJCC9c4IVLputXMV36zupB6RgNsNK4f1uIqsGYuc2lUsuZESVY2jtSRYR0vO+nrSQXA/FvIhUwapjIBg5cuTIKLvUjOAW+10YsFJt5fcU+qzL6cf858/+HB9pcVjUCKJeTdC///XvqFLqfb6A+PngnrSX+mbBpPf57L++mPh+f5svkH7sXqu3f3Cs9uszqard++M2/vq3lu1X9vPF519Eq44Sr78dQ/UPx3udV4L3ISPb8/9Q7/j/8+9Jz6UajktcUhaL+6Ncw3Mp86alSXsTt4z6b9ofsLwQmnot+3U8zruea5K+j1pS4QjXa7WI1z7dvJxzef/1gPB0KyxcKQpVClH+HKuMiyeDV0ZHtt1V+E3Q6teH6TE03KzFzBTSNnPL2BnBwncNiT1OKXwlYmh9FX7oKy63QkwUfJnQ2uKHS95ZZiu5oO7Q6txqQfDa4uSSNhNcU7plLCF6XixMiq8JtwYL19wABas9SWIJbsDasbjsjkeje3Ljy7M9mxFJRujYyszYKYFMaL0YLJsTgjV0843123l6GhY1IUFFlBZ6ynbSOWsr4ybju35wI2U9mykzd3dws1XcU1tNA3lZkQlnnXVWDHRPiWNGZtxJWUJkhhhIlC+44ILF8OHDK+9qTvCQJIJY6eKlUwqZ0Ho5EMqUsBTagyJPmUtN0EhgyJCJY/TqwVQhiQHxp2bBBRdcEGvMlKIgNedCVpqLzHU1h1PcqqdjQm5WyIzOv1gZd978AZYZC5gL3cxgVcp4UyJ5qjKHdUqg4YQmhuLOIv6SIPj8s/d6RkyuDPv2Q6iHeFx1Fn9bsbVq2Ee9/aTzr4e2jqEa9lHvmNo6Btvv6H7ae29H9lNGipsoOnWXTmj9XVT241+uqloqrqnXOnr9ewqOQUsTC42Cbuo3ZZGJYSE05RlJATahre+p1jUqo9Zn/U38kutLXZYE0b333tvafF4eUt2soKbiZmVWZ61McU+hYYTmjqHafbddd41V5CP33qe1pmuXnXaOjb+16n86Cq05bf0wHn/88WL3sO9tttqquOrKKyd5r/oghavqmw4+8ICY0UzwI1WysdXmmxf7BOtCVXs9+PHdefvtxU7bb1/sGH74Ks/LP0ZlGnvutlvMtml7+vzziUFqLUYG6m652WbFAfuNiiUY9SCOowhUC5Ks5+MTJvaU2t+9wS3aZccdY4nG7eNvm4RwFJnKVjrXo0Yf0abKgmyhIlT1ZLK/5bIU1++G668vttt667ivRx5+qPJKC1gPBgf77JhTTo4tSaA5Gglw1xKUhIwKVo1zV/uXMswynTKkawQrxGtUNDT5NwLq1JxT6qst46477ihOOfHEqN7hO1EmIymhY2GvioWpzisJOHqwkChYILlUFoKwTYLym/O7f/qpidllIEt1wH77xe/izDPGTfL7l/zQkaBNzm8mNd9LHgkjLL7YYpFYzS41WZ4MEGuHkGS9xEkzQaxR6Y44Wr0bYk+gYYR26sknRxUECgd0pPyAU2uR3rknH3+irhXQHpQo+OLrjZLzY1D/dciBB8bjUEuUGsARgLILaXs/IK092pOSAoH364VUn7TT9jvE0oByWUAZ2qcWXrBfceLxJ8R6Kft55KGH42sUTLVJ+fEpt4j1TIEoE/Qyaiynv6Y2bPBaa8WMWS0obzD1W7/i3nvsWSy1xBKx3QaMxNMjqXtA36GCX/MsQdmB6zR4zbXjuSrNQEi13CMuoqJgE8Zl9ZZfepmowpEI2lg63RVmfioJ6R8WmFo6+Ph3H8dOgS3DTcD5LL1k/7hwLXDTtVldV4abCui0WDXcpXfeYafivHPPLRZfeJFINIAULVo9oIjFTUKpTHf7EB2HXt5pw3aVe7hBlKG5X5uZazM0uMaUWZZbdtmoPJsITNbWsaW/FYfusMMOUW471XwpySFs4F+EtuyAAa2qLQZM+74VXfttOe9jw/eVoPdVx4O14ne3wjLLRvUQlo1WIWS65qBB0TiYZ6654zGsv+56rX2rzQ5dC1z16qb9nkZDCM3ioHKgdaYW3JlMJbdY/LjcCd2lX3/t9UkULfwYNCqXBRdZfpQxyPkgrmQJlIGwDL+1faTJUltv7XWilfH8s4HsAjncXwlMWpQG9SJJjeUqzYkLws/DQkKMimqroVzA4mBFxL/DtrU57bDNtvHv/UbuG+vRUumAQtA1V1s9Li61UX74qVj09UBOhuzqKa0GkkO+RAbBMapJQ16gSHjXYPFy6Z2rQtMtw48eHn7oodiYnmqxiFIqLH28Rh8qK9Yk8aQ8QZbHkGN/W7C6BfRVwqd/+lPUI0stU5dcdHG8CbxfadpPjepiYXobZQjTdlnGfht6Y4FumXYlRb1cp28Ht+R/wp1cnIUIQCTRMS1T2buKtwMp+L3oBnH+5bo8QD6uY7J0hoe/EYjAu2NHyINWHxQ7ARBzGobiPTwB0D+qvm3smDHxbzdbnSZ6VkHLFZUQc0jT336Hvl+zSL3GWgVdEAjvsEMPja6uGB69NccnpmffEi6KrHsLuJnOod5Nu6fQEEL7ayAnxZmq0H1Z1VAZT/VBpb7gquZn7h03dIdwV4azzzwr3sk3D+b5SsG8/l5FhFAhqR+KH6aF7o5WBsJgXZx8UssPCZJMjFYjLoEG9VQ5n9QaWGYTHn0s9kWmdiM/oM3DD52ZX42fvPuTaD1YzAnHBaJVEPrpp3+K1tDRpTvw5cHldAcWC9E6hdDeq1h+CH7FcI6svGq88cbrxdyzzxHdoATWhuuiB1HRZ1oI4E5PE4yrMubkU8JCWSa6T8DSQdAXXTC5/PO+wWLcMBB0coMMijXZnQDi++//LB4DWZ8ELVG+L3VaCnlV56faOha4nlWtUlRoBbG5ur4bfZwkeRKQruZzpPvow4/EoluuCX0x27Nd59sdnBhuBr4Xx+VmUN2Mj9DKx79LcOsdg4Z02Vmu3V677xlfA2KUSEU9lZs3vPjiC7FT4vHHJ94sttpii2i1FsV/YjcD6yxZh488/HAkWS6wm6r2tOeeeza+BizeRQOZq6xHBMAlR67c8rPDte1tmJKuZkLDXM5Hwo+TkoQ7j17Fcne9uxYyUpPkLuwOrSKcXhOSc9dbcrFFozQOXHLhRdENYMmZF3jUkUfGz1gAv/5o0nS5mJH+yLIKqzYad3qxG8S1QiCP1GfHMqQtdtABBxTXXn1N/Gy5C8DCVW1fHad4/rnnozV3U0kmRlcA4qTesHRVI7T4mrsusqQK4fU0k5ELGGV9dplcyZQlSewwxVTg8EMOjS1OTwS3nVV11RUt7hwgbMflRiJuSe016frr3bSgxYrKYG2K81l8yaLkZqvUV7VPWgjplONPlGHpi/3m17+JpM89THFK8UDXAaGLPQmss5aJSFargbjW2sEs8KuuuKKYZeaZI1mQvfHd7BbcwU2GDu2QSm4tCCW4uaTaPC67G1pqYAcWvJYpclHv/+z9YsYZZiimn266aDGq8eJuLtV/QLjhjA6/kwNjLJG1JjGQQESybA3DAaP2i83/n3z8STE4uKis9BRmERv0Gxa28ODyJnki4YQBwW1HXMpGgDv+3ZlmiseydUXOKaN9NIzQgDrpiL32iq6L5uVUq3PySScXqw0cGIPO3BQkIhCfQC1iycUWL6656prinrvvCQRwZvHd8CNL7T1665YKP8rf1hjSmgitbLlx7VhHb7z+enEKQgsuTwp4Sy5stMEGMaDNzdLoXCY0rTU0tVgXZbirLhrey9pK4GpZyH7UFo14UwIVC8fw8osvtRBaeJ2bBbYtmJ6axstIhKavMYEMuBvAU088GS29FB8EfYoIzbW2gNZaY1Cr5eFcnXtS3khIhOY7+mflPH/+/s9je5XWJ61GCC1pqgFXUZ8kFwqhsawToVl8VCx2CJYVckp1W6r3KWWM3Gciof0okAZCE2qgNMtVnX666WPjupuOAPmmG2882fXnBrMAXYsjDjuseL50fcq44/bbozWffjvIiDSU5v+EfcJvlP4aq2jJ8B2xgjYP1wKScGO/YLmzFFldWrGqkQhN7DSBJehmyb2uJrTXX30t/Fb6F3fdcWcroQmxIErdFLom3HhdUzf5FSvFySzejI6joYQGzEwLj7V29BEt7SGnnHTKJIQWLZ0bW9QgALmwyOhYkfBxV/V48YUW3aoLKi5kLfkeixZZCConcPdYJsgOGS671FKt5MriWyVYi+PGnl48eP8DgQwXKl6pNBVzDwSKuQrVsBC5qlde8f3KM0WMn3AdWUICwGVLSE+j/SpXoRiB3JKVIC5IrpqSbDVeeemlSGhlMkF8MmksWgR18YUTeyKJHLo2LC0uMEs41SixZn0Pho9UY6+wTZZQsuZ++IMfFIuGG8PmwWrjajoG7mGCJA+r5p//989i1512igs9kQ7xSb2aG4YbhUV4TyVJwRLdfNNhxfBddo5/w7NPPxO3bTFTsO23wPzRRWWdaFTnopYVMhK4xhddcEFx4gknFMcfd1xw+SbVNAO/PdaX7YsBugmsFqy1OWaZJYp4BnaJ70tJIplkirniZqmxnOKrc1g3EBMgmJQoKePZp5+OhEZ8M4FqyXbBvdZqJtnC2k9uF2sXeT77zLMxpodQxeeUtwwIvyt9ozLaPAPH5Bg0npctwIz20RBCcxeq/tItliQBQ864LUI7c9wZ0VWVGaoFChgWbbJwqiEovkNp0AmVWvEex/XQA0hr4dbAsIU09xxzxsUqxiZLeHPlWH71y1/FbNMZgeyqYUGxNg4/tGVYih8qC0dJA0gOEBdMP2AuDxWOf4UF8cSECdES5DIDS3becIdmTVRD7EnD9zlntcRM/vrXv0QtNkkCBLLuOuvETGqC+NS2gQTglptvjgtFtgycI7f3qRqlC2cHK1hMMEkbORZul4X02KOPxWzv2Epwnvu3VnBl07lTpUCsSViRysgCwSrSXygG9HpJpJJkD/WOZDWyVt0YBIvFFFlo3E37PTRcMzeis8LvoStwXckHIZKbb7o5qpWY9kXrTYwPmSq5KCcFVN5r9k6lGOJkjkUpSVtwo2Itu2GCm5okATEAGH3oYfG8UxILGYt1SvK8+867wUKbp1g2nCslCu1imut5JkpDENn/BquRSGd1hjajbTSE0ARKWVRiZ2JMLC7qn5dfell83WJkwcQYmh/xPPNM4gIk64c09KMPP1zcW3E7U3r8umuvjW6KxVAtnwx333V3dDOoKbRIP/eLnwEN3ciVmylG58ctRsZSA/EdstQUIrgIKyyzXGsCoRq2vVBwRS4L58U6W2TBhYrHJ7RYUoL4jmFccDuVTCDtKy5vseZYKuJVyiRkHlk3Ske4FrXAcmN1kq9xLZdbeqnirTffjK8pp7A4L7rwong9HMNDD7RYUqSwuVGsOfuhdbbT9jvWbNoWn1w23ERYanfcfkeM8ZlURMdMtpLMEquSiCKpcseT3Kv3fvpe0T9YfqPCtSPL47vdI2yHnA1SKxdSmhNgO4cHN5H7Z+GOOaUlMwhGDCJDJDIbFYngln3wQdcmFLGQSUO9VLHsE2STbX/11VaPQoxuCkPC78HNY+lwDbYPrmW6EZ0QLEDvnX3W2aL7yxrdf99RNW+2spLLBSv85ptuimUrSD7VF775Rkum1U3Azdv1S+Uq6hWRqISIwcSugfik6UwLhd+NBMXMwWrcbuttosUprkgxxvedCa5tNITQLBjaWRuut34csuHuZyGkhSSeJGAu6CtOooaqPJEJpKS3D1YWORzkgzxSjMZC3T9YXSRuLr34kvhcGd4nHsPFUFph3+kHCu6IMnOUKQ4I1o3yjAQk627KNWHyc5/qgYXEchKg51I4r/9ULFP7Yw201LmtN1lxLxIQu3EMZIrKxb3VkFChfzYoLED6YoQME/ygueCCz0pV7g4kXbaO6XjtvP0O0eWSRW2rbon7w8UTuN82WNPKEnasWJxuJkjNMXDXyCSVoa6QRer104LFdmNYtOq2KEFU47577i02Ccfqup1/7nkxTJDAUttlx52KbwSXUyN4OT7YGYgLSmiwav5SydwmcKfXCtcLUXlsv9328ffl2iBwOm0JqdNh3cGDY0zM+DtlQ8mCK8MNSTmNa+BmXE7kAD2+YRtvEuOa55x5VgwFEGLUlM8qHRbWiWuPrPx+FaFKAiwZbhZqAt3M0kN9p3rB8m8qY3I0NIaWXM8UCO0s2vt8rVhGGT5X77Np2/XQ3rbLaOsYu3MM1WhrP+0dQ0f3471uPHovLeQTg5VT3m5Hz5Wr5PMsnPLNJKH83mqwYFlOPi9+lDoJGgWab2nknEdS+LglWG5qzB4OXgE4PplMWmfKWDqKjlwjN0PijKxYccrUsO2zLFqk6thWDJaaco2MrqHhSYGM3of3g8WqpUczMdnkzgIhkbWxIPUcdhasjjQhSIC8kVLWLM1BgwbFbXPl/CuTCYpWxavUCiYgmHqSR10Fi1uihAWLzFJxLriZmHDuuLj83//+xKRTRueRCS0jWg7cPQHqrrTWIA0yQKrZy10enQFXTKZTCUVZf6w7YCmywhC18getS4gjTTLn9hnQm4qLewLIUfZWWQYyq5bp1iGBVB0XPbmM7iETWkYcVGJBGf7RFbBwTPehXNtVKLhWi+Y4jMRrBLh5SIxlxMUzOg9pUrFA3BICspw9BbFfViC3VnysWs5bUoIckHMmS5SSYBldRya0jDhT0qKiKNEVSAj4vDhQqk3rChTk2o5G8JSF7g6UQ9ieuBS3Gqn5m4S2obymi9cK9jcCyExcEZkhK5nzcmxRgkCszvEgck3pZbLL6BoyoWW0Vsdzz7qCNPCWtE13QBeN6yuW9M4771Se7TyIC4pL0RJzXKkPkgKE7XtO2QT12Z5wN2U/kTOrlYIHt7NMVmKGyM55Og43hFQMndE9ZEL7ikPsKqlJkEymlX/XXXe1qaNWBouMtaPavrvKpILn3ED9oOJ6XcElJKLWXz+ej4cuBNOSgIS158SzjKJLYgGNBII0WAWZIrNyT3OC60vfzHlyeXuLJFBvQCa0ryhUycu2DRw4MKpLWOhzzjlnlNDxt8B5uUC2HmTpZBEF3btrZSjXSNYiC6azYCGussoqccSbAlXbocefilFJ86jz4uolfblGIsXsJEfE6WqVn+h7Vcjr2BBvueE9o/vIhPYVhHjNqaeeGgPk3CKLiyXDYmEZjRgxIj5HIrs9cO+QYFLL6C4IAjouswnaQ7n2yzkhCgTGXeVOOof99tsvunhiaIQTWUYTqoqEGwHEjiiRmTmUtcgd4Y0ZMyYel2uWel4zGodMaF8xUHfgbqnJ4mLSxzeDEiEl90jjNyvHNPD2Fr8CVFZPR8ivI7A97pr9a8+CaqKUrURejl3dm0LUww8/PJY/kH4GcTPEofIfEK8KfYNGGg3kNWzYsNh1oGi3XkLDDE1k7bh6o75Zb0AmtK8QkIVK/KjIGtxE2lv6cLma3LEy0gi3cePGVZ6pDYoRCO3ckh5ddyATiKwE7xGAzKsuhtTwTlMulTp4OBdWpmPgJqdM4oUXXhjLNdJxOT+j9hoJgX43ASUZMqduFLKbtaC0JY34875a3RQZ3UcmtK8IuFwHHHBADESzfmQUQUbO39UuHovG/EcDbpOlVAtHHXVUjLl1plWoPahDs/CnnXba+C+yMFIOlFmQqGZdpoHGHo6hTKqKc5Gd83SOCO3Oqr7X7sB2BPMVy7IMZTXrlYAQnUxxMy1eFE7qtUpldA+Z0L4CYIWdd955sUyANTZ27NhWC0E2E2lx2aohwM1SSlnCaohNaWZHOI2crclylIlMREWeO0EngmC6f5WLpISGc0tzDEAJCvcOiXM7xc8alU1ERlrEdBmwAo8//vi6pC9u5tpzR43AY3V2p1Yvo21kQuvjQDqas2UhLX4B/6RNBvomkQFLqwyLlpwNsqARVsuiECtChjKlaYpWI0CmiCVp3wbtlmNoLEEZRPtW34WovM+8ynIfqlmW3FCxQv9yQRsFGVJkpuH9zDPPrEtmrLjnn38+Zl5ZcRIxjbxOGZMjE1ofhxiPSUwWvbhZdeM3ElDcWavdiMa+hShGVAtcLAkFA3AbCRlLVp9jduxlOH61W2JVWoUMsvU+7md5DoQp7pQtvCbhUd1D2VVIkshmujko3m3L6kO6w4cPj8fgM11p/M/oHDKh9XEcccQRcUEhiFo1Ty+99FKMVaXgf9kSE+sRR+Mq1apJU0jLuuPWNTLILYvJlXPcu+yyyyQumuMrF6smyWzCkuX4mGOXLWXhNUrBQpmFNia6cddee21dgc4ErqZjY8USdczoeWRC68MQBJ+vogaLJGqRjkJPbpmJ59VAJKwbcbRahagWqW030p1jZWmSt10Phbbc5npgrXkfty6NmAPnKq6nTKURULSrx1RcTjN/2W2vBR0YLF+JiTR0OaPnkQmtj4JFtc8++8TFLnBfr82He4ewCDPWgliRbdRqa2pUD2cZ3DTxPJOQzCeQzewIoYnj9VQ/pHgcvTjWqHOtFU8sg2vJknNczqO992c0DpnQ+iiosApaKyZtS19MwoAVoe6sFmjeW5j6D6vBkmKxNLonEoFx58Tn9EO2ZQ0lpRCKGo0qySiDu6rAmNudSkfaAndY8J/LLP5HFikT2pRDJrQ+CA3SFriFLgbVFsTQZAHpdtVCqrgnUlgG8hDwFqeyaBsNrid9tTXXXHOSmFk1koUmOVB2ObsLLqtGd+Uj4nPc9/aAiPXHpunxVDS0RGVMOWRC62NANEoJWAjzzz9/65i6ehAbY8nViqHBaaedVtNCI7stsyjo3lOlCLKrLKN6rURQ1lBri/g6A/sTF0T0+jKT/n97YFUmpQ/dALlEY8ojE1ofg4HKFiFXELG11zCuaFbWrp7LmZqpq8seWFA6DBBaWzGu7kCpA7ezXjaRFaXDwfGx5pBsd6EURceBbdp2Z7KTyVp0zN3Rc8voOjKh9TGoqreoqLGmOZptQRbQ+8vV+JDiPiw0Ra5pMlICN1MGVX9kT7hVJH8QMyuwrfIIxb+ytILw3U0K6LfURSFJctxxx8UMcEfBvTS7gFXXkVhbRs8gE1ofguA8iwlBsc46AqQne0dupxaSBVQdQ5PJa8tVbQSQJWunLZdTJT4S6Yp+Whl6VwlAigmy0MpFuu2B9ZqKl1lpPTl0JaNtZELrI2BRkdJRHY/U2oudJSRCq5cUoM5hoSqlKBOLRcwi6eocgo6A8qvC3rbG2rHKdAV0R7BRXyjdNFZtZ+WFqH8gQladOB6CzfjykAmtD0ERLPLRHdBRN1BvJJet2uUEcaCk/KrVZ/z48ZVXWspCyG5Xu6KNgngYq0dsrCebubV3qdOTJe0smbnGms01nns0SkIpo+vIhNZHgGxYZxRTOyKdncA6oSdWq9qfcCKpHjM3EZvMaSqi1UYltqaOrScg0aD31KzQngIX3TwExbtd6XbQxykxgvApk2QVjS8fmdD6AGT7uIQWFhXXzmQd33777VjeUR1Dsw0ulG2yXC6//PIoPaRZ/frrr4+uFRnpntLEp6TBdR46dGiPEAXSV+M2ePDgLqvYJnecq5oHnTQHMqH1AdABE88S0O6sC0j4UXN6kqpOUFDredtMMaw0NcmUKPVWFFh7KgAuNsWlHTVqVOWZxoFSh95PLi3FjK5A7FBrFguWJZvRHMiE1svBekm1Yl2RmKblxeUsZwmVLyAvUteskFSwighS4aggOFf0d7/7XXyt0UDSXNxawpPdAXJW+c/6Y3V2BQbJ6B2VXZVNbisLmzFlkQmtl0PwXKyJNfPII490um9QPRlL67DDDqs8U8T2nSOPPDJutzxTwLZT8agHC6eR7UZl6KFEGOVERHfBjdUStvzyy8ftd6Ug2A2AXJLzJ6vNZc9oHmRC6+WQnZSltFB1CXQWFrnSiL322iv+zYKhakv+hrunFKQMMbM0+k5msKcULhS4yqx2pDi4PWgHS24m8nbNutJVIKupHk8XhrhZI8k2ozHIhNaLoa0pWQsEB7sChKTin0wQiKmJK9keAqjuR9QaJBlgnwMGDOgRd0tcTnbTDM2O1tPVg4SJY2ZtSn6QAurq/FD6ajTOuNvmCGQ0HzKh9WIgH64ma6GrhaXairQXqWEDrph4GkFIahPVkjziaSS3EZrG8Z7IcrISqbwqqegOHDsX0bkhItnZrhIwCaPUDeC4EGVG8yETWi+F+I+2IwtM4L6roMsvwJ00+QXKuVLqqqrdzQTDdO2Xq6uHsdGwTRlWlmJXtcR8Tnxwiy22iFlZmnBdjffZluSEJn5WXk/IJWU0BpnQeik0b2vItli1/nQHXEsZS+SGrFS9EymsBxprCM0Cp1rbaCgh0SfancEmGst1ACirEDNrq32qPSgmNl2KNtodd9yRNc6aGJnQeikM7FCp3904E9eJC6neTHGoTGm9RnVgraQiXg+k0cjCVy4tchXT60yDeBlKPvbYY48YvOc2d6e0xLYcC2tUS1m9YcIZzYFMaL0QrDNZQISiALarQE6yfdwyi19GsTpmVgtKOhKhqeeqR2jcYq/51zG3lxF1PFqpdCSog+sKEJDsLAIydakrmd8EhKrzwnnqmuiuJZzR88iE1gshC8iK4RqqGesuttlmm7hoO9plQI3VWDxxLuUiYkoSFAgRwUoqqFcbNmxYDMgjTLMB1lhjjRjva0tySNZWAF+nQGeBzA455JB4Loiou9aU6yGjKfGSJzf1DmRC64W49dZbY4wJQbBquos0DLej8yv33nvvYquttooiiD632WabRZcVEXGBZV0NFjGghVvM+jOIxXu1Cyls/fDDDytbmwhFquJ5LKzOZiN1NyRXmHXXmQb9WvjFL37ROpXd5PiM3oFMaL0QqvpV0bMaukNoPuuhkNbCNeGpPajh4mayXpR2+JyHoSASBGJy4mAKdpECC1KRrpIJhEnyu54S7AMPPBCD+HfffXflmY6BhXjiiSdGN9M5dLd2TXJEltd5cTWzYGPvQSa0XgbFnWq0SAU1KqbDArF4O1L+Ia6k6FUiQWFtIjTZ0e5ALI/lpp1IvK2jUGdGJpxrKBHQ3ZF69i32phvC9CZ1dh2JK2Y0BzKh9TIY2sGKkXlrVHGnqnek1JFRcDoIvFf8jrSPBnLW4sknn9xla9Hnbrnllrh/VlxHtyPgnyZcIdTuDiaxXxakujzlMN3pKsj4cpAJrZeBogZCEXjvKoFUI42q0wLVlq4XNzLtX7xKnEpvpL+VR3QVzkMvqfhbW0OFy1BXZkAK4tlggw1i/K27lpSuCTMUuK6s1lpxvozmRia0XgSZP5LUtM9kFRuFNLZNHIwLVw/KLlKXQFLnSOob3SmwVawqocA66gjEuHQ0zDbbbNGa0vbVFeWMaqTrQCLJAOaM3odMaL0IBt5acEOGDOlSWUM9SC7YrmzkhAkTKs9OilRrZn6ninnlFYBYfJZ71hWIeSnrMDC4IzVjYnhao/SR9u/fv3juuecaUrnvvFl7WpsQbEbvRCa0XgKEksoSGj067qabborb9ajVm8kyU1/GzfNAJqmUQQYzVeR3FshJj6VSDaUo7UHA3gR3yQjusa6GrnYTlGEkH0tPSUlHx/9lNCcyofUSIDRZQO4myedGxc9AM7p6MbGjq6++uvJsC8SlZP1OOOGEmIlUkqE+a+TIkfF1bUWKbHUPdBbKLZZZZpkOyWw7DkqxMqwykIitEeUU5JFYm+r6xM8yejcyofUSqPtCZko2kiR2o4AoEBoLTUtVGYQR99lnn6hcK6uKSC183QLAYqOP1llCsy1ZUjVtHSmiffHFF+P705CWRijlukkQbBS/MzAl15v1fmRC6yUwmQjhcDsbVa6RkKaP2351ca3iWSPsymoVEgE6BZAbMmI5drb3UswMObM22wvoq72TXeXaGjfXiDkGLD7bVSri/BT7NtLqzfhykAmtF4A1ojQB4VS7hI2ALCG30fZZYwl6IUkUIZG02P2LjDbddNP4N5hrqR+0o2UTyi2QmXIRpRJtQWnIoYceGgnXMJhGlVKwzpCkRIAOhZT0yOjdyITWCyCjKQgudtXdtp5aMD08yWrvvvvurVlDZEL4sVrokfCiZvMECq4ItyOlE+J14mYKgzWTtwWuNSkjx6XpXL9mo0BzzcwCJKm+LqNvIBNaLwACsajVoPVEnEftmTiSfWg0T5aWroBaLU0ITmaSdcX93W677eKjvZYlWUnnIKPYnkoIUpV9lajYddddi9dff73ySvfx4IMPxsb5TTbZJE6Oz+g7yITWCyDDiGy4aj0B3QFKMexDUWkiNHE71lQ1iXJ7lU4kfTM9lNzOtkooxOm8hxIHBdj28NRTT8VEBfkhGmmNAqtQHZ8i4jy1qe8hE1qTQ5Zx6aWXjmRz2223VZ5tLATZWU72QcMs9S9qr6o12UnN2MILL9xKdPvtt18kRBX8taDBWzbTZ5Bke6DSQeSRu3v77bdXnu0+WJRUObia4nIZfQ+Z0Jocsm9afJBao8s1EtKgFITGekn9lDKcmtCrhR+VUNA/SxOfEJo+zFqlFG+88UYkRZaZuFV7U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CONVOCATION EVALUATION
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A l\'attention de part 11   part nom 11

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 10   part nom 10

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 9   part nom 9

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 8   part nom 8

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 7   part nom 7

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 6   part nom 6

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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0RhuKMU/Zqs5woAbCtKhprveBAHIQQQGjEdhNo44S15MLyMfCwfVuRhT0EydN0YcEVHPLYVJKLESJ5v9wzEYLueXZKvhVCEXveRMAeA/Px8bN68qU1BVgDgt99O4bffTjcKI9we9Ho9fvzxx1Z5tIvFYjz99LN47733MHLkyGaF+Z1apkwmw7Jly7Fly1b07t2n4TeJxAzLlz+NTz/9PwwdOqxTNd/W1gnRvR3ISSAQYOLESQgPH2ky7ZUrl3DixIk29aOioiJ8++23JpdGxGIxFi5cBDc39/taPjGB3laTBsehl42hx7yCCIVqZbufq+J12F6cgoomBu/nrJ0RZPNfr1pbkRmed/ZtZFrhAeytK8dNRXmXdpRJPTzxumsgHJvMxOtBWFt0E6cr8rrNSe5mXSUO1hSj6RRmtJkVJrn4QMgO2+g0wbNnzx5kZma0fXIoFGLjxg0oLi7uUBkKCgpw8OCPrcrv6aefxcqVK9u8vUwkEmHkyJF4//0P4OPjCx8fH3z++edYvXp1qxy/7mfs7e2xbNkyk+vDHCfA9u2RyM3NbXXf++mnn5CUlGgy7ahRYzB27Nj7vi2YQG8HjhJzND2NRglCja793q+xNSU4r6oxuD7LxbeRQxcHYJyzF3ybrJcrQDhQnNqlWrKQ4/CYey8ssHOHWWMFHtm8DmtzopFW1/UBOAjAn5X5KDTyrk+5+MNFYsE6aSeRkpKCPXu+b7emePNmEg4fPtyhEKDR0dFITU0xmW7WrNl49tlnTWrlzQscDqGhofjiiw2IjPwOERFTWhURjQEMGTIU06fPMNlPUlKSceTIEeh0OpPPzMrKwu7du0xq9NbWNli0aCHs7Ozu+3ZgAr0daHjeqJBpr26qIx67i1INDkSZa2GHUCOmY0exBZ519DTIf0d1IdK7OHqZrVCM1Z4DMNnC1qDzXNCq8K+s6yju4m10PBHO1hSj6fTJSyjBKAcpBGDaeWeg1WoRGbkNJSUd07A3bfoKOTk57fs2dDqcP3/epLm7Rw8nLF68uMN7jzmOQ79+/eDl5cWOVG0DVlZWmDdvvkmnL4FAgG3bvjVp8eF5Hvv27WuVZSgiIgJDhgxljcAEevuo1KjQ1JvVHByshe3bKpGsqMBxheG+2kecvI2e7iXkODzo4gP7JuvZubweJ0symvFT7zxczSzxludABIvMDETnobpybM6L7ZT1/ObIV9chpd7wCMiJFrZwkJizDtpJXL58Gfv37+vwc8rLy7B3795WaWVNKSsra5Uz3oIFCxEQEMga7S4SHByMJ56Yb1KjLikpxt69P7QYEjYxMQH79v1gMs8ePZywcOGidltlWp7cARUV5Q2n8rX3Lz8/v83+J+2Febm3VTsnHtdrDDUWO04At3Zs3eJB+LEkDalNBOAEiSVG9fBo9j5vSzu8aNsTa+/w8tYD2FKehWluAW0Kj9vmjg4g1NYZa2XBWJ59HcX035VzFYDPy7PhZW6LJ9x6dcladrlGiXwjE4Yhtq7d7mnf9rr7e2h9tbW1iIzc1qqDSYjIpDa7Y8d2TJ48GSEhIW0uhylzOxFhxIgRXb7Hl9EyYrEYjzzyCH7++RiysjJbtILs3r0LERERGDBggMHvarUae/bsQVFRocl+9cQTT6BPnz5d861yAqxY8Qr0el2HnuPr64fffjvTJZOObhPoZdp6FKg7LwCDABxczCzuujk1X1WLPYoSg+v9Le1bfVb2nWQpa7C/qgAcGpvspzvIWlwLFnMCTHf1x9rqgkbRJG7yOpwty8Z8Wd8uNu1wmOTkhdWqGrxSnNKo9BVE+KgwCd4Wdhjp0PlepyX1ChQZrJ8T3Mys7+0Rjwjf5NyAo7DzYuALOQGe9Q2DuJPPqb969QqOHv3J4Azxpnh5eWPgwIE4cGAfWtqDXVtbi507d6J3795tOme8oCAfdXUKWFg0P1kOCuqNgIAAJlHvAXx9fTFv3jy8++6/W0ynUNRix47vEBQUBAuLxuNcVFQUDh48aFKYe3v7YPbsR7t0371QKOzwRFEg6L6JZhcJdA4v5dyAGdd5Fd1LZIadfSbAWnj3NLA6vQ4bc2OR3WTGZgbgIXt3CNvxvqfLshHbZLvbEJEEU1x8TdeJTQ88Y9UDXynKGq5pAewsy0SEqx96iLt2RigRCLBQGoQMVQ2+qCls9FuiXot3c6KwwcwS/padG0zB6Bo9ocsOPelEiY73aks69Ym9OQGepsGdOxkvK8WGDRtMCnOe57F8+XIMGzYcly5dQn5+y+cPHD16BFOnTsXo0aNbXZbS0lKIRC1/84GBgd2i/TBaI7wEeOihh/Dzzz8jKup6i2mPHTuGGTNmYNSo//aHuro67N69GzU11Sb3tS9duhRyuZxVeiNFq4vI0muRrFN32l+9TtPla8MtoeJ12J2fgA3VBYZailCM0T082mw7KFTXYUd5lsF9D9r2hIeRuO1NsRCIMMvFz3CSoFHiXHlOt9SLg8gMKzxDEWFuWN5f1XX4JCcaFdrOjX1dayTMKzgOTmLmkdxReJ7HkSNHceWK6UAeffr0xcSJk+Dj49OqEKB1dQps2vQVampa77hZV6cEZ2Ki7OHh2Satn9G1uLm5Y9GiRRCLW7ZE1dersG3bNigU/z2O+dKlizh27IjJvhQWNgSTJ0d0W1S8+16g/69AADJU1ViXcRUri5JhTDStdPGDczuOiv29PBfntapG05QAgRCzXP1bPTkYaN8Ts80ar5frAPxYkoG6Dq79tBZPCxu86dEffY2Ent1eU4xv8+I71UnO+EE4BP09HoTj70BOTg42bfrKpJlQr9fjqaeegouLMziOw4wZM+DhYTqi1p9/XsCxY8da//21ok27y+GI0XrGjh2HkSNNB5v5/fffce7cWQBAVdWtMwBMOU9yHLB8+VPsKNv7UaDzAIo0KmTXK1r9l1VfizhFOc5X5OHTzGuYm3QGaytyUGvEQjDD3AaP9AyAoI3OX1VaNXaUZRg0xmRrZwRZt/54RjuRGR4zYp7fVV+Nq910aAsHYJi9G/4h7Qf3JtqUGsDHZRk4UprZaSfS2TSz7FKkVbEvugPodDrs378fhYUFJtOOGzce48aNx+11czc3NyxfvtykZkVE+Pbbb02a529jbW1lMkpYfn4etFota8B7CDs7Oyxa9KTJbYQajRqRkZEoLS3F6dOncfbsGZP9Z8qUhzBixAhWyUbosgXpXgIRLDrRw9lGKGqXh3AdgBezrqKtxth6AHVEBpHbGmnHIjO84z0Yju1Yu71YVYCjTbZeuXIcHnX1b7Nn+IgeHphQlIyTTQTajyXpGNFDDjHX9fM2DsBUFx8kq6rwUWkmFHfUWwnxeCcvDr4Wtgi1delwXs05lZVq6u/tr43jsKdnENwknXeQjYDjIOoks2NycjK2bv26VWkXL17SaM8xx3GYPDkC33+/2+TRqTdvJuHAgR/xwgsvmJwAODk5Q6fTtWi+TU6+CY1Gw9bR7zHCw8MxderD2Lv3+xbTXblyGXv2fI9ffvnFZH+QSCRYsmQpbGxsWAV3hUAnMrayTXjPMxQDjIRIbb8pgYNlO7wFedw66rOzCROZ4VOvQejbjndU6nU4VGoYMGGUhR0G2bm2+XkuEgtMdZDiZElaYy29rhxP1pQitB3PbA8WAiGelwcjW1WL7YpS3Kkzxes1eCv7Or70D4dnB7fUuZlbw47jUN1I4+eQV19zj39uHAY7yuBzDx65Wl9fj61bv4ZSaXpnyvTpMzB0qGEgjx49euDZZ5/Ds88+Y2Jew+Hbb7di8uTJ8Pf3bzGtVCqFlZUVeL75iXViYgJSUlIwaNAgNqLfS8JFJMKCBQtw8uSvqKgob1GGfPLJxyaXV4h4LFiwEH379u22dxCLxR32cpdIJN0WpKjDAp3jjOvNPcUW8DL/35xFPW5hj1Weoehv69KuTXQxNSXYcodneoNA5ATYXZDUrmdW67V/6cl3bh/j8WNJGvrZukDUTR3KXmSGVV4DkJb6B8422bb4s6oGn+VE49++Q2HdgaNebSSWcOMEqCZ9IwvB77UlWKjXwkbIHKTayqVLl3DkyE8m092KCDbPYKvR7bFg7NhxGDduPE6f/q3F55SXl+O777bj7bf/0eLZ1dbW1vD19W9xLzrHCXDu3DmEhoayvej3GL1798YTTzyBL75Yb1IxNIVM5oE5c+Z0WzheIsLbb/8Dw4cP75gyKhB2m9MmCyzTBgaIzPCUkzcecQtAD3H74oVriceh0nSjv0XWVSCyrqJTy7y9uhCLlFXw7UatMNDSHv/2GIDF6ReR2sQj/bOqAnjlJ+IZWT9I2mkqlptbw0tsgZtqxR02IeB4fS1K1UrYWLKYzm1BoVDgq6++bDFy153aef/+oS0K/KVLl+G33061qJVwHIcdO77DlClTjWr7t3F2dkb//v1NBpfZtWsnHnroIbYf/R5DKBRi9uxHceTIT8jKyurQs5544gn4+3df+xIRpFLZ3yoCIfNybyUPmtvgcNB4LPUIbrcwB26Fed1eXdRt5c7l9ThSkt5pDmmtZZi9G95072PUj2JdSSpOdWBbnaVQhCFGHAdreT1Ol2d3+7v+3fn1119x5cplk+lcXFzxxBPzWtSoAWDgwIGYOXOWyefxPI9vv/3G4AzyRhqHSISRI0eZPNylrKwU33yzFXV1HQ9mFR8fh+zsbNYxOgkPDw8sWbKsQ7sR+vULxrRp05kF5n7X0C0BvO3iB3+L1mlt5eo6PFV00+B6oroOefW1kFm0fxlBT4QjJekope7dZrOlIhdz3YPQ08yq2/IUchxmu/ohS1WNf5VnGUwy3smNgZu5Nbza4SDGAZjg6IGvKnJQcofw5gB8VZqBSc7eXRr69n+JwsJCbN68uRWnoXGYO/cxBAUFmXymhYUF5s+fj6NHfzLpfX78+M945JFZmDRpUosTBF9fvxbDiQLA3r170LNnTzz33PMmJx3NER0djVdfXQWxWIznn38BEydONBnYhmFCaxQIEBERgUOHDuL69WttF1KiW2edy2QyVpn3u4YuBjDWQYZHXP1a9bdI3g9rHQ1jqOcQj49ybqCyA0FS8uoV2FmVj+7eNZuk1+BUaVarwvLwnRi+x1IownMewVhiZahNX9fV44PsKOS3MzxwiK0zhjbZf08AonRqHCpOY3vSW8mBAweQlJTQKi1rzpw5rdaQgoODMW/eApNroxzHYePGDSgvb95pSiaT4eGHp5l0LOJ5Hhs3bsTGjRtRU9M2B0mdToerV6/i7bffQnLyTcTHx2HlyhVYv/5zlJSUsI7SQZydnbFs2fJ23Tt06FBMmDCBnX7HNPS2I+EEWCbrhzO1pTjTZBvYr2oFduTH4wWvgW12XCMQfi5JQ3qTMK/2nADP2Uth2UkhbXkiHKkpwhVt4y1cm8rSMa2nH2xELTuUEBE685w0J7EFVnsNRGrKeZy/o0x6AD8qKyHKiQLa4QZoLRTjmZ6BOJd1DdVNpiAflaShv7UTwnvIOz3yv5Z4XKjIx0A7V9iIJH/rvp6eno6dO78zbRHhOCxevKRNGpJEIsHjjz+OI0d+QllZaYtpY2KicfToUcyfP99o5C+O4/DYY3Px88/HkJaW2uKzNBo11q//DElJiVi+/CmEhIS06JDE8zyqqqqwb98+fPnlRlRW/teHpa5OgfXrP8fVq1fx+utr0K9fPxaZrAOEh4cjImJqqyLB/dfaY4nFixfDwcGBVSAT6O2jp7k1Vkv74M+sa40iwykBbCjLxHB7KQbZ92zTM0s19dhZnm0QaW6JjQve9A2DWScF8CcCfPMTsbAgvtG2sQsaFc6X52KKq1+L9ws5rtM7hb+VA972CMXTmVeRfoeTnB7AHmVVu587zFGGCSVp2K+sbHQ9n3isybmBrebWCLRy6DShXqfXYnNuHD4uTcc8O3e87TMYtn9Toa7T6bBz5w7k5+ebHFz9/PwxderUNmtIgYGBWLhwIT755OMW7yUibNr0FcaNG9dsbG53dymWLFmKN99cY3ItVq/X45dfjuPcuXOYOHEiJk16EL17B8HVtScEAgGICDU1NcjNzcWff17A/v37kZubY/S5PM/jwoU/MG/eE1iz5g1Mnz4dlpaWbJBsB7a2tliwYAHOnTuLujpFq+6ZNGkShg+/O0FkOI5DcXERQsOCJAAAIABJREFU0tPTO+2Zjo6OXTo5YQK9GcY4eeHVqkK8W9U42loqr8enuTHYaOUAhzbEDj9dloUYXVMvYg6PuPrDojOP/OSAsc5e8ClORnITa8Dm4hSMdfKEZYvburrGrDXaUYZVymq8XpSEmjtiF3TEMG4rkuBptyCcybiIiibxEC5qVXg+9QI+8QlDSDu3F95JmUaFT7Ki8FFVPgDCF1V50GcQ3vEJ+1tq6lFRUdi1a6dJIc1xHJ555lk4O7cvpsTMmY/g4MGDyMhoeVDMz8/DgQP78eKLLxoNO8txHKZMmYITJ34xGU3sNiqVEocPH8JPPx2GSCSCubk5HB0doVSqUF1dDb1e1wrfgVtUV1dhzZrVuHEjCq+/vgY9evRgg2Q7GDhwIB599FF8++03Jvuera0dnnxy8V2bQHEch7fffqvTrDJEwLp1n2LGjBldVmZmP2oGM4EQS2T9MExkZiAMvldVYV9BEvhWiqNqnQbfl2agrkn6+Zb27QpMYwpniSWecjDUdH6vr8W1qqK7Up9iToD57kF42l6KztqRyQEY7SjFuy4BBi3BA/hNU4elaX/idFk26tsZS17D3zKxP3vzLD6qymuYgqgBbKjKx/sZV6DQ/73CjtbV1WH79kjU15uOrDd06HA88MAD7V6/lMvlmD9/fqvu3759O5KSkpr93d7eHmvWvIGgoN5tHEgJWq0WtbW1yM7ORmlpCTQadauF+Z3PsbOzYxHpOjKumplhzpy5kEpNL988/vjj6Nev310tr16vh1ar7aQ/TZeXlwn0FvCytMNb0r6wbCLSOQCfl6Yjprp1zjIXK/NxSmPo/DXXxQ82os4POCDkOEzr6Q+XJjPLKgB7SlKh4fV3pT6thCI85xGCKZ14nKqIE2CerA9W2bkZ/f26To0HMi7jzZQ/EFdT2upDYlS8HimKCnyYcRnh6Rew30gUOi2AWr0WujbsWrgX3HouXryIQ4cOtkKA8XjmmWcahXhtDw899DD69DEd3au8vAzffvst1OrmHU979eqFd95ZC0fH7tWQiQhTpz6E55573mR8ckbLBAYG4rHHHmsxjUwmw5w5c9gOg7aOh6wKWma8szeWV+bh/2qK//txA0jkdfg8NxbrrUa3uI5ap9dhb3EalE22V0VIrDDEwb3Lyi23sMXTtm5Y22TJ4KiiDE8ryhHcCTHV21UuM2v8y3MgclP/wDVd5xyrai0UY4XXQBSmXsCuJuvpt1vs05oi7FKUYpalA8LtpRhg6wJzkQSWQjEshUKoeR4qvQ4KrQpRNaU4W5mHSGUl1H8Ja2O2mNfspVjjPRj2RhwNtc0I+cNlWXCuLu6SunU2s8TEHh4tpqmsrMTWrVtb5a0+bdoMDBkypMPlcnFxwZIlS7Fq1QqTWvGxY0cxffqMZk/q4jgOYWFh+PjjT/DWW2+26iCZjsLzPGbOfARvv/02c87qDIVDKMSMGTNx/PhxJCYmGKlvPZYsWQovL29WWUygd7KJSCDEsx79cT7pDK7rG5tMtisrMKrwJhbK+jV7oEpibSl+UFU1ES/AbCdv9BB3nelOzAkw1cXXQKDnEuHHolT064R15fbS16YH3pKH4Jns6yjsJGuBm5kV1vmHQ559Ax9WGT/Jq5jXY6OiDBsVZbAVCOEjEMFdIIQ9J0Qd8SgjPa7rNKhvhcb9vpMPnvfo36yFxeiBOMTjleKULqvX52x7tijQeZ7H8ePH8ccf502uCwoEHBYsWGg0xGt7mDRpEvbsGYzLl1s+Z12pVCIychsGDBjQrCYsEAgwfvx4ODk54R//eBsxMdFd9x2JxViwYCFeeOFFODo6sgGxsyb2cjkWLVqEN95YY3BcamjoQEyd+hALItMOmMm9Ffha2uNVtyDYGjG9v1ucglSF8T20WuKxvzgNyiYCYoTIDOOcPLq83H1snLHU0nAQ+qGmECmKirvY6ThEOHniTRd/dKa7i6uZJV73GYwNroFw4wQtTlhqeD2idWr8rFFit7oWhzV1uKCtNynMewnF2O8xAC97hnbJcklHMDVBKygowMaNG0wKcyLC44/PR0hISKeVzdraGs8993yrYlqfOnUSp06dNDHhEKB///744osvMGPGzC4xzbq5ueOTTz7FqlWvMmHe2X2V4zBx4iQMHhxm0PeWLVsGV1dXVklMoHfdQPlwTz8ssnGBsImmncnr8Un2Daj0OoP7UhQV2FFraF59xEHeLZHMLIUizHU1PM0qidfjRFnmXa1TMSfAPPcgLLbr3GUHO5EET3uEYL/fCCy0doJrJwWjkHECvGjnhoO9xmBmT39YCP9exi29Xo+DB39Ebq7pkLv29g54/PHHOv0QjGHDhv11hjpMTii2bt2K4uJik0LBy8sb7733PjZt2oIRI8I75RAMe3sHLFiwELt27cb06dPZmnkX4ejoiMWLl9zhZEiYNOlBjB49hlUOE+jNDA6d9BwLgQjPe4Sgt5EtX7uUFThUlNIoxhoPwvHSTAOTcm+BCBEu3bc2NNDBDbPMbQ2u76/IRV694q62jZ1IglWe/THF3KZT20zIcRju4I5NvcZgl/cQPGZhD6927vPvLRDhFTs3HPAPx8cB4ehl5Qjub9jX09LSsGXLllvHHbfwx/N6LFiwsM2e5K3BzMwMy5cvh0QiMVmOqKhrOHLkp1adwmVtbY0JEyZg06bN+Oyz9Rg9egxsbe1aHTuciCAUChEY2AvPP/8Cdu/ejbff/gf8/Py6NDrZrfrmm/2jLoh2SIQW8+xIvPX2EB4ejgkTJt5SQCytsGDBQtjZdd/hSqbqorP/upoOqxm2IjMscZA3GkwIBEdx92/tcBSbY4W91EgZO2efsK+VPd6Th+BsVaHBbzGqakzUqhvWxau1GlQQb1AeuZk1/Cy7z7HGXmSGBa4BkFcXNhJEBCBNWQWZuXXjwVEkwQJHeaMDTngQLLtor7WnuQ0+8h6CvnesLXMAHDqh/5gJhBjv5IlwRxmSFRW4VF2IazUlSNHUIUWvRSHPAw2BeDmAE6CPQIheQglk5jYYZ++OXjbO8LO0g6CNA7uVxByrHeXoTr92XwvbZgVHcXExli9/yrTlRCzCjBkzu2z9sn//UHzwwUcoKjK9fVIgEKKurg7W1tamrWgcBzs7Ozz00EOYOHEi0tLSEBcXhytXrqCgIB95eXmoqalGfX09hEIhrKys4eTkDC8vT3h7e2PkyFHw8/ODs7Nzt4QYFYlEeOONNw3Wjxu/vwBOTk6dluft6H3Tpk1r2Rolk3VbRDwrKyssXrwEp0//hhkzZiIsLKzbvpeIiAgMGzasW2VUr169uvT5HBELes24f9AToUSrQq1WDZ1OC9xeM+cE4AQCmIskcJJYsDPV/4dQKBSorKyERqOBXq8Hx3EQiUSwtLSEk5MTc766y+h0Oqxfvx4TJ05A3779WIUwgc5gMBiMvyu1tbWwsrJisfKZQGcwGAwGg8GmQwwGg8FgMIHOYDAYDAaDCXQGg8FgMBhMoDMYDAaDwWACncFgMBgMJtAZDAaDwWAwgc5gMBgMBoMJdAaDwWAwGEygMxgMBoPBBDqDwWAwGAwm0BkMBoPBYDCBzmAwGAwGwxARqwLG/QARQaVSged5mJmZQSxmx6MyGIz2odfrUV9fDwAwNze/Z47gZRo6475AoVDgrbfewpNPLsKNGzdYhTAYjHbB8zyOH/8ZTz/9FNat+6RBsDOBzmB0EzU1Nfj552O4cSMK7u5urELu0DTy8/PATlFmMFpHQkIC/vnPf0Kr1WHRoidhZWXFBDqD0Z2kp6ehvLwUwcEhsLOzZxUCIDn5Jj788ANs3rwZPM+zCmEwTFBYWIj3338PcrkcH3zwATw8PO6p8jGBzrgvyM7OgZmZOQYOHAQLCwtWIQAOHTqEr776EsHBwRAI2FDAYLREfX09Nm3ahIqKCnz00Ufw9va+58rInOIY//Oo1WrEx8eBiODv7w+RqPXdnogamaNNCb4707dXSLYlzzvTcRzX6F6O48BxnNH0CoUCN2/ehFgshlQqa/Tb7XuM/Z+IjD73Tg3f2O/tLa+xe1tTnq56bnO09f1bWz9tKWNb3rm179KZfa8tfd1UPbVU562pY2PlNHWfXq/HrFmzsHjxYsjl8ja9W3dNmJlAZ9wHAr0eUVFRUKvr4ePj0+pBLTs7G9euXcOVK5dRUVEBBwdHjB49GsOGDYOTk5NB+sTEBJw+fQapqSkQiyUYP34cRo8eA2tr61blqdfrkZ6ejtjY2L/yrISjowPGjBmLsLAwgzwBYNu2bSgpKcaMGTNRX3/rPePj4/6yRgzE2LFj4ejo2JD+woULOH/+HOrqlLh27Rp4nsePPx7AmTOnAQDTpk1Dnz59UVZWhm+//QZCoRDLly9HYmISzpw5jczMTDz77HMICQkBEaGkpARxcXE4f/48iouLYW5uhpCQEISHj4S/v7/B4BgVdR3nzp3HgAGh8PHxxcmTJxEdHQ2VSgl/f3+MHj0GgwcPNvAa1ul02LRpE+rqFJg9+1FoNBqcPXsGsbGxePDBB/Hww9MAAEqlEjdu3MCFCxeQnp4OgYBD7959MGrUKPTp08dgMpebm4vvvtsOHx9fPPDAA7h27RpiYmKQn58HPz8/hIeHIySkv9FJIM/zKCwsxLVr1xAVdR25ubmwsrLGyJEjER4eDjc3t0bvX1paiu+++w48r8eyZcthb2+49BMfH4ejR4/C3d0dCxYsBMdxqK6uxtdfbwERYdmyZUhPT8eZM2eQlpaGxYsXY/DgMOTkZOP48V8QHx8HgEN4eDjGjx8PZ2fnVk8i8/Pzcf36NVy9eg1FRUWwtrbCyJGjEBYWBplMZjDBOH78Z0RHR2PKlCmwsbHFpUuXEB8fB41Gg5CQ/hgzZozBfXdOsuPi4nD16lUkJyejqqoK7u5ueOCBCRg8eDB++ukwSkpKMXXqVPj7+zfKNy8vr6GcxcVFsLa2xogR4Rg9ejREIhG+++47mJubY8GCBbC0tGy4T6FQIDo6GteuXUVmZiYUCgV8fHwxadIk9OnTG9u2RYKIx9y5jzX61nQ6HZKTkxEVFYUbN26gsrIC7u5SjB49GuHh4Q153Eaj0SAq6jr++OMPJCenQCp1x/jxD2DYsGFtUibaqw0wGP/TpKSkkFTqRoMHD6KSkhKT6Wtra2nz5s00YEAoeXjIKCDAn0JDQ8jDQ0YeHjKaNGkixcREN6TneZ6OHz9OgYEB5OPjTWFhgykgwI+8vDzotddeo6qqKpN5VldX0+bNm6hfv74kk7lTYGAAhYQEk6ennDw95TR16lSKj49vdE9lZSVNnTqFAgL86MknF1FAgD/5+nqTn58vSaVu5OEho2nTHqasrKyGe/bu3Uu+vt7k5eVJcrmUPD3l5OfnQ35+PhQWNohSUlKIiOj69etkZ2dBU6dG0CuvvEy+vt7k5uZKvXsHUWpqCmm1Wjp16hRNmjSRPDxk5O3tSaGh/cnHx5tkMnfq3TuIjhz5ifR6fUPeOp2O1q1bRzKZO82YMZ3CwgaRXC6lwMAAksulJJO5k5+fL3300UekUCgavWtWVhYNHTqEQkP707/+9U8KCupF7u6u5OhoS6dOnSSe5ykhIYFmz55F3t5e5OXlQSEhwdSrVwDJZO4UEOBPn376KdXX1zd67qFDh8jV1Ynmzp1LU6ZEkIeHjAID/cnDQ0YymTv5+/vS5s2bSaPRNLpPpVLRd99tp8GDB5JcLiUfHy8KDu5L3t636nX06FF06dIl4nm+4Z7Y2Fjy9/elmTNnGDzvNl999SXJZO60cePGhnsTExPJxkZCEydOoFWrVpKfnw+5ublSYKA/xcXF0qVLl2jQoIHk6Smn/v1DqG/fPuThIaO5c+dQbm6uyb6nUqlo//79NHJkOMnlUvL19aaQkGDy8vIguVxKI0YMp7Nnz9Adr0I8z9Py5cvI01NOS5YspuDgfuTl5UEBAX4kk7mTXC6l4cOH0dWrVxvlxfM8ZWdn0TPPPEN+fj4klbqRp6ec/P1v9VkvLw+aO3cOjRgxnAIDAyg7O7tROX/4YS+Fh48guVxKHh5SCgrqRV5eHiSTudPYsWNo7dq15OrqTMuXL6O6ujoiItLr9XT9+jWaNu1h8vLyJKnUjXx8vBry9/f3pWXLlpK3txfNmDGdysvLG/IsLS2ld9/9N/Xu3euv79KfgoP7NXw7Tz75ZKPvS6vV0ubNm8nPz4f8/f0oLGwweXl5kI+PF61bt460Wm2XjnVMoDP+5zlx4gS5u/ekpUuXGAiKptTV1dHatWtJLpdSRMRk+u677yguLo6Sk5PpwoULtHz5cpJK3WjatGlUXV1NREQVFRU0YEAo9evXh44fP07p6el05cqVv4TWYDp79qxJYf7GG2+QTOZO06Y9TPv376f4+Hi6efMm/f777zR//nySy6U0f/78hjyJiJKSkqhv3z4kl0tp/PhxFBkZSbGxMRQbG0s//LCXhg8fTnK5lNaseZ10Oh0RERUUFFBcXBz961//JKnUjd566y2Kjo6m2NhYSkhIaBB427dHkru7K8lk7jRp0gT6+ustdOnSJfr999+pqqqKDh48SAEB/jRo0EBat24d3bgRRSkpKXTjxg368MMPycvLgwIDAygmJqahvBqNhubMeZTkcin5+/vRq6+uovPnz1N8fBxFRUXRhx9+QIGBAeTu3pP27t3bqI4uX75M3t5eJJdLaejQIfTRRx/RH3/8QefPn6eysjKKioqioUOHkJ+fD61cuZIuXvyTbt68SfHx8bR161YaNGggeXl50KFDBxsJ2c8//4xkMnfy8JDRiy++QOfOnaP4+Di6evUqrVmzhmQyd/L0lNOVK5cb7qmvr6fPP/+M5HIpjRo1krZs2ULR0dGUlJRE165doxUrVpCnpwc98MD4RgJ1z5495O7ek955551GE507hd0rr7xM3t6edP78uYbr+/fvJze3W20xbtxY+vLLL+nixYv0+++/U35+Ps2dO4fkcint2rWTkpOTKTExkZYvX0aBgf4UGRnZYt+rr6+nDRs2kIeHjEaODKetW7dSTEw03bx5k6KiomjNmtcb8s3JyWm4r6qqiiZOnEByuZQGDhxAX3zxBV2/fp3i4uLoxIkTNHPmDJLLpTRz5kyqrKxsuC8jI4MiIiaTVOpGDz44iXbu3EFXr16luLhYOnfuHL344ovk4SEjuVxKY8eOaeiPKpWKPv10HXl4yCgoKJA++OB9unTpEiUkJFBUVBT93/99SgMG9G+YGH711ZcN7Xzp0kUKDu5HMpk7zZ8/nw4ePEg3btyg2NhYOnr0KD3++OMkl0tJLpfS6tWvNdxXUlJCS5YsJrlcSnPmPEpHjhyhuLg4unnzJp09e5Zmz55FMpk7rVy5oqGcSUlJJJO508SJE+j8+XOUnp5OJ0/+SoMHD6LRo0dRXFwcE+gMRnvR6/W0adMmkkrd6LPPPjOZft++fSSVutHcuXMazbxvU15eTk888QTJ5TLat+8H4nmeoqOjycNDRkuWLG40YUhMTKSUlBSjg/edg/jWrV+TXC6lBQsWNNJI7tQSpk6dQq6uznT48OGG67/+emuiMnPmDKMDxZEjP5G/vy8NGjSQioqK7tCUtfTPf/6DpFI3OnbsmMF9Op2O1q5dSzKZOz399NONBvJbmmYM9enTm8LCBtOZM6cbCcjbgvv9998jqdSNVq9e3TDYFRcXN2iQBw4cIJVKZZDv999/Tx4eMho/fhwVFBQ0/BYZuY1kMnd68MFJFB0d3ahOi4qKaPr0aeTj4027d+8itVpt8E6HDx8iLy8PmjDhgQaLiUKhoMWLnyR3d1fauHGjwWSvtraWli9fRjKZO23Zspl4niee5+nEiRPk4+NNERGTKS4u1iAvhUJBS5cuJXf3nrR58+aG6++88w7J5VI6evSo0b5QUlJCERGTqU+foAZLiV6vp//7v09JJnOnJUsWU0ZGRqP6rq6uosBAf+rXr2+jNs7JyaHo6OhmLQG3+95vv51qsDrduHHD6Lu89tqrJJW60fr16xuux8fHU9++fWjo0CF04cIFgz4QFxdHAwcOoMBAf4qKiiIiIqVSSS+//BLJZO60evVrlJeXZ5CfWq2mf/97LUmlbvTmm2+QVqslnufp119/JblcSmFhg+nkyZMGbazX6+nChQvUr18fcnbuQadOnSIiosLCwgYr0rp164xayyoqKmju3Lnk7t6Tdu3a1fC8zz//jKRSN3r55ZeorKzM4L60tDQaM2Y0+fh40aVLF4mI6JdffiGp1I0++OD9RmmjoqIoOzu7xbGgM2CurYz/aTQaDa5duwatVgMfn5a9UsvLyxEZuQ1isRivvLICnp6eBmkcHR0xZsxo6PU6XL58BTzPw83NDebm5rh+/ToSExMbnHWCgoLg7+/fokNMSUkJvvnmGzg5OWPVqlVGt8E4OTnh0UfnQCKRICYmuuF6TEwMBAIBHn/8CfTt29fgvgEDBkIu94BSqURZWWnD9ZqaWsTExAAgo/nV1NTg2rWr4Hkezz//fCMHII1Gg71796KiohzPP/88xowZa7BGKhaLMXPmI6isLMTJkyegVqsBAJmZGaipqUZYWBgiIiJgbm7e6D6hUIjJkyfDy8sbMTE3EBsb2/BbQkICRCIRXnzxJYSEhDSq099+O4XLly/h0UcfxSOPzIJEIjF4p2HDhsPfPxD5+fnIyclpWG+/dOkSevRwwpw5cwz2E1tbW2P06NHgeR75+QXQ6XRQq9XYuvVrCAQCrFy5En379jPIy8rKCrNnz4JIJEJ8fDx0Oh1qamqQnJwMsVjSbByEysoKZGVlQSaTQyaTNZTx4sWL0Om0ePHFl+Dt7d2ovgUCIfz8/FFSUoQLFy5Ar9cDAORyOUJCQlqMiKjRaPDNN9+A4zi88sor6N+/v9F3mThx4l/r+/FQKusAAEVFRaiursIDD9xaG27aB273faVS2RB4JS4uDt9/vwseHp545plnIZVKDfKTSCSwt3cAAISGhkIkEkGpVGLjxg3geR4vvPAixo0bZ9DGAoEAffv2hYODI4RCAXr16gUA+OOP35GUlIixY8dh2bJlsLOzM8jT1tYWYrHoL3+L3gCArKwsREZGwsnJGa+88gp69OhhcJ+vry9GjBgBrVaLxMREEBEcHBzA8zx+//13pKenN6QNDQ2Fh4dHlzvHMac4xv809fX1iI6+AUtLKwQG9moxbVpaGi5e/AO2tvbYt28fjh49YiQVh5SUZAgEAiQl3RLePXr0wBtvvIk1a1bj2WefwcqVKxERMQW2trYmy5eSkoKiokJYWVljx47vDITcbW4PDpWVldDptOB5QlpaOiQSCWQyqdF7BAIOAoEAYrEYFhaWjQR2XFwsvL19jXrr1tTUIDY2Br169WoQLLdRKGpx7NgxCAQCnDt3HqmpaQAMg9IoFHXo0UOK/Pw8qFQq2NraIj+/ABqNBoGBgc2+p6WlJYYPH4HU1BQUFRUBAKqqqpCamgorKyuDSZZWq8Xly5chEomQkZGJd9/9d7NOjqWlJairq0NtbS0AIDs7G0VFBZg5cxYsLMybqUMhAIKdnR2EQiGSk5ORmJgIgHDo0CGcPXvW6H35+fkgArKzs1BdXYW6OiVSUpLh4OBgdKJ4u40rK8sxZcqUBoGlUCgQExONwMAgowLQysoKzz33PJYvX4o1a15HYWEh5syZY9SBsinZ2dmIiooCxwlw7NjPuHDhgtF0hYVF4DgOCQnxqKtTwtLSCteuXf1r0jjAqNPb7X4nkUgaHMESExMgEokxe/ajzXqJ19fXIzk5GRzHoWdPt7/uS0RsbCyGDBmKyZMnNysUq6urkZSUgCFDhjU4qp05cwYcx2HWrNmwsbExel9tbS3S0tIgk3k0OCpevXoVhYX5cHR0wqZNmyESCY2OBdeuXWuYrBARgoODsXjxEkRGbsOzzz6Dl156GePHj4eZmRnzcmcwOkpWVhZKSorRu3cfODg4tJg2MzMTZmYW4HkeBw7sazGtWCyBg4MjOI6DUCjEo4/OgUgkxtq1/8Krr67CyZMn8eqrryEwMLDFrTfZ2dl/aXDV2L+/5TxFIjGEQhE4ToCysmKkpqbA2toGMpnxwbGmphbFxUVwcXGFi4tLo0lETU01pk59yOhAk5KSAqWyDqGhAwwEb1lZOYqKCiAWS3D69KlWlFcIiUQCnudx+fIl8DyPgQMHmahbMQBqGETLysqQnZ0NV9eeBoKgqqqqYbJz5colXL16uYUnc5BIxBAIuIb2Njc3R0hI/0YTnjs9qktKigFwkEqlEAgEqK6uhkJRC57nm5nw3fn+IlhaWkIkEiMvLxd5eTl48MEIWFsbFyxJSTchFIowaNDgBqGVnp6G6upqTJr0oIE3NXBri9WECROwefPXWLv2Hbz//rs4ffo3vPzyywgPH9li3ysqKkJ9veqOdyET/d0BQqEQGo0GyckpsLCwaHZyUlFRgaKiYtjZ2cPBwQFarRZZWdkg4iGTyZoVyrW1tUhMTICFhQV8fX0bnqXTaREQEGBUU75NamoKRCIxBg0aBFtbW9TV1aGwsBDm5uaQSt2bvS8nJwdVVZUYNGgw3NxuTSIKCvIhEolRV6fAnj27Tfbz2+UyNzfHypWrYG/vgA0b1uOpp5ZizpzHsGLFSri7uzOBzmB0hIKCAhAR+vbta3SbUFNtj+M4PPLIbKxevdqo6bbpYHp7e5WFhQUee+wx9O/fH5s3b8Lhw4eRkZGBr7/+Gn5+/kbvJyKo1bfMkXPnPo7XX3/d5PsIhUIIhUKUl5cjIyMdAwcOanZrUmZmJioqyjF27LhGwXSysrIgFkswYMAAo5pydnY2RCIxgoODDQS+Wq0Gx3Hw8/PH119/DUfHHibLbGdnB51Oh5iYGNjbO7Q4sOl0OkRH34BOp4OX160lkry8PJSWFhvdIqTT6aBQKCASibB79x7RMj2ZAAAgAElEQVQEBgaaLI+lpeVfZtIE6PV6eHp6GhV8t7bARUOjUTcsTRAReJ7HkCFD8dVXm0weysFxHGxsbJCamgqOEyAkpL/Re9RqNdLT0yEUiuDhIW8oT25uLgQCAYKCgpoNiCQSiTB58mQEBwdj584d+Prrr/HKK69g/fr1GD58RLNl43k9iAijRo3BJ5980qr+bmNjg8LCQqSnp8HOzh5ubsbbsqSkBEVFhfD29oZUKgXHcTAzk0AgEECpVDabR0VFBWJibmDSpMkN5vHb6VuqayJCTk4OOI6DTCaDUCiEWCyGWCyGVquFRqNp9t68vDzU1dXB09Ozob/rdDoAwGuvrcbcuY+Z3FMvFAobJikODg54+eWXMXJkOD799FP88MNeZGVlYdOmza2ynDCBzmAYQa/XIyYmBjyvh6+vr8kT1pycekCn0+LmzSRYWlo2a6IzZs4VCAQQCATo06cPPvjgQ7i5uePLLzdg586d+Mc//mlUI+E4Dl5et9ZECwryYWVlZXJQvU1iYiLU6noMGDCw2YEuMTEBHCdopPHV19cjISEBOp3WqHalUqkQExMNrVYDDw/D393d3WFuboEbN66CCCatHv8dNHNRUlICb29v9OzZs9lB+fz584iLi8WQIcMQEBAAAEhIiAeARu9x52TB398fmZkZqKysbHV5FAoFrl+/DqFQ2OwkQKVSITo6Cu7u0ob4BRYWFjA3t0BVVRV0Ol2rB+jy8goIhUK4uroaba+KinLEx8fBwsK8YQKo0Whw48attvD29mm2790OjiKTyfDqq6/By8sbb7zxOj7//HMMHhzWbL93dHSERCJBamoKVCoVXF1dW/ku5cjPz0NY2JBmJ5O3td6goAiYmZlBIBDAyckZt5asUqBWq41ah65fvw6JRIJRo0Y1TDatrKz++kYKoFQqjVoqNBoNrl+/jvp6JYKCggDcWo93de0JrVaLmJhYhIUNMRDMer0eFy/+CZ7nERIS0nDd1tYORDxSU9NgZWXVapO5Xq+HUCiESCRCWNgQfPnlV1izZg1OnDiOkyd/xWOPPd6lYx5zimP8Twv0qKjr0Ot5BAX1Npk+NHQA/P0DER8fh2PHjkGr1RrVAhQKRcP/4+Li8OWXG1FSUtKQzsrKChERERCLxUhISGjx4JOAgAC4urri/PlzOHHiF4OY6jzPIyMjw+BEp4yMW9pcSEiIUQGh0WiQnp4OkUgEX1+fhoFMrVYjLS0VSmV1wxplU00xKioKjo494OfnZ/C7lZUVpk+fCWtrO2zfHom6ujqjA35hYWET824xqqqqoFarUVtba1AnPM8jOTkZ//nPR9Dr9Zg79zE4OztDp9MhLS0NIpEYvr6+BgOypaUlBg0aDL1ej02bvmpYd2/6Tv/f3nlHx1Vdi/u700fSqGtmNCpWteUqG4MLmGLAlICBAAmmOLz3CxB4TkKABMgjgVASQhJqEpKQAAYC5NEMxhhsggFj44JxxUWWbFnF6l1TNeX8/pA8nhmNpJFkmZLzrWXW4mpuOefuu/c5++y9T2VlZdg929ra+OKLnUyePDWs8E4ohw5VcvhwLdOnzwgakaKiIoqKiigr28fy5cuDM7lIV3ZbW1vYseTkZAIBP9u3b+83W/T5fGzYsJEDB8qZPHlKsBCR1+tl69bPSU5OCSuuckT2amtrWbp0aVjwlVqtZt68U8jMtNHQ0NjvOUIpLh7PxImTqK2t4a233ooq7w0NDTQ3N/cbKLpcLkpLpw/oOj8S0Dhz5szgOzvttNNIT8/gueeeZfny5djtdrxeL16vF7vdzooVK3j00UdQFBVW69GiPIWFhZhMibz//mo2bdrYT3b8fj979uzhk08+ITc3n3Hj8oJ/u+SSSzAa43j66adZu3Ytbrc7OGNvbW3l6aef5rXXXiM+PoHi4vHB8+bOnYtWq2P58rf4/PPPo8prZWVl8LvsHRhs4E9/+mPQo6AoCmlpaVxxxRUEAoHgOvtYov7Vr371K6n6Jd9EmpubeeKJxxGi16DX19ezf//+fv8qKyuxWq2kpKRgMBh4//3VrF+/Ho1Gg9VqRQhBe3s7q1at4qc/vZWGhkbmzJmDoij85S9/6fuIXZSUlKAoCnZ7NytXvsvatR9z8cWXMG/evAFddiaTCY1Gy4cfrmHdunXExcWTkpIMKLS2trJixdvcdtutOBxOZs6ciUajoauri6VLn6WmppobbrghqmFubm7iqaeewu128z//syTovuzp6WHZsmW0tbWTk5NLTk4OXq8XlUqFRqOhoqKcJ554jFmzZnP55d/p55LXaDRkZGTw7rsr2bRpIx0dHVgsFnQ6HXa7nc8++4z777+fd99dybx584JejhUr3mbt2o9pbW1h48aNpKSkBF3xTU1NrFy5kjvu+BlVVYdYtOhKrr/+BvR6PS0tLfzjH3/H4XCyZMmSqFHKNpuNLVs+Z/v2bZSVlWGxWDGZTLjdbsrLy/nLX/7Cvffew+zZs4Pu/m3btvHqq69y1llnc/7534pawWvDho2sXr2KSy+9jNNOO63PbawnNTWFlStXsnHjRnw+LxaLBZVKRUdHO2vXfsIdd9zOvn1lzJ07Nziz8/v9vPnmm+zZs4eMjAxsNhter5eamhpeeulFHnjgPoQQLFp0FXPnzkWlUlFVVcUTTzzOpEmTueKKRf1mpsuXL+fuu39BRUUFU6dORa/X43K5WLNmDStXvsO0adP47nevGNCDo9FoSE1NY+XKd9i0aSM+n5+0tDQ0Gg12u51169bxs5/9lN27dzN79uzg/V9//XV27tzBdddd32+gcUTGXnzxn9TUVHPdddcHg/nS0tKIi4sLDl7Xrv2YgwcrWbv2Yx555BGeeeYfOBwOfD4fixcvJi8vL+iFAVi/fh2bNm0mOTmF1NRU/H4/9fX1LFu2jDvvvJ329nZmzpzJpZdeGpTbnJwcGhsbWL/+E95+ezmbN29m7959rF69igcffJAVK5bj9XpJTk7myiuvDK6FJycn43K52bRpAx999BFJSckkJycjhKClpYVXX32FW265GZMpkcmTJ+P1evnFL+7iX/96ORi8KYSgra2NpUuXsm/fXhYvXhw1K+KYIjOVJd9UNm3aKAoK8oPFJrKyMqP+u+qqq4I5yE6nUzzyyCMiJydLZGVlivT0ZFFcXCiyszOFzWYRJSXjxQMP3C+6u7uEEEJUVlaKSy65WNhsVlFQkCcWLrxQzJx5gsjMtIhFi64Iy6UeCLvdLv7whz8IiyVdZGVlitTURDF58kRhs1mEzWYVEyaMF48++kiwqExNTY2YMWO6OPHEE8KKdoSye/dukZeXKy66aGFYdbSenh7xxz8+IdLTk0VWVqZITo4XBQV5Yt++vUIIIVasWCFsNqt44IEHgsVoouWpr169Wpx44kyRlZUpzOY0UVRUIAoK8kRmpllYrRliyZIl4sCBA8F85yVL/kfk548T119/XV+VN6swm9PE1KmTRVaWta+dxeKhh34rWluP5vyWlZWJoqKCfu2I5LPPPhPnnLNA2GxWYbWaxbhxOWLSpBJhtWYIq9UsLrpoodi8eXMwl3zp0qV9eeJ/jXo9r9crHnjgfmGxZIg33ni939+WLl0qiot7q6KlpSWFvC+LyMnJErfffrtoa2sLy69+8MEHgzKXmWkREydOEOnpyeKUU04Wp512qsjOtonly5cHz1mz5oN+hYEi86d/8IMbhMWSIQoLC8S5554jzj77LJGdnSlOO+3UqHnl/d+lVzz//POipGSCyM7OFBkZKaKwME+MG5ctMjMtIjc3W/zv//5cNDU1BgvKLFq0SBQW5ocVDQrl8OHDYv78M8QJJ8zoJ/9ut1u8/PLL4sILLxAmk0YkJRlFamqiuOCCb4lnnnlaXHHFFcJqNQfzyENrMdx0043CbE4TWVmZwmrNEMXFhcJqzRCFhfli/vwzRHa2Tdx33339nqe9vV089tijYs6cWcJgQCQm6oXVmiEWL75GPPvss2L27FmitHSq2Lt3T7/z7rrrLmGzWfp0QUrfPc3CZrOKqVOniL///amgXO7atUvMn3+GsNksYtq0KeLiiy8SU6dOFhZLurj55h+HFYUaKxQh5EbIkm8m69Z9wqpVq4b8XXHxeL73ve+FzTB27drJO++sZNeuXTgcdtLTM5gxYwbz589n0qRJYWvdjY0NLFv2Jp99tpnGxkZyc3OZOnUql112GWZzbOuSHo+HTZs28emn69m5cyddXV1YLFamTJnCggULKCkpCc4i9+3bxz//+QJms5kbb7wp6rr7+vXreffdlRQXF3PNNYvDZmkOh4M1a9awd+9euru7MRj0/PSnP0Or1bJixdts3ryZ008/gwULFgwaN1BeXs4HH3zA1q2fU1dXh8lkYtKkyZx88snMnTs36Dru6OjgyisX0djYwEsv/Qu3283q1b3uU4/Hg9lsYcqUyZx++hmUlpaGzZY3b97E8uXLo7Yjmqv7/fffZ8uWLRw4UIFOp6O4uJhZs2Zz6qmnBiP9fT4fzz23lMrKSi666GJmzZrV71put5snn/wzbW1t/Nd//Xe/5Qe/38+uXbv6atFvo7m5GYvFQmlpKXPnnsyMGTP6zagdDgerV6/mo48+orx8P3l5+UyZMpkFC85h3brevOVrr72W4uLxCCFYvXoVn3yyjtmzZ7Nw4cKobW5vb+f999/nk0/WUlVVRWpqKtOnT2fhwoUUFhbFHAPS25bVbNu2nfb2NjIyzEyePIl5805lxowZwYC8xsZGnnqqd7vdW265NWpqZnV1Nf/4x99JTEziJz/5SVTvR0tLC21tbXR0dJCcnExqagpqtYZFi65g69YtvPvuKk488aSwczo7O1mz5gM+/PDDvowUPVOmTOGcc86ltbWVjz/+iPPOO5+zzz47anzGkaUQt9tNUlISGRkZNDc3s2jRFWg0Gv71r38FAzFD4yjWrl3L2rUfU1ZWht3eTVFRMVOmTOWMM86gqKgo2D4hBFVVVbz99tts3LiBjo4OiouL++rqnx1zfMdokAZd8o0lEPATCAwt3qHR6pFrmw6Hg0AggEajISEhYdAdnBwOB16vF71ej8FgGFERiUAggN1ux+/3o9VqgwFBkb85Egw1kIGL5TdH2njE/XrEUAkhgkF+seBwOOjp6UGtVhEXF99Pge/evZvvfvc75Obm8vrrbxAXF4cQgq6uLgKBwIDtHE47Io2xy+VCURTi4uKiDniOtFOtVg/4To/0zWC/EULQ3d2Nz+dDq9UOKiNHn8+Fy+VGr9cHjX60ew3nXbhcLjweDxqNmvj4hBHttBYICOz2bvx+PxqNhvj4+H73FUIEi9cMtNGIEAH8/gCKAmp17HHXW7du5bLLvk1qahrvvbdqwIC73ra6URQV8fG98ubz+YLPHaucALz11pvcfPOPOfHEk3jhhX8OmEng9XpxOp34/X6MRuOgWzAfkYkjvx2o5sJYIKPcJd9YVCo1oynMpNFooq7ZDjQoiHVXtcGfWTVkQZpYFHysBjlSKQ9HGR4hPj6+X5W1UOrr6+ns7OCEEy4JKkJFUWLq2+EMLI5gMBiGVKKxtDOWnbEURYmpgFD48/VGyg91r+G8i6GMTGyyN3RbFEUZsl8URYVGo+o3OFqx4m3Gjx9PScnEsHcaCATYt28fDz30W7xeL1deedWgs9lobdVoNP2ey+Vy8corr7BgwYJ+O9/19PTw2Wef8cgjvUF4V1yxaND+02q1w9IFw5UJadAlEsnXgq1bt6JSqZg9e86I9+iWfL3ZsuUz7rjjdpKTU5gzZw4nnTSLrKwsmpub2bZtG//+9/s0NjYwf/6ZLF68+JhsM/r228u59957eOGF55k9ezYzZ55IcnIyhw/XsmPHDt577z26u7u48sqruPDCC78R/Sxd7hKJZMzw+bzcdNNNfPTRh7z44stR16sl33x6C6v8lQ8++DdNTY1h6VuKopCRYWbhwoX84Ac3DlinYLhs376dJ598kg0bPqWzs6Of98NqzeTaa6/l6quvibnmhDToEonkPxaPx8POnTvx+31MnDgpZrel5JtHbx2HKqqqqqioqKCrq4vExCRycnIoLCxg3Li8ES35DIbf72ffvn3U1dVRWXkQp9NJamoa+fn55OfnYbNljfmGKdKgSyQSiUQiGRayUpxEIpFIJNKgSyQSiUQikQZdIpFIJBKJNOgSiUQikUikQZdIJBKJRBp0iUQikUgk0qBLJBKJRCKRBl0ikUgkEok06BKJRCKRSIMukUgkEolEGnSJRCKRSCTSoEskEolEIpEGXSKRSCQSadAlEolEIpFIgy6RSCQSiUQadIlEIpFIJNKgSyQSiUQiDbpEIpFIJBJp0CUSiUQikUiDLpFIJBKJRBp0iUQikUikQZdIJBKJRCINukQikUgkEmnQJRKJRCKRxILmy7hpm9dNvdtOmauT9h4XakVFgkZHviGBHEMiaTojakUZ8PweEeCgowN/wD/iZzCqteTHJxN6l2aPk6YeB4ijxyxGE+laQ/j9AwEqHO0IEeg9oECy1kiWIWHI+3oCfiocbWH3MGn15BgTw57FKwIcOAZtLIhPHvX7qnJ2Yvf1jPh8tUpFQVwKOpUKd8BPpaOdgBCjeyhFwWYwkaLVD/vUCkc7Hr8v7FiKzogthvd39N204w8Ewo5nGk2kRsjKUKzvqKelxxX8/3i1ltNSbOhU6pivYfd7aXLbEQzepwoKBkWFolKhV2tJ0RpQhrh2t6+HGlcX4sj7UsCsTyBDZxzyubp8PdQ4O8OOZejjMevjwo45/F6qnJ1H7zECUnVGMmN8f6G0e93UubpHJYpDvfcuXw/17m72Ojtp97oAhQSNFqsujmJjEsk6I4ZhvO8j19vlaKfb50EA8Wod4/Tx5Mclkaw1oB/G9SJlu9njpMzRTr3XSXePGxAYNXqy9fFMjE8lZRjPKxAccHbi8XmDxwxqDflxyagUZcjzy+xt+EJ0oFalpiA+BU3IuQI45OzEGaKjdGoNBXHJg9qRI5Q72ukJ0Qeh+ir0HrWubrq87pHPnhWF/PiUYb3rr7RB7/B5WNVUydKWA7zncfR1kxLSZTBZY+DyhHS+lVFAaaI5qmB2+Xq48cCnfOxxjPhZfmay8OuS09AqR1/axvZaLqreFva75fmzWJiRH6HkPEwuXwshAnS2IZG/j59HnsE05GBmyr4PIUR5/S51HLcWzg4TPoffy7UHN7DZbR9xG28zZfCHiWeO+r39q3YXd3YcHvH5J+niWDHpbMw6Iy1eN1eXf8K2UQwQjhj0jwtP5rTU7GGf+vChLfzV0RZ27Lvxqfx5/Kn9Bm/R+LjtMN+u3IQ9bLAlWJ0/hwUZeTE/R1OPizsqN7PeF6IkFBV7dWdSYkqLfcDl7uaEPR/QIwIx9Bug0rBAa+A0YwoXmAuZZEof0AAccnUxrewjCGnrdYkWfls4l7QhBlPVjnamln0Y8o3DmznTuThzQvjv3HbO2v8xDRGDrOHwkqWEK8eVDvu8HV3NzD+wPuwZh4fg3wUnc1Z6br+/OAM+3m06yKvNlfyfuzOqvrOptVwel8q5abmckpJNkkY34J2cAR//bj7ES80H+D9X5PV6rzlOrePbcSlclJ7HzGQbiYNcL3KStLOriTcaK1juaGG3zxOlTwRZah2XGlO41FzASck24tWDmxCfENxTtZWXupuDx2xqLf8qmMO8FNugvS6E4NaDG1npPjrgutSYxNMTzyQ5pF1+EeCx2p080VEXPJaoUvNG/mzOTMsZ/B4I7jy0hTdC9EGovgp9ltcayri1+cCIZXSqWsuKKeeSq48fMxt73FzujR4nP9u/nkWHd7IqaIiVCE2jsNvn4d6Ow8yuWMed+9dx0NkRdd6hQQFl5P9USnRdp4743UDCkBnxu7Webh6v3o7d7x2yLywRz64MMIrUjbaNI1ZS/ftlNM+hVY5tu1AUElFG3DpVlPu/4mxnWWMF/iFmiY09Lp6s34NdBPpdQxnmA33aVstWX09Q9kEBIXi7qYIAYlhvyBpr36FAwM/7Hge/7KjlhPK1/PrAJtoGmXlYIq7xj+5mXqzfizeWAUSkrEd5a4oCCaOUCWWEwqAoo5fFaPe2+708cnALl9fs4BV354D6rs7v44nuJi44tIUb9q5hU3tdVO9Vt9/LHyo/5+KabX3GnCgGV6HK7+Wx7ibOrNzMkn0fsamjnqHe0mG3nfvKNzCvfB0PdtaxOyiT/d/lYb+XP9qbmH9wE7eWfcyhCA9MVA9dxLutC/h4oGYH1e7uGM4N1z3qAZ4sUm93iQC/qt1BubNj2PfQKmOjB3WKMuZ29rgYdJffxy8PbuQfjpaQselQA1/BY92NPFi1FV8gwFedHuC5rgaer9+Hb7TuZMmXwh+bKyhztA8623i1YT/LXJ2j/yYCPl5pOYgrytfwUlcDDW7H8Wm0ENzfUcsvDmykO4bBaK9iEzzUfIBVLdXDHHj8Z+AXgmdqdvHL9uq+OWBsvOLu4mfVW2mJGFx5RYB/1OzinrYqlGHoln+6OvhV9TZaQ5Z0Itlnb+XG/Z/w687DeMRw9KzgKUcr3y/7mE/b64bdR6s93fyhajudo/XUDcK6Hie/q9pGm9fzHyN7x8XlvqWznlfsrWHHUlCYqDMyXp+ARwSodHdT5e+hPkRg81QafpQ9Fa1q6HGHCchV1DHP2kJd7ceKdiF4vLGciXEpzB+BK7j/JxNOPJD3JbcRwACMU1RoY3ySBEUdZg40itLr4Yg0mEBzhMJKRCFeiT7qP9bj3V2+Hv5yeDe/LZob1ZW4x97Kn1oOHpN77ehsYrW7K+rftvs8rG2rYZFt4oivn4FCiqKEyVAAcCFoFYJIFfdidxPnNFVySeb4mOSyLuDn14d3UhSXREl8yjGXsQwULMOQX/UxnP3kKwrxMc51vIh+krjP2c4TrZURcgwTtQZKDIkIBBVuOzU+D/UiwJGFhnhF4ee2yf3iE6qdXfym9SBKiE6IB6ZqjRTpE9ApCgc8Diq9LupFAG/Qi6hiibVkwHiHSlcXPzqwkX/3OPrNRFMVhSxFTZrWQADo9Lmp8vtpj9BKa3xueg59xpOaU5hqSh9WP7/Q3cDEhjJuzJoS03r6SPg/ewsT6vbwk9zSMdGH4xVVr8cxBhIVFWM9Rx9zg+4XgnfbaukKEwSF32dO5LuZEzD2rd35RIBd3a280VjOsq4GykSAe6wTmJyQHlWh+CIE6xR9PC9MPCvmDtMoqjF5wfsDPu6v2UGWIYHxcaMISBP92zhdH8/rJfPRxPjcY2XQC1VqXi6Zj00XF5sbSFFIUveueaVp9fyx6JSobsVDjjYur90e5lT7QUo2V5iLovq/hopXGAl/627grNZqLjbnhynqbr+XPx/eTVmMs9ihvom3WippHWS29XxLJReYCzHFuAYayZJEK/89bkaYBPlEgE6fh71dTfypqYKNvqNmvQt4sbmC8y2FMQdUbfS6ub9qK48Wn4xZaxy5qAuIDP1cnJTJXfknxTy/PZaBRo/ZpnLKMGIh4tXaMN30RWcjNRHBrHek5bEkd3pwoOgXgjJnOx+2VLO0rYrtfi+3JGczPy23nw7b2FFHS4iX0gjck57PDTmlwesFhKDc2cGqlkO83FbNLr+X7yfbOHeAdjj8Xu6t3MxHEcY8BYXz4pK5MXMi0xIzetsmeoN5N3fW81JjBW84Wgj1Y63zebiv8jP+OnE+acMICu0Ugocb91NkTGbBEGvdI8WO4I/NByiJS+bCjLwRTwNEn4cu8ujL409jnDExRs+WMmiMxNfCoAsEO93dYZ9lqdbAxZZCTCEfgkZRcVKShZmJZq60t7C6tZpLLcVRR94KfWvoocYLhTSNfsD16OPJhz0OnqjezgNFc0nW6Ed2EYV+M2ANKlI1hpg8FmOJGkjR6If18QaVkUrNjAFG8vFRXH65ujhmJmYct7Z5heCR+j2ckGgmty9qOoDgvZZDPNXdeEzucdDZwf91Hb2WHphvMPFeyJriux4727qaRhT0B5Cq1gafP5ITTBlMNZm5qvwTdgeOBqJt97qpdHUNa8b9qqOVaYf38JPc6SOOrFaUvnXMCDlJ1eq/FPlOVGtGJNtHNN4OVydhjmRFxTXWCWHKXKPAtIR0piakc7G5kFcaK7g6c0LUgUlnRPBvhqJwiWV8uHFQYHJCGpMS0rjUXMRz9Xu5LnvKgIP6T9pqecfZHvQOKIAJhfstxfx31hTiQj1UCmhVKs5My2VOso0ZNTu5r/kATSFa/TVPN5c1Vw7bq1QZ8PNg7Q4KjYkUxiWNyfusFQF+fXgXecZEpiakjVQdh0XWHyFZoxuFrBx7jotlcIvw0epOfw9Ob8+As7lppgx+mjcz5gjNryJ/7m5mad1eer4G6/+SCGXX4+Sl+n3Bd1fl6ubh+n3HaIALq1qrqAwxpFPVWn6bdxKlEYO/V5sq6BlF2uJgTEvM4Fvx4cqtQvhxD3O90Qv8vqWSt5sr5Xp63/v1RL4zEaC5xzmgociLS+L2/JlR014DCJyB8Oh/p4A6j33Q691TOIcsffQBnSvg5+mGMlpCZpwCuCU1h+9nTw035hHEqTVcl1vKjSlZ/b1KzQdpHWZalwA+6nHy2+qtwz53OPfY5HXzUPU2mgaJJ/gmMOYGXUEhN8IdJwJ+flm5mY3th49ZwEIwAvFLwhYxslYQPNRUwcdtNcdUzX0FHBDfAK0bPsgap6goVevCPoY/tVWxpasBrwjwUv0+NnnDFcG5UZSlLoYljpYeF8vba8N8L+clWpmSkMb1qeGpTy/am6mIIUp3pMRFzixE8D/hRiXC1Rgp660iwG/qvuCL7tYIY8SIs8G+XDFXRnGmQl7EUpQK+MWhLaxoPECjx8lwhvgqFBIjBnotCH5VtZW3Gito8jiHzMyIZL+9jU0hAwIFOFGj579sk2JautCr1NyUU8psdfiE690ee7++FXMAABcqSURBVL+6A9HIUFSoI9aTX+hu4YX6fUNmTgQzVIbAgEJ8xPf4oqONpw5/gfsYDpIVvloKecxd7ipF4VyThRe7m8LcUM8723m+Yh3n6U3Mj09joimdUlMGmYaEIdd+BaLf+nKd38urDeUxGbx5yZlk6hOOaTtPiUtmoi6Bh9qq8PSpxSYR4N6a7RTEJVE4zPV0IXrdv6E0+3t4rbEipgCgk5OsZI3BGjP0rn2903KI1Bg8KHnGJE5KNH8F51FHmajRc7V1Aotrd6CI3lXbwwE/T9TuYrHXw8NtVWG/X2IyMy/RwqrDu8KOxxKuuK6tlvdDZms2ReHijALUisK56XkkNR+gs0+ptQvBe82VlMSnHvOgIXfAT21EtH6WSoUmZBmsVw4FkdnhVyRn4exx8jd7S/DYNl8Pv636nCcmnB7M5ffFGDUdbQ19j7ub1xrLhxwMKyicl5ZLwjH05n3U1UhzDGbXqNJwdlpumBFUgBmmDNKaKmjte/oAsNrr4r3qLZxYb2RhfDpTEjM4wZRBuj6BhCFyuScmWqC5PGyg8ZHXxUfVW5lRt5sL4lIoTbIyM9GMWZ8wZG74ju5makLejQDON2XEvBYMYNHHc1myjU2th8LexsbOeqYnWQY9N1tr4O7UXO5tPOol6EHw+6YKJselcFZ67oAptxoltlmoW6XiWWsJd9Xvpa6vrQrwcOshpsSlstBcMKxASkF/fQwKK1urMHcPHT+SYzAxO8n69Q+KU4CzMvKY21zOWq874gNVeM9j5z2PHdoOUajWcaExiTNTx3Fyio30AaIzFZR+a+hbfB6uqNka05v5XHfqMTfoCYqaH2RPocxj5xVH76ccANb7PNx/6HP+UHxKTEVLQmfi2giB2+PzcGXNtph6/bPCk/sZ9EpnJ+4hineoVArF8SmD5rBXiQA31u0mlgTE35uLx8SgCwQVjo4hUxo1KhXFkWvCEQNGBYX5qdnc5Wjj123VweNvujpZW72V9r4PWQEma3T8IGsKdVFmIkOl/dj9Xt5sDR8cnGJIYkpfTEGOMZEbTGZ+39UQ/Ptz7TVcYZtI1jEsRuEK+Hm5bm9fsZOjTNboyYyQGeVI/mzIqx6nNbLAOp5dFZ/yacjg5E1XJ0XV2/l5/okYVZpej4UYesIbbQ39DVcHb1RvjUnWG5Osx9Sg39tRCx01Q/7uQl08J6dk9ZvVnpBk5bL4VJ5ytIZ7K1DY4nWzpe/66SoNF+hNLEjJZn5aDrYBBuAzksxcH5/B3x0t/f62zedhW1cDdNVjVmk4X2/irJQszk7PI3MAmamM4q4vTcgYlrFRgJMSzRhbDxHqu7LH4NJ2iwCXmwtp8br5feshnH2apE4EuLt2J1lGE5PiU6Oe2yNEzFUmv5WeR4ffyz2N5XT1hVd2CMG9dV+QazRxwjD0kkJ/fawCftiwLyY9eG9qHrMSLWMe43Vc0tbSdEYeK5jDzQc3stHrpmeALjvg9/K4vYXH7S2c27CX/82eximpOcMYScXwO2Xs1vnMOiN3586govwTPg+JIH7O0cr4w7u5LXf6l+oO/F3NDv7Z3TTob0rUOj4tvQBVTAFOSgy/GBsB9gvBbVWf8+EQLulzdXG8PPW8CK9P/2cyqNRcZ5vMp/ZWPuyL/PUA9SHuOYHCTy0TmGxK43AUgz7UGvLu7haedx6tSBUPLM4oCAaT6VVqFmbk8/uu+uAzlvu9rG+t5ju2icPqyR3uLpY17A8tSEgAQXWPk+32Ft52deAM+aMBuCY9f8jqb0d6YlJ8KndnTeX6qi3BiG4X8Nf2Worjkrk6ohrc8Zb143Fv1QDSHafWcE/BbFwVn/KqqwP3ANdvCfh5ztXBc64OTm7az83WiXzbWtzPQ5mg1nJvwSxcBzbwqrMdzwDXawq53pnNB/ihtYTzzYX9Bhz9iwgJsnTDz1LQa/TEKwquEDmq83rwBALohwjcNag03Jg9hT2uTl53tgf9IRu9Lh6s2sYfik7GrBtdsJlWUfE920R2OTt4vrsp6Gna7vPwYPU2Hiueh00fN+LrB4ajB4/TWqnqeH0apYlmXpl4No9bJjBLoyNpiE5Y1ePkvys383bTga9VsE1JQgr3ZE/rl0P7p5ZKVrYc+lJbEhAB7EP88wv/16avY2mPCMQuPXlGE7fZJmEeYMnnelMGl5gLR1SBr0cEeKc5PDd5gkbPnJSssKtNMZm5RH/U9ekCnms+iDswvLKoT7s6uLRmO5fVHv33ndod3NZUzgvOdjqECCokDfAtQyLnZRQM6x7z03K4NaMQU0gLmkWA39fvZUtnI//J2AwJPFlyBi9nl3K21kjGEAp9g6+Hmw7v5M9V26KuI2caEnhywum8kDWN07RG0pXBh8prvG6ur93BU9Xb+5UE1kYZrI9kb4WAEP2WSowqVdQqnNEGS1ZdHHePO4ETImIE/ulo5ZnDu/Ecg4DiVI2eu8bNYJ4uLqy/XnN18mTtLlx+/zdK7o5bLXcFsOjjuCF3GlfaStjZ2ci6zkbWdNVT7uuhKooQHxQB7qrdycxECzlGU8h4sn+OtkVRmKkb2i3pR2BQj12zVSiclz6O/3V2cHNTefB4gwhwX+1OHlJrY6yU11u0Ikw4FRWzdcaYZr1a1di10URvvWNDDEFgpq9ZpsKZaTl8v7OBB9vDXa6lah03ZU0ecR5pjauLv3XVhx0r1sWxvbspYu1dIVWrI3Qa9pnXyca2OuZHqRc+WuJR+JYxkYeLTo5agESIAO4BlL1OUfH9rMmUOzv4a3dTcICwy+/loaptXG0uimmSHW0NvUilYYLWMOS3ElAUVMe43sIcjY5U9dDvOVNrHHRGlKDRcXHmBBaYC/iiq5l1HfWs625kn9fFvojALAG0CcEDzQc5JdnGScmZUb+ly20lLDDns7e7hU2djazpaqDM62J/lECvViH4bUslc5JtzAq5Xv90QIUdznZOTssZVj81ubtxRMhGukY/ZAxUvKIKxjpNSkjl/uxpXFu1haaQa/2+pZKpcSlEVn0wKKphv+98YxK/yT2BKw98GmZn/txWw7S4FDwxDGai56HDfK0xWEtlMNI0huPicDruu62pUEjS6Dk1LZd5abn8yO/loLOTnZ0NvNFWwzJPd1hFpP0BHxvbasjOmhTsj2h56LN08Sybel5Mxm6s3R9aRcX3siaxzdnBUntzUCB2+r38rHobnbGY9Ch56FN1cSybcm5MBWOitTGWgUQs49V8lZpnJ5xBdgzrumPZ1bFMKsQwfSJGlYbrsiazwdHKR33rwyYUlliKKR1mJayjrjnBhy3VNEUo3WXOdt45uKnf7yOVWLMQvN58gNPSco5pRbQZah0/sYznIkvhgPUSFEVBO9iATa3lttwZ7C1fF1yqAHjD082eut0xuiP7r6F/N8nKA0Unx7QD27EOGPx15hTOsBTGps+GuLdCb+GZ2Sk2ZqXYuKWvAMzuriaWt1XztquDdnFUStsQvNtSxQlJ1gFrcCRr9MxNyWJOShZLRIAKZyf7u5t5o7WKFRHXqxcBVjQfDDPo04z9A3R3dTXhCfhjriXgF4J3O+v7LZ+ajUPnkvcQCH67KhTOSh/HrY527myuCP6mHcGPD++gK+L9+xDD/qYVYFZyJndbJ/Lj+j04+s7vRHBL3Rcxedyi56EL/l58Kvkx5M8ryvGJiP9Stk8N7aQEtZZppnSmmdK52Dqe02p2cktIeU0fsNnVwWVCDGmIVShficIy9H10d46bQVX5Oj7sMwwBYKfPM6oeU6GMWIHdapvMEn/xEH3Ym1ISiyJTfYl9rVYUfpcznd8EBq/cplHUUQtCDEaBMZGfZE6irHor9SLApQlpfMdSPOLNbjq8Hp5uOxRFsUGslaxXOtu40d7CFFNsRXZOV+uYbjAFVV+dz8Nyjz3sfvlaAwvNBUMUP1J6DcsgOrQgLom7c0qprdxMecjSwD5/zygkvVf9fRnfs0phTGT7SHsmxKcwIT6FCyxFnFVfxvfqvggbdK9zdxAQYsjBm9I3eZgYn8LE+BTOMRfwSl0ZP2vYE1ZCudrdjSvgD84kJyVmMF2lYXvIu/qLs43vdTQwJzUrprbs7G7mY0d4mqJeUTE3yTrkuZHR4lpFxfezJlHm6uDZkMyJyigBvD4hRrTNrlpRuMxazA5nO090Hq09Xz/KFDZljGTlK2/Qyx3t7LW3cn5GwYCVzkwaHd+1TuCW1sqw6Zcj8PVc5xgfl8wd2dM4dGgLhwK+Lz0SoOQ4Vlwb+8GgwuSksUuHOyd9HNd0NfBeVyM/zpoStl3jsLwIwKftdewcZdGMyoCfVS1VTDbFFo18eaKVHxbNCf5/a48L774PWe6xB+XwDXcXC+rLuD5n2qhn/vNSsrjVOZ5bG/aGBUn9p9LocbKmrZqFGYUkaKL7OPQqNQvNhcxqOcjmkGwBh9/Xz59W53Gwoe0wZ2fkDbjsY1Rp+HbmeN5oqWS59+j13EL0pRD2GvQ8QyJnJqSxPaRaoRq4r2YbfzOayBkifa25x8XD1dv7uflvSEgn0ziy7KF0rYE7cmewv2I96wcowjNakjQ6fppbSkV5d9iWrN8kjktQXIPHwc8PbuLi6m08cHATe+2tAxZDqPc4+vlSC7VxQ6e+AF+xHP/elL3UbG43F4cFDo12RCgZJSKWHGM1P8yexq9sUyiNcVasV/q7Kz0BP882VRCqovJUar5lSOTCIf7lhcRBKMCyjsPUu+0xDyRCSdMZuSOnFBEhQHc3lbOls2H0MwNF4ZrMCSxJsn0jhoujocvXw32HPuOq2p3cXPYx2zsbBtyBscvXQ0dEwKNZYwj70O1+L48c+pzLa7dxS9ladnQ2DZjj3+BxcDjCa2XWaEkIqS+gUhSuzZxEQYgnzg+82+PkR+Xr+LyjIWogsl8I9jnauLtiAy+6wrNL0hQVi60lGEcRuzM+PplfZk0lS6UeM1WebTBxZ04p49XaY3KP/7jCMh0+D7879Dmvu7tQgPvaa/hnZz2Xm8ycnZJFtjERrUqDXwQ45Ojg4fo9YecnANNMaWHuzmiFZer9XpY1VMTcvXEaHaenZh/TTR2iKzoVV2ZOYJernb91NhCrryFaYZkWfw9vNlTEPJuKU2s5PS3nmLexSwjeaz5EWoyzVpWiYn5azlenlG+M/ZdrSCDLUhRzf0eLTt7Z3cyGiHzvW9LyuTZ7ypDXe7OhnP+q3x000Ot9Hta0VnNN1qQRNXtWso0n0gv5cchaZbMIcF/VVp6PO5M0nXFU3Zqg1vLDnGl84e7mvQF2khtI1iO/izJ3N282VsTsXjXr45mbnHlM3J+fdDXSPoytRPPjU5jeF1/hFQGW1n7BM32z32ecbbxdvo6r49M4IyWb8fEpaNVaBIImt52n6vexP2QLUTVwnik9KHM9gQDP1H7Bw10NgMKzzjbeKV/L1aYMTk3KpCQ+DZ1GQ0AI6l3d/KOhjM8jNhDKi0/rpxenmNJZkp7PL5oPhOWRv+Wxs6liHf8v0co5qTmk64woikJHj5t32mp4q7uR3VE2KLorLY/SUXrMFBTOTMvhTlcnP2oogzHwaSrAKUmZ/DJzIj86vIuOGOVroMIyq1qrsHQZY1Q7CnNSbFh1cWOm2sbUoAtgeeMB/tZXKONIdxwM+PhdZx2/66wjRaXGrKhwiAC1UVzrM3RxTDWZ+734yKC4z3weLoup6Eov5+lNzEq2jrlBP+LquT13BhX71/JvjyOm0o/RCsvs9nn4Tu32mO97oT6Bk1Iyj3kbD4kA1/cZmtgkWUV1YsZXqDZ/7Ep/OK7oyFlNAMHbzZU0hCiCOJWac9LzYoqWPyt9HLOb9rMpRIG+21bDRZaiEfWlWlG42jaJT7oaedVz1OX4YY+DZ2p3cVv+SaM2iLkGE/flTufggQ3sj3V/9ShBca+5OngtpsIyvdyWZGNWspVjsUHl3R210FEbs5Z70jopaNA/ba/jty0Hw3LPm0WAx+zNPGZvJk5Rka1S40Nw0O/vZ7RsKjXzUnOC7djQWc89zRVhgcJNIsCjXY082tVIsqLCqlLjRXAgyprzVJWGC9JyowyyFW7MmUa9x8HjXQ1hgZgNIsBvOuv4TWdd3+BXGdCrpaV3Z7/rckpjKn08FFpFxTWZE9jrbOfJrrFJfVQpCpeYC/nC0c5D7TUxa4xohWVuaoh9j4ckRcUHRtOYGnTVWKvNS63FPGQuIneAl90e8FPm90Y15jmKivuyp2HRH/sOON6u63EGE3flzqBAffziEL/cPdnCO/s/caXgoLOLtzrrw1T2TQkZFMRYBjjLkMD8xPBykS+5O9nR1TTiZ0rVGbgtp5SkkO/RBTzeVs2HrdXH5Js/IdHCLzInkXAcP7IvT77C7zw3OZMnsqYxWaWJ+v05RYD9fi8Ho6yTp6LwG+tESkKqpM1OsvBM1jQKB3Bld4gA+/zeqMY8TVH4iWU84wfYYSxOreWXhXO4O3UcSYO5TwYw5umKwi9Tc7mrYBYmjfaY9WiyRs9tuTNYcIyreUZ6k27OKeUyY/KI9eRws+T1x0FOx1znJ6i13JQ7gzeK5rEk0UJhDKM4LTBHo+eZcSdyamrON8YYnJKUyS+tE0mRC+H/Efy75RD7ItZHz08bhy7G7W8V4NvpeVgj5GVZU8WoNpg4MTmT+9PDi8gcFgF+V7uTeo991O1WKwqXWwq5LSXnP+6d61RqLsssZlnJfH6eks2kGL1jpWotj9om893MkjCvkEGl4ZLMCbxTcga/SslhYoxr1NPVWh61TeGakHTfaCRqdPw0/0ReGXciF+kTiKU2mwE4RxfHs7kzuT3/pGGVtI6VfGMiP8+eRskY1tPI1Mdxe+50pn2Nd/WM5LhMF9WKwsxkK9OSzNxkb2NzZz2fdjVR4bHTIgJ0iAAGFHJUGnJ1Rs5LyeHUtJwB61erUJiki8M2CsOYpo3r556LU2u5KmRUKISIupWgWlE4RxdPIKT4RE4MQq1WFC61FFHl7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CONVOCATION EVALUATION
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A l\'attention de part 5   part nom 5

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 4   part nom 4

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 3   part nom 3

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 2   part nom 2

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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CONVOCATION EVALUATION
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A l\'attention de part 1   part nom 1

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Vous êtes convoqué pour une évaluation de type : TD.
L\'epreuve se déroulera du 08/11/2025 11:00 au 08/11/2025 12:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 08/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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0RhuKMU/Zqs5woAbCtKhprveBAHIQQQGjEdhNo44S15MLyMfCwfVuRhT0EydN0YcEVHPLYVJKLESJ5v9wzEYLueXZKvhVCEXveRMAeA/Px8bN68qU1BVgDgt99O4bffTjcKI9we9Ho9fvzxx1Z5tIvFYjz99LN47733MHLkyGaF+Z1apkwmw7Jly7Fly1b07t2n4TeJxAzLlz+NTz/9PwwdOqxTNd/W1gnRvR3ISSAQYOLESQgPH2ky7ZUrl3DixIk29aOioiJ8++23JpdGxGIxFi5cBDc39/taPjGB3laTBsehl42hx7yCCIVqZbufq+J12F6cgoomBu/nrJ0RZPNfr1pbkRmed/ZtZFrhAeytK8dNRXmXdpRJPTzxumsgHJvMxOtBWFt0E6cr8rrNSe5mXSUO1hSj6RRmtJkVJrn4QMgO2+g0wbNnzx5kZma0fXIoFGLjxg0oLi7uUBkKCgpw8OCPrcrv6aefxcqVK9u8vUwkEmHkyJF4//0P4OPjCx8fH3z++edYvXp1qxy/7mfs7e2xbNkyk+vDHCfA9u2RyM3NbXXf++mnn5CUlGgy7ahRYzB27Nj7vi2YQG8HjhJzND2NRglCja793q+xNSU4r6oxuD7LxbeRQxcHYJyzF3ybrJcrQDhQnNqlWrKQ4/CYey8ssHOHWWMFHtm8DmtzopFW1/UBOAjAn5X5KDTyrk+5+MNFYsE6aSeRkpKCPXu+b7emePNmEg4fPtyhEKDR0dFITU0xmW7WrNl49tlnTWrlzQscDqGhofjiiw2IjPwOERFTWhURjQEMGTIU06fPMNlPUlKSceTIEeh0OpPPzMrKwu7du0xq9NbWNli0aCHs7Ozu+3ZgAr0daHjeqJBpr26qIx67i1INDkSZa2GHUCOmY0exBZ519DTIf0d1IdK7OHqZrVCM1Z4DMNnC1qDzXNCq8K+s6yju4m10PBHO1hSj6fTJSyjBKAcpBGDaeWeg1WoRGbkNJSUd07A3bfoKOTk57fs2dDqcP3/epLm7Rw8nLF68uMN7jzmOQ79+/eDl5cWOVG0DVlZWmDdvvkmnL4FAgG3bvjVp8eF5Hvv27WuVZSgiIgJDhgxljcAEevuo1KjQ1JvVHByshe3bKpGsqMBxheG+2kecvI2e7iXkODzo4gP7JuvZubweJ0symvFT7zxczSzxludABIvMDETnobpybM6L7ZT1/ObIV9chpd7wCMiJFrZwkJizDtpJXL58Gfv37+vwc8rLy7B3795WaWVNKSsra5Uz3oIFCxEQEMga7S4SHByMJ56Yb1KjLikpxt69P7QYEjYxMQH79v1gMs8ePZywcOGidltlWp7cARUV5Q2n8rX3Lz8/v83+J+2Febm3VTsnHtdrDDUWO04At3Zs3eJB+LEkDalNBOAEiSVG9fBo9j5vSzu8aNsTa+/w8tYD2FKehWluAW0Kj9vmjg4g1NYZa2XBWJ59HcX035VzFYDPy7PhZW6LJ9x6dcladrlGiXwjE4Yhtq7d7mnf9rr7e2h9tbW1iIzc1qqDSYjIpDa7Y8d2TJ48GSEhIW0uhylzOxFhxIgRXb7Hl9EyYrEYjzzyCH7++RiysjJbtILs3r0LERERGDBggMHvarUae/bsQVFRocl+9cQTT6BPnz5d861yAqxY8Qr0el2HnuPr64fffjvTJZOObhPoZdp6FKg7LwCDABxczCzuujk1X1WLPYoSg+v9Le1bfVb2nWQpa7C/qgAcGpvspzvIWlwLFnMCTHf1x9rqgkbRJG7yOpwty8Z8Wd8uNu1wmOTkhdWqGrxSnNKo9BVE+KgwCd4Wdhjp0PlepyX1ChQZrJ8T3Mys7+0Rjwjf5NyAo7DzYuALOQGe9Q2DuJPPqb969QqOHv3J4Azxpnh5eWPgwIE4cGAfWtqDXVtbi507d6J3795tOme8oCAfdXUKWFg0P1kOCuqNgIAAJlHvAXx9fTFv3jy8++6/W0ynUNRix47vEBQUBAuLxuNcVFQUDh48aFKYe3v7YPbsR7t0371QKOzwRFEg6L6JZhcJdA4v5dyAGdd5Fd1LZIadfSbAWnj3NLA6vQ4bc2OR3WTGZgbgIXt3CNvxvqfLshHbZLvbEJEEU1x8TdeJTQ88Y9UDXynKGq5pAewsy0SEqx96iLt2RigRCLBQGoQMVQ2+qCls9FuiXot3c6KwwcwS/padG0zB6Bo9ocsOPelEiY73aks69Ym9OQGepsGdOxkvK8WGDRtMCnOe57F8+XIMGzYcly5dQn5+y+cPHD16BFOnTsXo0aNbXZbS0lKIRC1/84GBgd2i/TBaI7wEeOihh/Dzzz8jKup6i2mPHTuGGTNmYNSo//aHuro67N69GzU11Sb3tS9duhRyuZxVeiNFq4vI0muRrFN32l+9TtPla8MtoeJ12J2fgA3VBYZailCM0T082mw7KFTXYUd5lsF9D9r2hIeRuO1NsRCIMMvFz3CSoFHiXHlOt9SLg8gMKzxDEWFuWN5f1XX4JCcaFdrOjX1dayTMKzgOTmLmkdxReJ7HkSNHceWK6UAeffr0xcSJk+Dj49OqEKB1dQps2vQVampa77hZV6cEZ2Ki7OHh2Satn9G1uLm5Y9GiRRCLW7ZE1dersG3bNigU/z2O+dKlizh27IjJvhQWNgSTJ0d0W1S8+16g/69AADJU1ViXcRUri5JhTDStdPGDczuOiv29PBfntapG05QAgRCzXP1bPTkYaN8Ts80ar5frAPxYkoG6Dq79tBZPCxu86dEffY2Ent1eU4xv8+I71UnO+EE4BP09HoTj70BOTg42bfrKpJlQr9fjqaeegouLMziOw4wZM+DhYTqi1p9/XsCxY8da//21ok27y+GI0XrGjh2HkSNNB5v5/fffce7cWQBAVdWtMwBMOU9yHLB8+VPsKNv7UaDzAIo0KmTXK1r9l1VfizhFOc5X5OHTzGuYm3QGaytyUGvEQjDD3AaP9AyAoI3OX1VaNXaUZRg0xmRrZwRZt/54RjuRGR4zYp7fVV+Nq910aAsHYJi9G/4h7Qf3JtqUGsDHZRk4UprZaSfS2TSz7FKkVbEvugPodDrs378fhYUFJtOOGzce48aNx+11czc3NyxfvtykZkVE+Pbbb02a529jbW1lMkpYfn4etFota8B7CDs7Oyxa9KTJbYQajRqRkZEoLS3F6dOncfbsGZP9Z8qUhzBixAhWyUbosgXpXgIRLDrRw9lGKGqXh3AdgBezrqKtxth6AHVEBpHbGmnHIjO84z0Yju1Yu71YVYCjTbZeuXIcHnX1b7Nn+IgeHphQlIyTTQTajyXpGNFDDjHX9fM2DsBUFx8kq6rwUWkmFHfUWwnxeCcvDr4Wtgi1delwXs05lZVq6u/tr43jsKdnENwknXeQjYDjIOoks2NycjK2bv26VWkXL17SaM8xx3GYPDkC33+/2+TRqTdvJuHAgR/xwgsvmJwAODk5Q6fTtWi+TU6+CY1Gw9bR7zHCw8MxderD2Lv3+xbTXblyGXv2fI9ffvnFZH+QSCRYsmQpbGxsWAV3hUAnMrayTXjPMxQDjIRIbb8pgYNlO7wFedw66rOzCROZ4VOvQejbjndU6nU4VGoYMGGUhR0G2bm2+XkuEgtMdZDiZElaYy29rhxP1pQitB3PbA8WAiGelwcjW1WL7YpS3Kkzxes1eCv7Or70D4dnB7fUuZlbw47jUN1I4+eQV19zj39uHAY7yuBzDx65Wl9fj61bv4ZSaXpnyvTpMzB0qGEgjx49euDZZ5/Ds88+Y2Jew+Hbb7di8uTJ8Pf3bzGtVCqFlZUVeL75iXViYgJSUlIwaNAgNqLfS8JFJMKCBQtw8uSvqKgob1GGfPLJxyaXV4h4LFiwEH379u22dxCLxR32cpdIJN0WpKjDAp3jjOvNPcUW8DL/35xFPW5hj1Weoehv69KuTXQxNSXYcodneoNA5ATYXZDUrmdW67V/6cl3bh/j8WNJGvrZukDUTR3KXmSGVV4DkJb6B8422bb4s6oGn+VE49++Q2HdgaNebSSWcOMEqCZ9IwvB77UlWKjXwkbIHKTayqVLl3DkyE8m092KCDbPYKvR7bFg7NhxGDduPE6f/q3F55SXl+O777bj7bf/0eLZ1dbW1vD19W9xLzrHCXDu3DmEhoayvej3GL1798YTTzyBL75Yb1IxNIVM5oE5c+Z0WzheIsLbb/8Dw4cP75gyKhB2m9MmCyzTBgaIzPCUkzcecQtAD3H74oVriceh0nSjv0XWVSCyrqJTy7y9uhCLlFXw7UatMNDSHv/2GIDF6ReR2sQj/bOqAnjlJ+IZWT9I2mkqlptbw0tsgZtqxR02IeB4fS1K1UrYWLKYzm1BoVDgq6++bDFy153aef/+oS0K/KVLl+G33061qJVwHIcdO77DlClTjWr7t3F2dkb//v1NBpfZtWsnHnroIbYf/R5DKBRi9uxHceTIT8jKyurQs5544gn4+3df+xIRpFLZ3yoCIfNybyUPmtvgcNB4LPUIbrcwB26Fed1eXdRt5c7l9ThSkt5pDmmtZZi9G95072PUj2JdSSpOdWBbnaVQhCFGHAdreT1Ol2d3+7v+3fn1119x5cplk+lcXFzxxBPzWtSoAWDgwIGYOXOWyefxPI9vv/3G4AzyRhqHSISRI0eZPNylrKwU33yzFXV1HQ9mFR8fh+zsbNYxOgkPDw8sWbKsQ7sR+vULxrRp05kF5n7X0C0BvO3iB3+L1mlt5eo6PFV00+B6oroOefW1kFm0fxlBT4QjJekope7dZrOlIhdz3YPQ08yq2/IUchxmu/ohS1WNf5VnGUwy3smNgZu5Nbza4SDGAZjg6IGvKnJQcofw5gB8VZqBSc7eXRr69n+JwsJCbN68uRWnoXGYO/cxBAUFmXymhYUF5s+fj6NHfzLpfX78+M945JFZmDRpUosTBF9fvxbDiQLA3r170LNnTzz33PMmJx3NER0djVdfXQWxWIznn38BEydONBnYhmFCaxQIEBERgUOHDuL69WttF1KiW2edy2QyVpn3u4YuBjDWQYZHXP1a9bdI3g9rHQ1jqOcQj49ybqCyA0FS8uoV2FmVj+7eNZuk1+BUaVarwvLwnRi+x1IownMewVhiZahNX9fV44PsKOS3MzxwiK0zhjbZf08AonRqHCpOY3vSW8mBAweQlJTQKi1rzpw5rdaQgoODMW/eApNroxzHYePGDSgvb95pSiaT4eGHp5l0LOJ5Hhs3bsTGjRtRU9M2B0mdToerV6/i7bffQnLyTcTHx2HlyhVYv/5zlJSUsI7SQZydnbFs2fJ23Tt06FBMmDCBnX7HNPS2I+EEWCbrhzO1pTjTZBvYr2oFduTH4wWvgW12XCMQfi5JQ3qTMK/2nADP2Uth2UkhbXkiHKkpwhVt4y1cm8rSMa2nH2xELTuUEBE685w0J7EFVnsNRGrKeZy/o0x6AD8qKyHKiQLa4QZoLRTjmZ6BOJd1DdVNpiAflaShv7UTwnvIOz3yv5Z4XKjIx0A7V9iIJH/rvp6eno6dO78zbRHhOCxevKRNGpJEIsHjjz+OI0d+QllZaYtpY2KicfToUcyfP99o5C+O4/DYY3Px88/HkJaW2uKzNBo11q//DElJiVi+/CmEhIS06JDE8zyqqqqwb98+fPnlRlRW/teHpa5OgfXrP8fVq1fx+utr0K9fPxaZrAOEh4cjImJqqyLB/dfaY4nFixfDwcGBVSAT6O2jp7k1Vkv74M+sa40iwykBbCjLxHB7KQbZ92zTM0s19dhZnm0QaW6JjQve9A2DWScF8CcCfPMTsbAgvtG2sQsaFc6X52KKq1+L9ws5rtM7hb+VA972CMXTmVeRfoeTnB7AHmVVu587zFGGCSVp2K+sbHQ9n3isybmBrebWCLRy6DShXqfXYnNuHD4uTcc8O3e87TMYtn9Toa7T6bBz5w7k5+ebHFz9/PwxderUNmtIgYGBWLhwIT755OMW7yUibNr0FcaNG9dsbG53dymWLFmKN99cY3ItVq/X45dfjuPcuXOYOHEiJk16EL17B8HVtScEAgGICDU1NcjNzcWff17A/v37kZubY/S5PM/jwoU/MG/eE1iz5g1Mnz4dlpaWbJBsB7a2tliwYAHOnTuLujpFq+6ZNGkShg+/O0FkOI5DcXERQsOCJAAAIABJREFU0tPTO+2Zjo6OXTo5YQK9GcY4eeHVqkK8W9U42loqr8enuTHYaOUAhzbEDj9dloUYXVMvYg6PuPrDojOP/OSAsc5e8ClORnITa8Dm4hSMdfKEZYvburrGrDXaUYZVymq8XpSEmjtiF3TEMG4rkuBptyCcybiIiibxEC5qVXg+9QI+8QlDSDu3F95JmUaFT7Ki8FFVPgDCF1V50GcQ3vEJ+1tq6lFRUdi1a6dJIc1xHJ555lk4O7cvpsTMmY/g4MGDyMhoeVDMz8/DgQP78eKLLxoNO8txHKZMmYITJ34xGU3sNiqVEocPH8JPPx2GSCSCubk5HB0doVSqUF1dDb1e1wrfgVtUV1dhzZrVuHEjCq+/vgY9evRgg2Q7GDhwIB599FF8++03Jvuera0dnnxy8V2bQHEch7fffqvTrDJEwLp1n2LGjBldVmZmP2oGM4EQS2T9MExkZiAMvldVYV9BEvhWiqNqnQbfl2agrkn6+Zb27QpMYwpniSWecjDUdH6vr8W1qqK7Up9iToD57kF42l6KztqRyQEY7SjFuy4BBi3BA/hNU4elaX/idFk26tsZS17D3zKxP3vzLD6qymuYgqgBbKjKx/sZV6DQ/73CjtbV1WH79kjU15uOrDd06HA88MAD7V6/lMvlmD9/fqvu3759O5KSkpr93d7eHmvWvIGgoN5tHEgJWq0WtbW1yM7ORmlpCTQadauF+Z3PsbOzYxHpOjKumplhzpy5kEpNL988/vjj6Nev310tr16vh1ar7aQ/TZeXlwn0FvCytMNb0r6wbCLSOQCfl6Yjprp1zjIXK/NxSmPo/DXXxQ82os4POCDkOEzr6Q+XJjPLKgB7SlKh4fV3pT6thCI85xGCKZ14nKqIE2CerA9W2bkZ/f26To0HMi7jzZQ/EFdT2upDYlS8HimKCnyYcRnh6Rew30gUOi2AWr0WujbsWrgX3HouXryIQ4cOtkKA8XjmmWcahXhtDw899DD69DEd3au8vAzffvst1OrmHU979eqFd95ZC0fH7tWQiQhTpz6E55573mR8ckbLBAYG4rHHHmsxjUwmw5w5c9gOg7aOh6wKWma8szeWV+bh/2qK//txA0jkdfg8NxbrrUa3uI5ap9dhb3EalE22V0VIrDDEwb3Lyi23sMXTtm5Y22TJ4KiiDE8ryhHcCTHV21UuM2v8y3MgclP/wDVd5xyrai0UY4XXQBSmXsCuJuvpt1vs05oi7FKUYpalA8LtpRhg6wJzkQSWQjEshUKoeR4qvQ4KrQpRNaU4W5mHSGUl1H8Ja2O2mNfspVjjPRj2RhwNtc0I+cNlWXCuLu6SunU2s8TEHh4tpqmsrMTWrVtb5a0+bdoMDBkypMPlcnFxwZIlS7Fq1QqTWvGxY0cxffqMZk/q4jgOYWFh+PjjT/DWW2+26iCZjsLzPGbOfARvv/02c87qDIVDKMSMGTNx/PhxJCYmGKlvPZYsWQovL29WWUygd7KJSCDEsx79cT7pDK7rG5tMtisrMKrwJhbK+jV7oEpibSl+UFU1ES/AbCdv9BB3nelOzAkw1cXXQKDnEuHHolT064R15fbS16YH3pKH4Jns6yjsJGuBm5kV1vmHQ559Ax9WGT/Jq5jXY6OiDBsVZbAVCOEjEMFdIIQ9J0Qd8SgjPa7rNKhvhcb9vpMPnvfo36yFxeiBOMTjleKULqvX52x7tijQeZ7H8ePH8ccf502uCwoEHBYsWGg0xGt7mDRpEvbsGYzLl1s+Z12pVCIychsGDBjQrCYsEAgwfvx4ODk54R//eBsxMdFd9x2JxViwYCFeeOFFODo6sgGxsyb2cjkWLVqEN95YY3BcamjoQEyd+hALItMOmMm9Ffha2uNVtyDYGjG9v1ucglSF8T20WuKxvzgNyiYCYoTIDOOcPLq83H1snLHU0nAQ+qGmECmKirvY6ThEOHniTRd/dKa7i6uZJV73GYwNroFw4wQtTlhqeD2idWr8rFFit7oWhzV1uKCtNynMewnF2O8xAC97hnbJcklHMDVBKygowMaNG0wKcyLC44/PR0hISKeVzdraGs8993yrYlqfOnUSp06dNDHhEKB///744osvMGPGzC4xzbq5ueOTTz7FqlWvMmHe2X2V4zBx4iQMHhxm0PeWLVsGV1dXVklMoHfdQPlwTz8ssnGBsImmncnr8Un2Daj0OoP7UhQV2FFraF59xEHeLZHMLIUizHU1PM0qidfjRFnmXa1TMSfAPPcgLLbr3GUHO5EET3uEYL/fCCy0doJrJwWjkHECvGjnhoO9xmBmT39YCP9exi29Xo+DB39Ebq7pkLv29g54/PHHOv0QjGHDhv11hjpMTii2bt2K4uJik0LBy8sb7733PjZt2oIRI8I75RAMe3sHLFiwELt27cb06dPZmnkX4ejoiMWLl9zhZEiYNOlBjB49hlUOE+jNDA6d9BwLgQjPe4Sgt5EtX7uUFThUlNIoxhoPwvHSTAOTcm+BCBEu3bc2NNDBDbPMbQ2u76/IRV694q62jZ1IglWe/THF3KZT20zIcRju4I5NvcZgl/cQPGZhD6927vPvLRDhFTs3HPAPx8cB4ehl5Qjub9jX09LSsGXLllvHHbfwx/N6LFiwsM2e5K3BzMwMy5cvh0QiMVmOqKhrOHLkp1adwmVtbY0JEyZg06bN+Oyz9Rg9egxsbe1aHTuciCAUChEY2AvPP/8Cdu/ejbff/gf8/Py6NDrZrfrmm/2jLoh2SIQW8+xIvPX2EB4ejgkTJt5SQCytsGDBQtjZdd/hSqbqorP/upoOqxm2IjMscZA3GkwIBEdx92/tcBSbY4W91EgZO2efsK+VPd6Th+BsVaHBbzGqakzUqhvWxau1GlQQb1AeuZk1/Cy7z7HGXmSGBa4BkFcXNhJEBCBNWQWZuXXjwVEkwQJHeaMDTngQLLtor7WnuQ0+8h6CvnesLXMAHDqh/5gJhBjv5IlwRxmSFRW4VF2IazUlSNHUIUWvRSHPAw2BeDmAE6CPQIheQglk5jYYZ++OXjbO8LO0g6CNA7uVxByrHeXoTr92XwvbZgVHcXExli9/yrTlRCzCjBkzu2z9sn//UHzwwUcoKjK9fVIgEKKurg7W1tamrWgcBzs7Ozz00EOYOHEi0tLSEBcXhytXrqCgIB95eXmoqalGfX09hEIhrKys4eTkDC8vT3h7e2PkyFHw8/ODs7Nzt4QYFYlEeOONNw3Wjxu/vwBOTk6dluft6H3Tpk1r2Rolk3VbRDwrKyssXrwEp0//hhkzZiIsLKzbvpeIiAgMGzasW2VUr169uvT5HBELes24f9AToUSrQq1WDZ1OC9xeM+cE4AQCmIskcJJYsDPV/4dQKBSorKyERqOBXq8Hx3EQiUSwtLSEk5MTc766y+h0Oqxfvx4TJ05A3779WIUwgc5gMBiMvyu1tbWwsrJisfKZQGcwGAwGg8GmQwwGg8FgMIHOYDAYDAaDCXQGg8FgMBhMoDMYDAaDwWACncFgMBgMJtAZDAaDwWAwgc5gMBgMBoMJdAaDwWAwGEygMxgMBoPBBDqDwWAwGAwm0BkMBoPBYDCBzmAwGAwGwxARqwLG/QARQaVSged5mJmZQSxmx6MyGIz2odfrUV9fDwAwNze/Z47gZRo6475AoVDgrbfewpNPLsKNGzdYhTAYjHbB8zyOH/8ZTz/9FNat+6RBsDOBzmB0EzU1Nfj552O4cSMK7u5urELu0DTy8/PATlFmMFpHQkIC/vnPf0Kr1WHRoidhZWXFBDqD0Z2kp6ehvLwUwcEhsLOzZxUCIDn5Jj788ANs3rwZPM+zCmEwTFBYWIj3338PcrkcH3zwATw8PO6p8jGBzrgvyM7OgZmZOQYOHAQLCwtWIQAOHTqEr776EsHBwRAI2FDAYLREfX09Nm3ahIqKCnz00Ufw9va+58rInOIY//Oo1WrEx8eBiODv7w+RqPXdnogamaNNCb4707dXSLYlzzvTcRzX6F6O48BxnNH0CoUCN2/ehFgshlQqa/Tb7XuM/Z+IjD73Tg3f2O/tLa+xe1tTnq56bnO09f1bWz9tKWNb3rm179KZfa8tfd1UPbVU562pY2PlNHWfXq/HrFmzsHjxYsjl8ja9W3dNmJlAZ9wHAr0eUVFRUKvr4ePj0+pBLTs7G9euXcOVK5dRUVEBBwdHjB49GsOGDYOTk5NB+sTEBJw+fQapqSkQiyUYP34cRo8eA2tr61blqdfrkZ6ejtjY2L/yrISjowPGjBmLsLAwgzwBYNu2bSgpKcaMGTNRX3/rPePj4/6yRgzE2LFj4ejo2JD+woULOH/+HOrqlLh27Rp4nsePPx7AmTOnAQDTpk1Dnz59UVZWhm+//QZCoRDLly9HYmISzpw5jczMTDz77HMICQkBEaGkpARxcXE4f/48iouLYW5uhpCQEISHj4S/v7/B4BgVdR3nzp3HgAGh8PHxxcmTJxEdHQ2VSgl/f3+MHj0GgwcPNvAa1ul02LRpE+rqFJg9+1FoNBqcPXsGsbGxePDBB/Hww9MAAEqlEjdu3MCFCxeQnp4OgYBD7959MGrUKPTp08dgMpebm4vvvtsOHx9fPPDAA7h27RpiYmKQn58HPz8/hIeHIySkv9FJIM/zKCwsxLVr1xAVdR25ubmwsrLGyJEjER4eDjc3t0bvX1paiu+++w48r8eyZcthb2+49BMfH4ejR4/C3d0dCxYsBMdxqK6uxtdfbwERYdmyZUhPT8eZM2eQlpaGxYsXY/DgMOTkZOP48V8QHx8HgEN4eDjGjx8PZ2fnVk8i8/Pzcf36NVy9eg1FRUWwtrbCyJGjEBYWBplMZjDBOH78Z0RHR2PKlCmwsbHFpUuXEB8fB41Gg5CQ/hgzZozBfXdOsuPi4nD16lUkJyejqqoK7u5ueOCBCRg8eDB++ukwSkpKMXXqVPj7+zfKNy8vr6GcxcVFsLa2xogR4Rg9ejREIhG+++47mJubY8GCBbC0tGy4T6FQIDo6GteuXUVmZiYUCgV8fHwxadIk9OnTG9u2RYKIx9y5jzX61nQ6HZKTkxEVFYUbN26gsrIC7u5SjB49GuHh4Q153Eaj0SAq6jr++OMPJCenQCp1x/jxD2DYsGFtUibaqw0wGP/TpKSkkFTqRoMHD6KSkhKT6Wtra2nz5s00YEAoeXjIKCDAn0JDQ8jDQ0YeHjKaNGkixcREN6TneZ6OHz9OgYEB5OPjTWFhgykgwI+8vDzotddeo6qqKpN5VldX0+bNm6hfv74kk7lTYGAAhYQEk6ennDw95TR16lSKj49vdE9lZSVNnTqFAgL86MknF1FAgD/5+nqTn58vSaVu5OEho2nTHqasrKyGe/bu3Uu+vt7k5eVJcrmUPD3l5OfnQ35+PhQWNohSUlKIiOj69etkZ2dBU6dG0CuvvEy+vt7k5uZKvXsHUWpqCmm1Wjp16hRNmjSRPDxk5O3tSaGh/cnHx5tkMnfq3TuIjhz5ifR6fUPeOp2O1q1bRzKZO82YMZ3CwgaRXC6lwMAAksulJJO5k5+fL3300UekUCgavWtWVhYNHTqEQkP707/+9U8KCupF7u6u5OhoS6dOnSSe5ykhIYFmz55F3t5e5OXlQSEhwdSrVwDJZO4UEOBPn376KdXX1zd67qFDh8jV1Ynmzp1LU6ZEkIeHjAID/cnDQ0YymTv5+/vS5s2bSaPRNLpPpVLRd99tp8GDB5JcLiUfHy8KDu5L3t636nX06FF06dIl4nm+4Z7Y2Fjy9/elmTNnGDzvNl999SXJZO60cePGhnsTExPJxkZCEydOoFWrVpKfnw+5ublSYKA/xcXF0qVLl2jQoIHk6Smn/v1DqG/fPuThIaO5c+dQbm6uyb6nUqlo//79NHJkOMnlUvL19aaQkGDy8vIguVxKI0YMp7Nnz9Adr0I8z9Py5cvI01NOS5YspuDgfuTl5UEBAX4kk7mTXC6l4cOH0dWrVxvlxfM8ZWdn0TPPPEN+fj4klbqRp6ec/P1v9VkvLw+aO3cOjRgxnAIDAyg7O7tROX/4YS+Fh48guVxKHh5SCgrqRV5eHiSTudPYsWNo7dq15OrqTMuXL6O6ujoiItLr9XT9+jWaNu1h8vLyJKnUjXx8vBry9/f3pWXLlpK3txfNmDGdysvLG/IsLS2ld9/9N/Xu3euv79KfgoP7NXw7Tz75ZKPvS6vV0ubNm8nPz4f8/f0oLGwweXl5kI+PF61bt460Wm2XjnVMoDP+5zlx4gS5u/ekpUuXGAiKptTV1dHatWtJLpdSRMRk+u677yguLo6Sk5PpwoULtHz5cpJK3WjatGlUXV1NREQVFRU0YEAo9evXh44fP07p6el05cqVv4TWYDp79qxJYf7GG2+QTOZO06Y9TPv376f4+Hi6efMm/f777zR//nySy6U0f/78hjyJiJKSkqhv3z4kl0tp/PhxFBkZSbGxMRQbG0s//LCXhg8fTnK5lNaseZ10Oh0RERUUFFBcXBz961//JKnUjd566y2Kjo6m2NhYSkhIaBB427dHkru7K8lk7jRp0gT6+ustdOnSJfr999+pqqqKDh48SAEB/jRo0EBat24d3bgRRSkpKXTjxg368MMPycvLgwIDAygmJqahvBqNhubMeZTkcin5+/vRq6+uovPnz1N8fBxFRUXRhx9+QIGBAeTu3pP27t3bqI4uX75M3t5eJJdLaejQIfTRRx/RH3/8QefPn6eysjKKioqioUOHkJ+fD61cuZIuXvyTbt68SfHx8bR161YaNGggeXl50KFDBxsJ2c8//4xkMnfy8JDRiy++QOfOnaP4+Di6evUqrVmzhmQyd/L0lNOVK5cb7qmvr6fPP/+M5HIpjRo1krZs2ULR0dGUlJRE165doxUrVpCnpwc98MD4RgJ1z5495O7ek955551GE507hd0rr7xM3t6edP78uYbr+/fvJze3W20xbtxY+vLLL+nixYv0+++/U35+Ps2dO4fkcint2rWTkpOTKTExkZYvX0aBgf4UGRnZYt+rr6+nDRs2kIeHjEaODKetW7dSTEw03bx5k6KiomjNmtcb8s3JyWm4r6qqiiZOnEByuZQGDhxAX3zxBV2/fp3i4uLoxIkTNHPmDJLLpTRz5kyqrKxsuC8jI4MiIiaTVOpGDz44iXbu3EFXr16luLhYOnfuHL344ovk4SEjuVxKY8eOaeiPKpWKPv10HXl4yCgoKJA++OB9unTpEiUkJFBUVBT93/99SgMG9G+YGH711ZcN7Xzp0kUKDu5HMpk7zZ8/nw4ePEg3btyg2NhYOnr0KD3++OMkl0tJLpfS6tWvNdxXUlJCS5YsJrlcSnPmPEpHjhyhuLg4unnzJp09e5Zmz55FMpk7rVy5oqGcSUlJJJO508SJE+j8+XOUnp5OJ0/+SoMHD6LRo0dRXFwcE+gMRnvR6/W0adMmkkrd6LPPPjOZft++fSSVutHcuXMazbxvU15eTk888QTJ5TLat+8H4nmeoqOjycNDRkuWLG40YUhMTKSUlBSjg/edg/jWrV+TXC6lBQsWNNJI7tQSpk6dQq6uznT48OGG67/+emuiMnPmDKMDxZEjP5G/vy8NGjSQioqK7tCUtfTPf/6DpFI3OnbsmMF9Op2O1q5dSzKZOz399NONBvJbmmYM9enTm8LCBtOZM6cbCcjbgvv9998jqdSNVq9e3TDYFRcXN2iQBw4cIJVKZZDv999/Tx4eMho/fhwVFBQ0/BYZuY1kMnd68MFJFB0d3ahOi4qKaPr0aeTj4027d+8itVpt8E6HDx8iLy8PmjDhgQaLiUKhoMWLnyR3d1fauHGjwWSvtraWli9fRjKZO23Zspl4niee5+nEiRPk4+NNERGTKS4u1iAvhUJBS5cuJXf3nrR58+aG6++88w7J5VI6evSo0b5QUlJCERGTqU+foAZLiV6vp//7v09JJnOnJUsWU0ZGRqP6rq6uosBAf+rXr2+jNs7JyaHo6OhmLQG3+95vv51qsDrduHHD6Lu89tqrJJW60fr16xuux8fHU9++fWjo0CF04cIFgz4QFxdHAwcOoMBAf4qKiiIiIqVSSS+//BLJZO60evVrlJeXZ5CfWq2mf/97LUmlbvTmm2+QVqslnufp119/JblcSmFhg+nkyZMGbazX6+nChQvUr18fcnbuQadOnSIiosLCwgYr0rp164xayyoqKmju3Lnk7t6Tdu3a1fC8zz//jKRSN3r55ZeorKzM4L60tDQaM2Y0+fh40aVLF4mI6JdffiGp1I0++OD9RmmjoqIoOzu7xbGgM2CurYz/aTQaDa5duwatVgMfn5a9UsvLyxEZuQ1isRivvLICnp6eBmkcHR0xZsxo6PU6XL58BTzPw83NDebm5rh+/ToSExMbnHWCgoLg7+/fokNMSUkJvvnmGzg5OWPVqlVGt8E4OTnh0UfnQCKRICYmuuF6TEwMBAIBHn/8CfTt29fgvgEDBkIu94BSqURZWWnD9ZqaWsTExAAgo/nV1NTg2rWr4Hkezz//fCMHII1Gg71796KiohzPP/88xowZa7BGKhaLMXPmI6isLMTJkyegVqsBAJmZGaipqUZYWBgiIiJgbm7e6D6hUIjJkyfDy8sbMTE3EBsb2/BbQkICRCIRXnzxJYSEhDSq099+O4XLly/h0UcfxSOPzIJEIjF4p2HDhsPfPxD5+fnIyclpWG+/dOkSevRwwpw5cwz2E1tbW2P06NHgeR75+QXQ6XRQq9XYuvVrCAQCrFy5En379jPIy8rKCrNnz4JIJEJ8fDx0Oh1qamqQnJwMsVjSbByEysoKZGVlQSaTQyaTNZTx4sWL0Om0ePHFl+Dt7d2ovgUCIfz8/FFSUoQLFy5Ar9cDAORyOUJCQlqMiKjRaPDNN9+A4zi88sor6N+/v9F3mThx4l/r+/FQKusAAEVFRaiursIDD9xaG27aB273faVS2RB4JS4uDt9/vwseHp545plnIZVKDfKTSCSwt3cAAISGhkIkEkGpVGLjxg3geR4vvPAixo0bZ9DGAoEAffv2hYODI4RCAXr16gUA+OOP35GUlIixY8dh2bJlsLOzM8jT1tYWYrHoL3+L3gCArKwsREZGwsnJGa+88gp69OhhcJ+vry9GjBgBrVaLxMREEBEcHBzA8zx+//13pKenN6QNDQ2Fh4dHlzvHMac4xv809fX1iI6+AUtLKwQG9moxbVpaGi5e/AO2tvbYt28fjh49YiQVh5SUZAgEAiQl3RLePXr0wBtvvIk1a1bj2WefwcqVKxERMQW2trYmy5eSkoKiokJYWVljx47vDITcbW4PDpWVldDptOB5QlpaOiQSCWQyqdF7BAIOAoEAYrEYFhaWjQR2XFwsvL19jXrr1tTUIDY2Br169WoQLLdRKGpx7NgxCAQCnDt3HqmpaQAMg9IoFHXo0UOK/Pw8qFQq2NraIj+/ABqNBoGBgc2+p6WlJYYPH4HU1BQUFRUBAKqqqpCamgorKyuDSZZWq8Xly5chEomQkZGJd9/9d7NOjqWlJairq0NtbS0AIDs7G0VFBZg5cxYsLMybqUMhAIKdnR2EQiGSk5ORmJgIgHDo0CGcPXvW6H35+fkgArKzs1BdXYW6OiVSUpLh4OBgdKJ4u40rK8sxZcqUBoGlUCgQExONwMAgowLQysoKzz33PJYvX4o1a15HYWEh5syZY9SBsinZ2dmIiooCxwlw7NjPuHDhgtF0hYVF4DgOCQnxqKtTwtLSCteuXf1r0jjAqNPb7X4nkUgaHMESExMgEokxe/ajzXqJ19fXIzk5GRzHoWdPt7/uS0RsbCyGDBmKyZMnNysUq6urkZSUgCFDhjU4qp05cwYcx2HWrNmwsbExel9tbS3S0tIgk3k0OCpevXoVhYX5cHR0wqZNmyESCY2OBdeuXWuYrBARgoODsXjxEkRGbsOzzz6Dl156GePHj4eZmRnzcmcwOkpWVhZKSorRu3cfODg4tJg2MzMTZmYW4HkeBw7sazGtWCyBg4MjOI6DUCjEo4/OgUgkxtq1/8Krr67CyZMn8eqrryEwMLDFrTfZ2dl/aXDV2L+/5TxFIjGEQhE4ToCysmKkpqbA2toGMpnxwbGmphbFxUVwcXGFi4tLo0lETU01pk59yOhAk5KSAqWyDqGhAwwEb1lZOYqKCiAWS3D69KlWlFcIiUQCnudx+fIl8DyPgQMHmahbMQBqGETLysqQnZ0NV9eeBoKgqqqqYbJz5colXL16uYUnc5BIxBAIuIb2Njc3R0hI/0YTnjs9qktKigFwkEqlEAgEqK6uhkJRC57nm5nw3fn+IlhaWkIkEiMvLxd5eTl48MEIWFsbFyxJSTchFIowaNDgBqGVnp6G6upqTJr0oIE3NXBri9WECROwefPXWLv2Hbz//rs4ffo3vPzyywgPH9li3ysqKkJ9veqOdyET/d0BQqEQGo0GyckpsLCwaHZyUlFRgaKiYtjZ2cPBwQFarRZZWdkg4iGTyZoVyrW1tUhMTICFhQV8fX0bnqXTaREQEGBUU75NamoKRCIxBg0aBFtbW9TV1aGwsBDm5uaQSt2bvS8nJwdVVZUYNGgw3NxuTSIKCvIhEolRV6fAnj27Tfbz2+UyNzfHypWrYG/vgA0b1uOpp5ZizpzHsGLFSri7uzOBzmB0hIKCAhAR+vbta3SbUFNtj+M4PPLIbKxevdqo6bbpYHp7e5WFhQUee+wx9O/fH5s3b8Lhw4eRkZGBr7/+Gn5+/kbvJyKo1bfMkXPnPo7XX3/d5PsIhUIIhUKUl5cjIyMdAwcOanZrUmZmJioqyjF27LhGwXSysrIgFkswYMAAo5pydnY2RCIxgoODDQS+Wq0Gx3Hw8/PH119/DUfHHibLbGdnB51Oh5iYGNjbO7Q4sOl0OkRH34BOp4OX160lkry8PJSWFhvdIqTT6aBQKCASibB79x7RMj2ZAAAgAElEQVQEBgaaLI+lpeVfZtIE6PV6eHp6GhV8t7bARUOjUTcsTRAReJ7HkCFD8dVXm0weysFxHGxsbJCamgqOEyAkpL/Re9RqNdLT0yEUiuDhIW8oT25uLgQCAYKCgpoNiCQSiTB58mQEBwdj584d+Prrr/HKK69g/fr1GD58RLNl43k9iAijRo3BJ5980qr+bmNjg8LCQqSnp8HOzh5ubsbbsqSkBEVFhfD29oZUKgXHcTAzk0AgEECpVDabR0VFBWJibmDSpMkN5vHb6VuqayJCTk4OOI6DTCaDUCiEWCyGWCyGVquFRqNp9t68vDzU1dXB09Ozob/rdDoAwGuvrcbcuY+Z3FMvFAobJikODg54+eWXMXJkOD799FP88MNeZGVlYdOmza2ynDCBzmAYQa/XIyYmBjyvh6+vr8kT1pycekCn0+LmzSRYWlo2a6IzZs4VCAQQCATo06cPPvjgQ7i5uePLLzdg586d+Mc//mlUI+E4Dl5et9ZECwryYWVlZXJQvU1iYiLU6noMGDCw2YEuMTEBHCdopPHV19cjISEBOp3WqHalUqkQExMNrVYDDw/D393d3WFuboEbN66CCCatHv8dNHNRUlICb29v9OzZs9lB+fz584iLi8WQIcMQEBAAAEhIiAeARu9x52TB398fmZkZqKysbHV5FAoFrl+/DqFQ2OwkQKVSITo6Cu7u0ob4BRYWFjA3t0BVVRV0Ol2rB+jy8goIhUK4uroaba+KinLEx8fBwsK8YQKo0Whw48attvD29mm2790OjiKTyfDqq6/By8sbb7zxOj7//HMMHhzWbL93dHSERCJBamoKVCoVXF1dW/ku5cjPz0NY2JBmJ5O3td6goAiYmZlBIBDAyckZt5asUqBWq41ah65fvw6JRIJRo0Y1TDatrKz++kYKoFQqjVoqNBoNrl+/jvp6JYKCggDcWo93de0JrVaLmJhYhIUNMRDMer0eFy/+CZ7nERIS0nDd1tYORDxSU9NgZWXVapO5Xq+HUCiESCRCWNgQfPnlV1izZg1OnDiOkyd/xWOPPd6lYx5zimP8Twv0qKjr0Ot5BAX1Npk+NHQA/P0DER8fh2PHjkGr1RrVAhQKRcP/4+Li8OWXG1FSUtKQzsrKChERERCLxUhISGjx4JOAgAC4urri/PlzOHHiF4OY6jzPIyMjw+BEp4yMW9pcSEiIUQGh0WiQnp4OkUgEX1+fhoFMrVYjLS0VSmV1wxplU00xKioKjo494OfnZ/C7lZUVpk+fCWtrO2zfHom6ujqjA35hYWET824xqqqqoFarUVtba1AnPM8jOTkZ//nPR9Dr9Zg79zE4OztDp9MhLS0NIpEYvr6+BgOypaUlBg0aDL1ej02bvmpYd2/6Tv/f3nlHx1Vdi/u700fSqGtmNCpWteUqG4MLmGLAlICBAAmmOLz3CxB4TkKABMgjgVASQhJqEpKQAAYC5NEMxhhsggFj44JxxUWWbFnF6l1TNeX8/pA8nhmNpJFkmZLzrWXW4mpuOefuu/c5++y9T2VlZdg929ra+OKLnUyePDWs8E4ohw5VcvhwLdOnzwgakaKiIoqKiigr28fy5cuDM7lIV3ZbW1vYseTkZAIBP9u3b+83W/T5fGzYsJEDB8qZPHlKsBCR1+tl69bPSU5OCSuuckT2amtrWbp0aVjwlVqtZt68U8jMtNHQ0NjvOUIpLh7PxImTqK2t4a233ooq7w0NDTQ3N/cbKLpcLkpLpw/oOj8S0Dhz5szgOzvttNNIT8/gueeeZfny5djtdrxeL16vF7vdzooVK3j00UdQFBVW69GiPIWFhZhMibz//mo2bdrYT3b8fj979uzhk08+ITc3n3Hj8oJ/u+SSSzAa43j66adZu3Ytbrc7OGNvbW3l6aef5rXXXiM+PoHi4vHB8+bOnYtWq2P58rf4/PPPo8prZWVl8LvsHRhs4E9/+mPQo6AoCmlpaVxxxRUEAoHgOvtYov7Vr371K6n6Jd9EmpubeeKJxxGi16DX19ezf//+fv8qKyuxWq2kpKRgMBh4//3VrF+/Ho1Gg9VqRQhBe3s7q1at4qc/vZWGhkbmzJmDoij85S9/6fuIXZSUlKAoCnZ7NytXvsvatR9z8cWXMG/evAFddiaTCY1Gy4cfrmHdunXExcWTkpIMKLS2trJixdvcdtutOBxOZs6ciUajoauri6VLn6WmppobbrghqmFubm7iqaeewu128z//syTovuzp6WHZsmW0tbWTk5NLTk4OXq8XlUqFRqOhoqKcJ554jFmzZnP55d/p55LXaDRkZGTw7rsr2bRpIx0dHVgsFnQ6HXa7nc8++4z777+fd99dybx584JejhUr3mbt2o9pbW1h48aNpKSkBF3xTU1NrFy5kjvu+BlVVYdYtOhKrr/+BvR6PS0tLfzjH3/H4XCyZMmSqFHKNpuNLVs+Z/v2bZSVlWGxWDGZTLjdbsrLy/nLX/7Cvffew+zZs4Pu/m3btvHqq69y1llnc/7534pawWvDho2sXr2KSy+9jNNOO63PbawnNTWFlStXsnHjRnw+LxaLBZVKRUdHO2vXfsIdd9zOvn1lzJ07Nziz8/v9vPnmm+zZs4eMjAxsNhter5eamhpeeulFHnjgPoQQLFp0FXPnzkWlUlFVVcUTTzzOpEmTueKKRf1mpsuXL+fuu39BRUUFU6dORa/X43K5WLNmDStXvsO0adP47nevGNCDo9FoSE1NY+XKd9i0aSM+n5+0tDQ0Gg12u51169bxs5/9lN27dzN79uzg/V9//XV27tzBdddd32+gcUTGXnzxn9TUVHPdddcHg/nS0tKIi4sLDl7Xrv2YgwcrWbv2Yx555BGeeeYfOBwOfD4fixcvJi8vL+iFAVi/fh2bNm0mOTmF1NRU/H4/9fX1LFu2jDvvvJ329nZmzpzJpZdeGpTbnJwcGhsbWL/+E95+ezmbN29m7959rF69igcffJAVK5bj9XpJTk7myiuvDK6FJycn43K52bRpAx999BFJSckkJycjhKClpYVXX32FW265GZMpkcmTJ+P1evnFL+7iX/96ORi8KYSgra2NpUuXsm/fXhYvXhw1K+KYIjOVJd9UNm3aKAoK8oPFJrKyMqP+u+qqq4I5yE6nUzzyyCMiJydLZGVlivT0ZFFcXCiyszOFzWYRJSXjxQMP3C+6u7uEEEJUVlaKSy65WNhsVlFQkCcWLrxQzJx5gsjMtIhFi64Iy6UeCLvdLv7whz8IiyVdZGVlitTURDF58kRhs1mEzWYVEyaMF48++kiwqExNTY2YMWO6OPHEE8KKdoSye/dukZeXKy66aGFYdbSenh7xxz8+IdLTk0VWVqZITo4XBQV5Yt++vUIIIVasWCFsNqt44IEHgsVoouWpr169Wpx44kyRlZUpzOY0UVRUIAoK8kRmpllYrRliyZIl4sCBA8F85yVL/kfk548T119/XV+VN6swm9PE1KmTRVaWta+dxeKhh34rWluP5vyWlZWJoqKCfu2I5LPPPhPnnLNA2GxWYbWaxbhxOWLSpBJhtWYIq9UsLrpoodi8eXMwl3zp0qV9eeJ/jXo9r9crHnjgfmGxZIg33ni939+WLl0qiot7q6KlpSWFvC+LyMnJErfffrtoa2sLy69+8MEHgzKXmWkREydOEOnpyeKUU04Wp512qsjOtonly5cHz1mz5oN+hYEi86d/8IMbhMWSIQoLC8S5554jzj77LJGdnSlOO+3UqHnl/d+lVzz//POipGSCyM7OFBkZKaKwME+MG5ctMjMtIjc3W/zv//5cNDU1BgvKLFq0SBQW5ocVDQrl8OHDYv78M8QJJ8zoJ/9ut1u8/PLL4sILLxAmk0YkJRlFamqiuOCCb4lnnnlaXHHFFcJqNQfzyENrMdx0043CbE4TWVmZwmrNEMXFhcJqzRCFhfli/vwzRHa2Tdx33339nqe9vV089tijYs6cWcJgQCQm6oXVmiEWL75GPPvss2L27FmitHSq2Lt3T7/z7rrrLmGzWfp0QUrfPc3CZrOKqVOniL///amgXO7atUvMn3+GsNksYtq0KeLiiy8SU6dOFhZLurj55h+HFYUaKxQh5EbIkm8m69Z9wqpVq4b8XXHxeL73ve+FzTB27drJO++sZNeuXTgcdtLTM5gxYwbz589n0qRJYWvdjY0NLFv2Jp99tpnGxkZyc3OZOnUql112GWZzbOuSHo+HTZs28emn69m5cyddXV1YLFamTJnCggULKCkpCc4i9+3bxz//+QJms5kbb7wp6rr7+vXreffdlRQXF3PNNYvDZmkOh4M1a9awd+9euru7MRj0/PSnP0Or1bJixdts3ryZ008/gwULFgwaN1BeXs4HH3zA1q2fU1dXh8lkYtKkyZx88snMnTs36Dru6OjgyisX0djYwEsv/Qu3283q1b3uU4/Hg9lsYcqUyZx++hmUlpaGzZY3b97E8uXLo7Yjmqv7/fffZ8uWLRw4UIFOp6O4uJhZs2Zz6qmnBiP9fT4fzz23lMrKSi666GJmzZrV71put5snn/wzbW1t/Nd//Xe/5Qe/38+uXbv6atFvo7m5GYvFQmlpKXPnnsyMGTP6zagdDgerV6/mo48+orx8P3l5+UyZMpkFC85h3brevOVrr72W4uLxCCFYvXoVn3yyjtmzZ7Nw4cKobW5vb+f999/nk0/WUlVVRWpqKtOnT2fhwoUUFhbFHAPS25bVbNu2nfb2NjIyzEyePIl5805lxowZwYC8xsZGnnqqd7vdW265NWpqZnV1Nf/4x99JTEziJz/5SVTvR0tLC21tbXR0dJCcnExqagpqtYZFi65g69YtvPvuKk488aSwczo7O1mz5gM+/PDDvowUPVOmTOGcc86ltbWVjz/+iPPOO5+zzz47anzGkaUQt9tNUlISGRkZNDc3s2jRFWg0Gv71r38FAzFD4yjWrl3L2rUfU1ZWht3eTVFRMVOmTOWMM86gqKgo2D4hBFVVVbz99tts3LiBjo4OiouL++rqnx1zfMdokAZd8o0lEPATCAwt3qHR6pFrmw6Hg0AggEajISEhYdAdnBwOB16vF71ej8FgGFERiUAggN1ux+/3o9VqgwFBkb85Egw1kIGL5TdH2njE/XrEUAkhgkF+seBwOOjp6UGtVhEXF99Pge/evZvvfvc75Obm8vrrbxAXF4cQgq6uLgKBwIDtHE47Io2xy+VCURTi4uKiDniOtFOtVg/4To/0zWC/EULQ3d2Nz+dDq9UOKiNHn8+Fy+VGr9cHjX60ew3nXbhcLjweDxqNmvj4hBHttBYICOz2bvx+PxqNhvj4+H73FUIEi9cMtNGIEAH8/gCKAmp17HHXW7du5bLLvk1qahrvvbdqwIC73ra6URQV8fG98ubz+YLPHaucALz11pvcfPOPOfHEk3jhhX8OmEng9XpxOp34/X6MRuOgWzAfkYkjvx2o5sJYIKPcJd9YVCo1oynMpNFooq7ZDjQoiHVXtcGfWTVkQZpYFHysBjlSKQ9HGR4hPj6+X5W1UOrr6+ns7OCEEy4JKkJFUWLq2+EMLI5gMBiGVKKxtDOWnbEURYmpgFD48/VGyg91r+G8i6GMTGyyN3RbFEUZsl8URYVGo+o3OFqx4m3Gjx9PScnEsHcaCATYt28fDz30W7xeL1deedWgs9lobdVoNP2ey+Vy8corr7BgwYJ+O9/19PTw2Wef8cgjvUF4V1yxaND+02q1w9IFw5UJadAlEsnXgq1bt6JSqZg9e86I9+iWfL3ZsuUz7rjjdpKTU5gzZw4nnTSLrKwsmpub2bZtG//+9/s0NjYwf/6ZLF68+JhsM/r228u59957eOGF55k9ezYzZ55IcnIyhw/XsmPHDt577z26u7u48sqruPDCC78R/Sxd7hKJZMzw+bzcdNNNfPTRh7z44stR16sl33x6C6v8lQ8++DdNTY1h6VuKopCRYWbhwoX84Ac3DlinYLhs376dJ598kg0bPqWzs6Of98NqzeTaa6/l6quvibnmhDToEonkPxaPx8POnTvx+31MnDgpZrel5JtHbx2HKqqqqqioqKCrq4vExCRycnIoLCxg3Li8ES35DIbf72ffvn3U1dVRWXkQp9NJamoa+fn55OfnYbNljfmGKdKgSyQSiUQiGRayUpxEIpFIJNKgSyQSiUQikQZdIpFIJBKJNOgSiUQikUikQZdIJBKJRBp0iUQikUgk0qBLJBKJRCKRBl0ikUgkEok06BKJRCKRSIMukUgkEolEGnSJRCKRSCTSoEskEolEIpEGXSKRSCQSadAlEolEIpFIgy6RSCQSiUQadIlEIpFIJNKgSyQSiUQiDbpEIpFIJBJp0CUSiUQikUiDLpFIJBKJRBp0iUQikUikQZdIJBKJRCINukQikUgkEmnQJRKJRCKRxILmy7hpm9dNvdtOmauT9h4XakVFgkZHviGBHEMiaTojakUZ8PweEeCgowN/wD/iZzCqteTHJxN6l2aPk6YeB4ijxyxGE+laQ/j9AwEqHO0IEeg9oECy1kiWIWHI+3oCfiocbWH3MGn15BgTw57FKwIcOAZtLIhPHvX7qnJ2Yvf1jPh8tUpFQVwKOpUKd8BPpaOdgBCjeyhFwWYwkaLVD/vUCkc7Hr8v7FiKzogthvd39N204w8Ewo5nGk2kRsjKUKzvqKelxxX8/3i1ltNSbOhU6pivYfd7aXLbEQzepwoKBkWFolKhV2tJ0RpQhrh2t6+HGlcX4sj7UsCsTyBDZxzyubp8PdQ4O8OOZejjMevjwo45/F6qnJ1H7zECUnVGMmN8f6G0e93UubpHJYpDvfcuXw/17m72Ojtp97oAhQSNFqsujmJjEsk6I4ZhvO8j19vlaKfb50EA8Wod4/Tx5Mclkaw1oB/G9SJlu9njpMzRTr3XSXePGxAYNXqy9fFMjE8lZRjPKxAccHbi8XmDxwxqDflxyagUZcjzy+xt+EJ0oFalpiA+BU3IuQI45OzEGaKjdGoNBXHJg9qRI5Q72ukJ0Qeh+ir0HrWubrq87pHPnhWF/PiUYb3rr7RB7/B5WNVUydKWA7zncfR1kxLSZTBZY+DyhHS+lVFAaaI5qmB2+Xq48cCnfOxxjPhZfmay8OuS09AqR1/axvZaLqreFva75fmzWJiRH6HkPEwuXwshAnS2IZG/j59HnsE05GBmyr4PIUR5/S51HLcWzg4TPoffy7UHN7DZbR9xG28zZfCHiWeO+r39q3YXd3YcHvH5J+niWDHpbMw6Iy1eN1eXf8K2UQwQjhj0jwtP5rTU7GGf+vChLfzV0RZ27Lvxqfx5/Kn9Bm/R+LjtMN+u3IQ9bLAlWJ0/hwUZeTE/R1OPizsqN7PeF6IkFBV7dWdSYkqLfcDl7uaEPR/QIwIx9Bug0rBAa+A0YwoXmAuZZEof0AAccnUxrewjCGnrdYkWfls4l7QhBlPVjnamln0Y8o3DmznTuThzQvjv3HbO2v8xDRGDrOHwkqWEK8eVDvu8HV3NzD+wPuwZh4fg3wUnc1Z6br+/OAM+3m06yKvNlfyfuzOqvrOptVwel8q5abmckpJNkkY34J2cAR//bj7ES80H+D9X5PV6rzlOrePbcSlclJ7HzGQbiYNcL3KStLOriTcaK1juaGG3zxOlTwRZah2XGlO41FzASck24tWDmxCfENxTtZWXupuDx2xqLf8qmMO8FNugvS6E4NaDG1npPjrgutSYxNMTzyQ5pF1+EeCx2p080VEXPJaoUvNG/mzOTMsZ/B4I7jy0hTdC9EGovgp9ltcayri1+cCIZXSqWsuKKeeSq48fMxt73FzujR4nP9u/nkWHd7IqaIiVCE2jsNvn4d6Ow8yuWMed+9dx0NkRdd6hQQFl5P9USnRdp4743UDCkBnxu7Webh6v3o7d7x2yLywRz64MMIrUjbaNI1ZS/ftlNM+hVY5tu1AUElFG3DpVlPu/4mxnWWMF/iFmiY09Lp6s34NdBPpdQxnmA33aVstWX09Q9kEBIXi7qYIAYlhvyBpr36FAwM/7Hge/7KjlhPK1/PrAJtoGmXlYIq7xj+5mXqzfizeWAUSkrEd5a4oCCaOUCWWEwqAoo5fFaPe2+708cnALl9fs4BV354D6rs7v44nuJi44tIUb9q5hU3tdVO9Vt9/LHyo/5+KabX3GnCgGV6HK7+Wx7ibOrNzMkn0fsamjnqHe0mG3nfvKNzCvfB0PdtaxOyiT/d/lYb+XP9qbmH9wE7eWfcyhCA9MVA9dxLutC/h4oGYH1e7uGM4N1z3qAZ4sUm93iQC/qt1BubNj2PfQKmOjB3WKMuZ29rgYdJffxy8PbuQfjpaQselQA1/BY92NPFi1FV8gwFedHuC5rgaer9+Hb7TuZMmXwh+bKyhztA8623i1YT/LXJ2j/yYCPl5pOYgrytfwUlcDDW7H8Wm0ENzfUcsvDmykO4bBaK9iEzzUfIBVLdXDHHj8Z+AXgmdqdvHL9uq+OWBsvOLu4mfVW2mJGFx5RYB/1OzinrYqlGHoln+6OvhV9TZaQ5Z0Itlnb+XG/Z/w687DeMRw9KzgKUcr3y/7mE/b64bdR6s93fyhajudo/XUDcK6Hie/q9pGm9fzHyN7x8XlvqWznlfsrWHHUlCYqDMyXp+ARwSodHdT5e+hPkRg81QafpQ9Fa1q6HGHCchV1DHP2kJd7ceKdiF4vLGciXEpzB+BK7j/JxNOPJD3JbcRwACMU1RoY3ySBEUdZg40itLr4Yg0mEBzhMJKRCFeiT7qP9bj3V2+Hv5yeDe/LZob1ZW4x97Kn1oOHpN77ehsYrW7K+rftvs8rG2rYZFt4oivn4FCiqKEyVAAcCFoFYJIFfdidxPnNFVySeb4mOSyLuDn14d3UhSXREl8yjGXsQwULMOQX/UxnP3kKwrxMc51vIh+krjP2c4TrZURcgwTtQZKDIkIBBVuOzU+D/UiwJGFhnhF4ee2yf3iE6qdXfym9SBKiE6IB6ZqjRTpE9ApCgc8Diq9LupFAG/Qi6hiibVkwHiHSlcXPzqwkX/3OPrNRFMVhSxFTZrWQADo9Lmp8vtpj9BKa3xueg59xpOaU5hqSh9WP7/Q3cDEhjJuzJoS03r6SPg/ewsT6vbwk9zSMdGH4xVVr8cxBhIVFWM9Rx9zg+4XgnfbaukKEwSF32dO5LuZEzD2rd35RIBd3a280VjOsq4GykSAe6wTmJyQHlWh+CIE6xR9PC9MPCvmDtMoqjF5wfsDPu6v2UGWIYHxcaMISBP92zhdH8/rJfPRxPjcY2XQC1VqXi6Zj00XF5sbSFFIUveueaVp9fyx6JSobsVDjjYur90e5lT7QUo2V5iLovq/hopXGAl/627grNZqLjbnhynqbr+XPx/eTVmMs9ihvom3WippHWS29XxLJReYCzHFuAYayZJEK/89bkaYBPlEgE6fh71dTfypqYKNvqNmvQt4sbmC8y2FMQdUbfS6ub9qK48Wn4xZaxy5qAuIDP1cnJTJXfknxTy/PZaBRo/ZpnLKMGIh4tXaMN30RWcjNRHBrHek5bEkd3pwoOgXgjJnOx+2VLO0rYrtfi+3JGczPy23nw7b2FFHS4iX0gjck57PDTmlwesFhKDc2cGqlkO83FbNLr+X7yfbOHeAdjj8Xu6t3MxHEcY8BYXz4pK5MXMi0xIzetsmeoN5N3fW81JjBW84Wgj1Y63zebiv8jP+OnE+acMICu0Ugocb91NkTGbBEGvdI8WO4I/NByiJS+bCjLwRTwNEn4cu8ujL409jnDExRs+WMmiMxNfCoAsEO93dYZ9lqdbAxZZCTCEfgkZRcVKShZmJZq60t7C6tZpLLcVRR94KfWvoocYLhTSNfsD16OPJhz0OnqjezgNFc0nW6Ed2EYV+M2ANKlI1hpg8FmOJGkjR6If18QaVkUrNjAFG8vFRXH65ujhmJmYct7Z5heCR+j2ckGgmty9qOoDgvZZDPNXdeEzucdDZwf91Hb2WHphvMPFeyJriux4727qaRhT0B5Cq1gafP5ITTBlMNZm5qvwTdgeOBqJt97qpdHUNa8b9qqOVaYf38JPc6SOOrFaUvnXMCDlJ1eq/FPlOVGtGJNtHNN4OVydhjmRFxTXWCWHKXKPAtIR0piakc7G5kFcaK7g6c0LUgUlnRPBvhqJwiWV8uHFQYHJCGpMS0rjUXMRz9Xu5LnvKgIP6T9pqecfZHvQOKIAJhfstxfx31hTiQj1UCmhVKs5My2VOso0ZNTu5r/kATSFa/TVPN5c1Vw7bq1QZ8PNg7Q4KjYkUxiWNyfusFQF+fXgXecZEpiakjVQdh0XWHyFZoxuFrBx7jotlcIvw0epOfw9Ob8+As7lppgx+mjcz5gjNryJ/7m5mad1eer4G6/+SCGXX4+Sl+n3Bd1fl6ubh+n3HaIALq1qrqAwxpFPVWn6bdxKlEYO/V5sq6BlF2uJgTEvM4Fvx4cqtQvhxD3O90Qv8vqWSt5sr5Xp63/v1RL4zEaC5xzmgociLS+L2/JlR014DCJyB8Oh/p4A6j33Q691TOIcsffQBnSvg5+mGMlpCZpwCuCU1h+9nTw035hHEqTVcl1vKjSlZ/b1KzQdpHWZalwA+6nHy2+qtwz53OPfY5HXzUPU2mgaJJ/gmMOYGXUEhN8IdJwJ+flm5mY3th49ZwEIwAvFLwhYxslYQPNRUwcdtNcdUzX0FHBDfAK0bPsgap6goVevCPoY/tVWxpasBrwjwUv0+NnnDFcG5UZSlLoYljpYeF8vba8N8L+clWpmSkMb1qeGpTy/am6mIIUp3pMRFzixE8D/hRiXC1Rgp660iwG/qvuCL7tYIY8SIs8G+XDFXRnGmQl7EUpQK+MWhLaxoPECjx8lwhvgqFBIjBnotCH5VtZW3Gito8jiHzMyIZL+9jU0hAwIFOFGj579sk2JautCr1NyUU8psdfiE690ee7++FXMAABcqSURBVL+6A9HIUFSoI9aTX+hu4YX6fUNmTgQzVIbAgEJ8xPf4oqONpw5/gfsYDpIVvloKecxd7ipF4VyThRe7m8LcUM8723m+Yh3n6U3Mj09joimdUlMGmYaEIdd+BaLf+nKd38urDeUxGbx5yZlk6hOOaTtPiUtmoi6Bh9qq8PSpxSYR4N6a7RTEJVE4zPV0IXrdv6E0+3t4rbEipgCgk5OsZI3BGjP0rn2903KI1Bg8KHnGJE5KNH8F51FHmajRc7V1Aotrd6CI3lXbwwE/T9TuYrHXw8NtVWG/X2IyMy/RwqrDu8KOxxKuuK6tlvdDZms2ReHijALUisK56XkkNR+gs0+ptQvBe82VlMSnHvOgIXfAT21EtH6WSoUmZBmsVw4FkdnhVyRn4exx8jd7S/DYNl8Pv636nCcmnB7M5ffFGDUdbQ19j7ub1xrLhxwMKyicl5ZLwjH05n3U1UhzDGbXqNJwdlpumBFUgBmmDNKaKmjte/oAsNrr4r3qLZxYb2RhfDpTEjM4wZRBuj6BhCFyuScmWqC5PGyg8ZHXxUfVW5lRt5sL4lIoTbIyM9GMWZ8wZG74ju5makLejQDON2XEvBYMYNHHc1myjU2th8LexsbOeqYnWQY9N1tr4O7UXO5tPOol6EHw+6YKJselcFZ67oAptxoltlmoW6XiWWsJd9Xvpa6vrQrwcOshpsSlstBcMKxASkF/fQwKK1urMHcPHT+SYzAxO8n69Q+KU4CzMvKY21zOWq874gNVeM9j5z2PHdoOUajWcaExiTNTx3Fyio30AaIzFZR+a+hbfB6uqNka05v5XHfqMTfoCYqaH2RPocxj5xVH76ccANb7PNx/6HP+UHxKTEVLQmfi2giB2+PzcGXNtph6/bPCk/sZ9EpnJ+4hineoVArF8SmD5rBXiQA31u0mlgTE35uLx8SgCwQVjo4hUxo1KhXFkWvCEQNGBYX5qdnc5Wjj123VweNvujpZW72V9r4PWQEma3T8IGsKdVFmIkOl/dj9Xt5sDR8cnGJIYkpfTEGOMZEbTGZ+39UQ/Ptz7TVcYZtI1jEsRuEK+Hm5bm9fsZOjTNboyYyQGeVI/mzIqx6nNbLAOp5dFZ/yacjg5E1XJ0XV2/l5/okYVZpej4UYesIbbQ39DVcHb1RvjUnWG5Osx9Sg39tRCx01Q/7uQl08J6dk9ZvVnpBk5bL4VJ5ytIZ7K1DY4nWzpe/66SoNF+hNLEjJZn5aDrYBBuAzksxcH5/B3x0t/f62zedhW1cDdNVjVmk4X2/irJQszk7PI3MAmamM4q4vTcgYlrFRgJMSzRhbDxHqu7LH4NJ2iwCXmwtp8br5feshnH2apE4EuLt2J1lGE5PiU6Oe2yNEzFUmv5WeR4ffyz2N5XT1hVd2CMG9dV+QazRxwjD0kkJ/fawCftiwLyY9eG9qHrMSLWMe43Vc0tbSdEYeK5jDzQc3stHrpmeALjvg9/K4vYXH7S2c27CX/82eximpOcMYScXwO2Xs1vnMOiN3586govwTPg+JIH7O0cr4w7u5LXf6l+oO/F3NDv7Z3TTob0rUOj4tvQBVTAFOSgy/GBsB9gvBbVWf8+EQLulzdXG8PPW8CK9P/2cyqNRcZ5vMp/ZWPuyL/PUA9SHuOYHCTy0TmGxK43AUgz7UGvLu7haedx6tSBUPLM4oCAaT6VVqFmbk8/uu+uAzlvu9rG+t5ju2icPqyR3uLpY17A8tSEgAQXWPk+32Ft52deAM+aMBuCY9f8jqb0d6YlJ8KndnTeX6qi3BiG4X8Nf2Worjkrk6ohrc8Zb143Fv1QDSHafWcE/BbFwVn/KqqwP3ANdvCfh5ztXBc64OTm7az83WiXzbWtzPQ5mg1nJvwSxcBzbwqrMdzwDXawq53pnNB/ihtYTzzYX9Bhz9iwgJsnTDz1LQa/TEKwquEDmq83rwBALohwjcNag03Jg9hT2uTl53tgf9IRu9Lh6s2sYfik7GrBtdsJlWUfE920R2OTt4vrsp6Gna7vPwYPU2Hiueh00fN+LrB4ajB4/TWqnqeH0apYlmXpl4No9bJjBLoyNpiE5Y1ePkvys383bTga9VsE1JQgr3ZE/rl0P7p5ZKVrYc+lJbEhAB7EP88wv/16avY2mPCMQuPXlGE7fZJmEeYMnnelMGl5gLR1SBr0cEeKc5PDd5gkbPnJSssKtNMZm5RH/U9ekCnms+iDswvLKoT7s6uLRmO5fVHv33ndod3NZUzgvOdjqECCokDfAtQyLnZRQM6x7z03K4NaMQU0gLmkWA39fvZUtnI//J2AwJPFlyBi9nl3K21kjGEAp9g6+Hmw7v5M9V26KuI2caEnhywum8kDWN07RG0pXBh8prvG6ur93BU9Xb+5UE1kYZrI9kb4WAEP2WSowqVdQqnNEGS1ZdHHePO4ETImIE/ulo5ZnDu/Ecg4DiVI2eu8bNYJ4uLqy/XnN18mTtLlx+/zdK7o5bLXcFsOjjuCF3GlfaStjZ2ci6zkbWdNVT7uuhKooQHxQB7qrdycxECzlGU8h4sn+OtkVRmKkb2i3pR2BQj12zVSiclz6O/3V2cHNTefB4gwhwX+1OHlJrY6yU11u0Ikw4FRWzdcaYZr1a1di10URvvWNDDEFgpq9ZpsKZaTl8v7OBB9vDXa6lah03ZU0ecR5pjauLv3XVhx0r1sWxvbspYu1dIVWrI3Qa9pnXyca2OuZHqRc+WuJR+JYxkYeLTo5agESIAO4BlL1OUfH9rMmUOzv4a3dTcICwy+/loaptXG0uimmSHW0NvUilYYLWMOS3ElAUVMe43sIcjY5U9dDvOVNrHHRGlKDRcXHmBBaYC/iiq5l1HfWs625kn9fFvojALAG0CcEDzQc5JdnGScmZUb+ly20lLDDns7e7hU2djazpaqDM62J/lECvViH4bUslc5JtzAq5Xv90QIUdznZOTssZVj81ubtxRMhGukY/ZAxUvKIKxjpNSkjl/uxpXFu1haaQa/2+pZKpcSlEVn0wKKphv+98YxK/yT2BKw98GmZn/txWw7S4FDwxDGai56HDfK0xWEtlMNI0huPicDruu62pUEjS6Dk1LZd5abn8yO/loLOTnZ0NvNFWwzJPd1hFpP0BHxvbasjOmhTsj2h56LN08Sybel5Mxm6s3R9aRcX3siaxzdnBUntzUCB2+r38rHobnbGY9Ch56FN1cSybcm5MBWOitTGWgUQs49V8lZpnJ5xBdgzrumPZ1bFMKsQwfSJGlYbrsiazwdHKR33rwyYUlliKKR1mJayjrjnBhy3VNEUo3WXOdt45uKnf7yOVWLMQvN58gNPSco5pRbQZah0/sYznIkvhgPUSFEVBO9iATa3lttwZ7C1fF1yqAHjD082eut0xuiP7r6F/N8nKA0Unx7QD27EOGPx15hTOsBTGps+GuLdCb+GZ2Sk2ZqXYuKWvAMzuriaWt1XztquDdnFUStsQvNtSxQlJ1gFrcCRr9MxNyWJOShZLRIAKZyf7u5t5o7WKFRHXqxcBVjQfDDPo04z9A3R3dTXhCfhjriXgF4J3O+v7LZ+ajUPnkvcQCH67KhTOSh/HrY527myuCP6mHcGPD++gK+L9+xDD/qYVYFZyJndbJ/Lj+j04+s7vRHBL3Rcxedyi56EL/l58Kvkx5M8ryvGJiP9Stk8N7aQEtZZppnSmmdK52Dqe02p2cktIeU0fsNnVwWVCDGmIVShficIy9H10d46bQVX5Oj7sMwwBYKfPM6oeU6GMWIHdapvMEn/xEH3Ym1ISiyJTfYl9rVYUfpcznd8EBq/cplHUUQtCDEaBMZGfZE6irHor9SLApQlpfMdSPOLNbjq8Hp5uOxRFsUGslaxXOtu40d7CFFNsRXZOV+uYbjAFVV+dz8Nyjz3sfvlaAwvNBUMUP1J6DcsgOrQgLom7c0qprdxMecjSwD5/zygkvVf9fRnfs0phTGT7SHsmxKcwIT6FCyxFnFVfxvfqvggbdK9zdxAQYsjBm9I3eZgYn8LE+BTOMRfwSl0ZP2vYE1ZCudrdjSvgD84kJyVmMF2lYXvIu/qLs43vdTQwJzUrprbs7G7mY0d4mqJeUTE3yTrkuZHR4lpFxfezJlHm6uDZkMyJyigBvD4hRrTNrlpRuMxazA5nO090Hq09Xz/KFDZljGTlK2/Qyx3t7LW3cn5GwYCVzkwaHd+1TuCW1sqw6Zcj8PVc5xgfl8wd2dM4dGgLhwK+Lz0SoOQ4Vlwb+8GgwuSksUuHOyd9HNd0NfBeVyM/zpoStl3jsLwIwKftdewcZdGMyoCfVS1VTDbFFo18eaKVHxbNCf5/a48L774PWe6xB+XwDXcXC+rLuD5n2qhn/vNSsrjVOZ5bG/aGBUn9p9LocbKmrZqFGYUkaKL7OPQqNQvNhcxqOcjmkGwBh9/Xz59W53Gwoe0wZ2fkDbjsY1Rp+HbmeN5oqWS59+j13EL0pRD2GvQ8QyJnJqSxPaRaoRq4r2YbfzOayBkifa25x8XD1dv7uflvSEgn0ziy7KF0rYE7cmewv2I96wcowjNakjQ6fppbSkV5d9iWrN8kjktQXIPHwc8PbuLi6m08cHATe+2tAxZDqPc4+vlSC7VxQ6e+AF+xHP/elL3UbG43F4cFDo12RCgZJSKWHGM1P8yexq9sUyiNcVasV/q7Kz0BP882VRCqovJUar5lSOTCIf7lhcRBKMCyjsPUu+0xDyRCSdMZuSOnFBEhQHc3lbOls2H0MwNF4ZrMCSxJsn0jhoujocvXw32HPuOq2p3cXPYx2zsbBtyBscvXQ0dEwKNZYwj70O1+L48c+pzLa7dxS9ladnQ2DZjj3+BxcDjCa2XWaEkIqS+gUhSuzZxEQYgnzg+82+PkR+Xr+LyjIWogsl8I9jnauLtiAy+6wrNL0hQVi60lGEcRuzM+PplfZk0lS6UeM1WebTBxZ04p49XaY3KP/7jCMh0+D7879Dmvu7tQgPvaa/hnZz2Xm8ycnZJFtjERrUqDXwQ45Ojg4fo9YecnANNMaWHuzmiFZer9XpY1VMTcvXEaHaenZh/TTR2iKzoVV2ZOYJernb91NhCrryFaYZkWfw9vNlTEPJuKU2s5PS3nmLexSwjeaz5EWoyzVpWiYn5azlenlG+M/ZdrSCDLUhRzf0eLTt7Z3cyGiHzvW9LyuTZ7ypDXe7OhnP+q3x000Ot9Hta0VnNN1qQRNXtWso0n0gv5cchaZbMIcF/VVp6PO5M0nXFU3Zqg1vLDnGl84e7mvQF2khtI1iO/izJ3N282VsTsXjXr45mbnHlM3J+fdDXSPoytRPPjU5jeF1/hFQGW1n7BM32z32ecbbxdvo6r49M4IyWb8fEpaNVaBIImt52n6vexP2QLUTVwnik9KHM9gQDP1H7Bw10NgMKzzjbeKV/L1aYMTk3KpCQ+DZ1GQ0AI6l3d/KOhjM8jNhDKi0/rpxenmNJZkp7PL5oPhOWRv+Wxs6liHf8v0co5qTmk64woikJHj5t32mp4q7uR3VE2KLorLY/SUXrMFBTOTMvhTlcnP2oogzHwaSrAKUmZ/DJzIj86vIuOGOVroMIyq1qrsHQZY1Q7CnNSbFh1cWOm2sbUoAtgeeMB/tZXKONIdxwM+PhdZx2/66wjRaXGrKhwiAC1UVzrM3RxTDWZ+734yKC4z3weLoup6Eov5+lNzEq2jrlBP+LquT13BhX71/JvjyOm0o/RCsvs9nn4Tu32mO97oT6Bk1Iyj3kbD4kA1/cZmtgkWUV1YsZXqDZ/7Ep/OK7oyFlNAMHbzZU0hCiCOJWac9LzYoqWPyt9HLOb9rMpRIG+21bDRZaiEfWlWlG42jaJT7oaedVz1OX4YY+DZ2p3cVv+SaM2iLkGE/flTufggQ3sj3V/9ShBca+5OngtpsIyvdyWZGNWspVjsUHl3R210FEbs5Z70jopaNA/ba/jty0Hw3LPm0WAx+zNPGZvJk5Rka1S40Nw0O/vZ7RsKjXzUnOC7djQWc89zRVhgcJNIsCjXY082tVIsqLCqlLjRXAgyprzVJWGC9JyowyyFW7MmUa9x8HjXQ1hgZgNIsBvOuv4TWdd3+BXGdCrpaV3Z7/rckpjKn08FFpFxTWZE9jrbOfJrrFJfVQpCpeYC/nC0c5D7TUxa4xohWVuaoh9j4ckRcUHRtOYGnTVWKvNS63FPGQuIneAl90e8FPm90Y15jmKivuyp2HRH/sOON6u63EGE3flzqBAffziEL/cPdnCO/s/caXgoLOLtzrrw1T2TQkZFMRYBjjLkMD8xPBykS+5O9nR1TTiZ0rVGbgtp5SkkO/RBTzeVs2HrdXH5Js/IdHCLzInkXAcP7IvT77C7zw3OZMnsqYxWaWJ+v05RYD9fi8Ho6yTp6LwG+tESkKqpM1OsvBM1jQKB3Bld4gA+/zeqMY8TVH4iWU84wfYYSxOreWXhXO4O3UcSYO5TwYw5umKwi9Tc7mrYBYmjfaY9WiyRs9tuTNYcIyreUZ6k27OKeUyY/KI9eRws+T1x0FOx1znJ6i13JQ7gzeK5rEk0UJhDKM4LTBHo+eZcSdyamrON8YYnJKUyS+tE0mRC+H/Efy75RD7ItZHz08bhy7G7W8V4NvpeVgj5GVZU8WoNpg4MTmT+9PDi8gcFgF+V7uTeo991O1WKwqXWwq5LSXnP+6d61RqLsssZlnJfH6eks2kGL1jpWotj9om893MkjCvkEGl4ZLMCbxTcga/SslhYoxr1NPVWh61TeGakHTfaCRqdPw0/0ReGXciF+kTiKU2mwE4RxfHs7kzuT3/pGGVtI6VfGMiP8+eRskY1tPI1Mdxe+50pn2Nd/WM5LhMF9WKwsxkK9OSzNxkb2NzZz2fdjVR4bHTIgJ0iAAGFHJUGnJ1Rs5LyeHUtJwB61erUJiki8M2CsOYpo3r556LU2u5KmRUKISIupWgWlE4RxdPIKT4RE4MQq1WFC61FFHl7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+DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:37:08] "GET /myclass/api/Send_Evaluation_Convocation_Participant_By_PDF/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/690f1d2e0f9e7ee9f6ce5b83/690f1d44995b26cde96118e6,690f1d44995b26cde96118e7,690f1d44995b26cde96118e8,690f1d44995b26cde96118e9,690f1d44995b26cde96118ea,690f1d44995b26cde96118eb,690f1d44995b26cde96118ec,690f1d44995b26cde96118ed,690f1d44995b26cde96118ee,690f1d44995b26cde96118ef,690f1d44995b26cde96118f0,690f1d44995b26cde96118f1,690f1d44995b26cde96118f2,690f1d44995b26cde96118f3,690f1d44995b26cde96118f4,690f1d44995b26cde96118f5,690f1d44995b26cde96118f6/66dc4ddf75b3f60c3ea43084 HTTP/1.1" 200 - +INFO:root:2025-11-08 11:43:14.100623 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:43:14] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:43:14.165962 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:43:14] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:43:22.130895 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:43:22] "POST /myclass/api/Duplicate_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:43:22.224479 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:43:22] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:43:24.498052 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:43:24.500054 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:43:24.504575 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:43:24] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:43:24] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:43:24] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 11:44:50.158545 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 11:44:50.158545 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 11:44:50.158545 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 11:44:50.158545 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 11:44:50.159545 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 11:44:51.426331 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:44:51] "POST /myclass/api/Update_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:44:51.601616 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:44:51] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:44:58.986163 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:44:59] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:45:00.401515 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:45:00.403514 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:45:00.407513 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:45:00.412520 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:45:00.421522 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:00] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:45:00.429090 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:00] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:00] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:00] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:00] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:00] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:45:05.294033 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:05] "POST /myclass/api/Get_Accepted_Insription_From_Session_id_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:45:09.987494 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:10] "POST /myclass/api/Record_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:45:12.155285 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:12] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:45:55.836104 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:55] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:45:55.928206 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:45:55] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:46:40.586142 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:46:40] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:08.467455 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:08] "POST /myclass/api/Add_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:08.554643 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:08] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:10.633939 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:47:10.637476 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:47:10.638473 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:10] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:10] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:10] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:29.858076 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:29] "POST /myclass/api/Update_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:29.949063 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:29] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:32.393442 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:32] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:34.340568 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:47:34.343582 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:47:34.344568 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:47:34.350601 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:47:34.355605 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:47:34.364608 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:34] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:34] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:34] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:34] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:34] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:34] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:37.307767 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:37] "POST /myclass/api/Get_Accepted_Insription_From_Session_id_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:44.299799 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:44] "POST /myclass/api/Record_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:47:46.129541 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:47:46] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:49:24.651483 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:49:24] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:49:24.747045 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:49:24] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:49:53.851354 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:49:53] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:49:53.919407 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:49:53] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:51:05.237217 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:51:05.239218 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:51:05.243219 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:51:05.250219 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:51:05.252728 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:51:05.257734 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:51:05.269741 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:51:05.279740 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:05] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:51:21.459490 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:51:21] "POST /myclass/api/Get_List_Evaluation_Planification_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:52:04.630607 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:52:04.632607 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:52:04.633607 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:52:04.636609 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:52:04.639629 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:04] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:04] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 11:52:04.648630 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:04] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:04] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:04] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:06] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:52:15.617109 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:52:17.825686 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2077 +INFO:root:2025-11-08 11:52:17.833672 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:18] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 11:52:18.013119 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:52:18.016125 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:52:18.020126 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:18] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:18] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:52:18] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 11:53:25.850113 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 11:53:25.850113 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 11:53:25.850113 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 11:53:25.850113 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 11:53:25.850113 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 11:57:49.351732 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 11:57:49.351732 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 11:57:49.351732 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 11:57:49.351732 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 11:57:49.352742 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 11:58:46.348890 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.356891 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.365899 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.384619 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.403619 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.411619 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.414653 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.426657 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.438707 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.454711 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.465711 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.474827 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.489823 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.495824 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.508848 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.523831 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.539348 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.549348 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.555377 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.566349 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.573350 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.580349 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.592350 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.598351 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_Class_Niveau_Formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:58:46.679975 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.682938 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 11:58:46.686935 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:58:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:59:12.114141 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:59:12] "POST /myclass/api/Add_Update_UE_To_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 11:59:12.162650 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 11:59:12] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:10:26.846420 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:10:26.846420 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:10:26.846420 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:10:26.846420 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:10:26.846420 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:10:46.914236 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:10:46.915220 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:10:46.915220 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:10:46.915220 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:10:46.915220 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:11:52.554029 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:11:52] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:11:53.432868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:11:53.435868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:11:53.438868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:11:53.441870 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:11:53] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 12:11:53.448868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:11:53.453874 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:11:53] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:11:53] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:11:53] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:11:53] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:11:54] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:12:05.045948 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:12:06.305117 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2095 +INFO:root:2025-11-08 12:12:06.313102 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:12:06.406220 : Cacul_Session_Note_Finale_For_calcul_mode_1 -'list' object has no attribute 'keys' - Line : 1351 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:12:06] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:12:06.410216 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:12:06.411216 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:12:06.413216 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:12:06] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:12:06] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:12:06] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:13:51.554671 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:13:51.555673 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:13:51.555673 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:13:51.555673 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:13:51.555673 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:15:48.656342 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:15:48.656342 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:15:48.656342 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:15:48.656342 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:15:48.656342 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:16:20.888175 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:20] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:21.643880 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:21.645894 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:21.652900 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:21.655881 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:21.658895 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:21.662898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:21] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:21] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:21] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:21] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:21] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:22] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:38.551376 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.552377 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.555385 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.558376 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:38.570377 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:38.609888 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.611894 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.615895 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.620894 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:38.627895 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.632895 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:38.638903 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.641903 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.646902 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:38.654420 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:38.658420 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:38.666425 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:38] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:39] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:39] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:48.605471 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:48.610470 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:48.614473 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:48.621510 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:48.622471 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:48.626470 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:48.635470 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:48.640485 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:48.643470 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:48] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:16:50.367058 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:50.369075 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:50.372078 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:50.375062 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:50.382078 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:16:50.385077 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:50] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:50] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:50] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:50] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:50] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:16:51] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:17:16.378782 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:16] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:17:17.133669 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:17:17.136670 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:17:17.139671 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:17:17.143671 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:17] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 12:17:17.147670 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:17:17.149669 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:17] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:17] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:17] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:18] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:17:27.962206 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:17:29.910192 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2098 +INFO:root:2025-11-08 12:17:29.917193 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:17:30.018986 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1444 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:30] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:17:30.023985 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:17:30.024986 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:17:30.025987 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:30] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:30] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:17:30] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:19:16.188566 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:19:16.188566 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:19:16.189551 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:19:16.189551 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:19:16.189551 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:20:29.698798 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:20:29.699798 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:20:29.699798 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:20:29.699798 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:20:29.699798 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:20:35.697366 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:20:35.700350 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:20:35] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:20:35] "POST /myclass/api/Get_List_base_calcul_note_class_and_ue_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 12:20:45.833018 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:20:45] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:20:56.035697 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:20:56] "POST /myclass/api/Add_Class_UE_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:20:56.086780 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:20:56] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:20:57.941450 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:20:57] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:21:07.204858 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:21:07] "POST /myclass/api/Add_Class_UE_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:21:07.283373 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:21:07] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:21:22.251937 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:21:22] "POST /myclass/api/Delete_Class_UE_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:21:22.270176 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:21:22] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:21:33.515892 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:21:33] "POST /myclass/api/Delete_Class_UE_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:21:33.532408 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:21:33] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:22:10.045669 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:22:11.113415 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2100 +INFO:root:2025-11-08 12:22:11.120409 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:22:11.222941 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1446 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:22:11] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:22:11.226876 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:22:11.228946 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:22:11.230945 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:22:11] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:22:11] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:22:11] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:24:31.215937 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:24:31.215937 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:24:31.216937 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:24:31.216937 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:24:31.216937 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:24:43.909882 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:24:44.840983 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2102 +INFO:root:2025-11-08 12:24:44.849020 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:24:44.951759 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1448 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:24:44] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:24:44.958760 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:24:44.960761 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:24:44.963762 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:24:44] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:24:44] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:24:45] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:26:08.885555 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:26:08.885555 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:26:08.885555 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:26:08.885555 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:26:08.885555 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:26:35.111201 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:26:37.430685 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2102 +INFO:root:2025-11-08 12:26:37.438246 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:26:37.546192 : Cacul_Session_Note_Finale_For_calcul_mode_1 -list indices must be integers or slices, not str - Line : 1422 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:26:37] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:26:37.551193 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:26:37.553192 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:26:37.555192 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:26:37] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:26:37] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:26:37] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:27:54.667382 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:27:54.667382 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:27:54.667382 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:27:54.667382 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:27:54.667382 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:27:57.950591 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:27:58.935548 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2102 +INFO:root:2025-11-08 12:27:58.943548 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:27:59.053694 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1448 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:27:59] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:27:59.057694 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:27:59.058696 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:27:59.060700 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:27:59] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:27:59] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:27:59] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:29:01.157381 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:29:01.158387 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:29:01.158387 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:29:01.158387 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:29:01.158387 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:29:06.291839 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:29:07.326447 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2105 +INFO:root:2025-11-08 12:29:07.334793 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:29:07.446159 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1451 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:29:07] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:29:07.450641 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:29:07.452641 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:29:07.454648 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:29:07] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:29:07] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:29:07] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:30:30.433307 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:30:30.433307 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:30:30.433307 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:30:30.433307 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:30:30.433307 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:30:30.491219 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:30:31.120139 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2107 +INFO:root:2025-11-08 12:30:31.128034 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:30:31.249846 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1453 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:30:31] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:30:31.254835 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:30:31.258841 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:30:31.260841 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:30:31] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:30:31] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:30:31] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:35:23.010663 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:35:23.010663 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:35:23.010663 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:35:23.010663 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:35:23.010663 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:35:29.511604 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:35:29.511604 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:35:29.511604 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:35:29.511604 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:35:29.511604 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:35:53.407144 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:35:53.409149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:35:53.414149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:35:53.418147 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:35:53.420149 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:35:53.425660 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:35:53] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:35:53] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:35:53] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:35:53] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:35:53] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:35:54] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:35:59.093402 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:36:00.946775 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2113 +INFO:root:2025-11-08 12:36:00.953775 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:36:01.068240 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1459 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:36:01] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:36:01.071788 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:36:01.073928 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:36:01.074928 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:36:01] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:36:01] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:36:01] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:38:41.857711 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:38:41.857711 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:38:41.857711 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:38:41.857711 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:38:41.857711 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:39:05.457965 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:39:05.459992 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:39:05] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:39:05] "POST /myclass/api/Get_List_base_calcul_note_class_and_ue_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 12:39:08.747524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:39:08] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:41:19.660210 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:41:19.660210 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:41:19.660210 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:41:19.660210 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:41:19.660210 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:41:33.856495 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:41:35.308483 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2112 +INFO:root:2025-11-08 12:41:35.332505 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:41:35.438050 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1459 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:41:35] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:41:35.442228 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:41:35.444115 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:41:35.446121 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:41:35] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:41:35] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:41:35] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:43:23.879692 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:43:23.879692 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:43:23.879692 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:43:23.879692 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:43:23.879692 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:44:31.033191 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:44:31] "POST /myclass/api/Get_List_Evaluation_Planification_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:45:10.753712 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:45:10.753712 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:45:10.753712 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:45:10.753712 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:45:10.753712 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:45:52.339113 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:45:52.339113 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:45:52.339113 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:45:52.339113 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:45:52.339113 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:46:31.281380 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:46:31.281380 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:46:31.281380 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:46:31.281380 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:46:31.281380 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:47:49.248902 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:47:49] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:47:55.262325 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:47:55.266839 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:47:55] "POST /myclass/api/Get_List_base_calcul_note_class_and_ue_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:47:55] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:49:39.440651 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:49:39.440651 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:49:39.440651 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:49:39.440651 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:49:39.440651 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:49:39.500352 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:49:39.502351 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:49:39] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:49:39] "POST /myclass/api/Update_Class_UE_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:49:39.540434 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:49:39] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:51:08.145442 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:51:08.146442 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:51:08.146442 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:51:08.146442 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:51:08.146442 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:51:30.324829 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:51:30.324829 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:51:30.324829 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:51:30.324829 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:51:30.324829 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:52:01.280851 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:52:01.280851 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:52:01.280851 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:52:01.280851 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:52:01.280851 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:53:33.511646 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:53:33.512635 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:53:33.512635 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:53:33.512635 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:53:33.512635 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 12:53:47.279185 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:47] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:53:48.426483 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:48.427445 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:48.433448 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:48.436483 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:48.439490 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:48.445490 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:48] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:48] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:48] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:48] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:48] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:49] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 12:53:51.981421 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:53.772294 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2112 +INFO:root:2025-11-08 12:53:53.780294 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:53:53.911326 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1459 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:53] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:53:53.915326 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:53.918326 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:53:53.919325 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:53] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:53] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:53:54] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 12:54:39.660485 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:54:40.039468 : Cacul_UE_Note_Finale_Standard -could not convert string to float: '-' - Line : 2112 +INFO:root:2025-11-08 12:54:40.048752 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:root:2025-11-08 12:54:40.242328 : Cacul_Session_Note_Finale_For_calcul_mode_1 -float division by zero - Line : 1459 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:54:40] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 12:54:40.247596 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:54:40.250106 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 12:54:40.252107 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:54:40] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:54:40] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 12:54:40] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 12:56:36.759533 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 12:56:36.759533 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 12:56:36.759533 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 12:56:36.759533 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 12:56:36.759533 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:01:49.431167 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:01:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:02:06.179154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:02:06] "POST /myclass/api/UpdateStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:02:06.891051 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:02:06.892058 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:02:06.894194 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:02:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:02:06] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:02:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:09:13.800908 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:09:13.800908 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:09:13.801907 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:09:13.801907 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:09:13.801907 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:15:57.458996 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:15:57.458996 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:15:57.458996 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:15:57.458996 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:15:57.458996 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:17:53.905252 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:17:53.905252 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:17:53.905252 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:17:53.905252 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:17:53.905252 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:18:56.977782 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:18:56.977782 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:18:56.978783 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:18:56.978783 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:18:56.978783 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:20:39.252615 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:20:39.252615 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:20:39.253629 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:20:39.253629 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:20:39.253629 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:20:47.402500 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:20:47.402500 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:20:47.403500 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:20:47.403500 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:20:47.403500 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:21:25.647604 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:21:25] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:21:26.129898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:21:26] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:21:33.035128 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:21:34] "POST /myclass/api/UpdateStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:21:34.896075 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:21:34.897074 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:21:34.899074 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:21:34] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:21:34] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:21:34] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:23:09.607668 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:23:09.607668 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:23:09.607668 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:23:09.607668 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:23:09.607668 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:23:50.661412 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:23:50] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:23:52.492034 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:23:52.495034 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:23:52.499036 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:23:52.502539 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:23:52.506056 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:23:52] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:23:52] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:23:52] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:23:52] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:23:53] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:24:06.772108 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:24:07.852535 : L'utilisateur destinataire de l'email est invalide +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:24:08] "POST /myclass/api/AddStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:24:08.265839 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:24:08.268839 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:24:08.271349 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:24:08.276349 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:24:08] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:24:08] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:24:08] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:24:08] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:26:39.737701 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:26:39.738658 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:26:39.738658 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:26:39.738658 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:26:39.738658 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:26:47.312773 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:47.315764 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:47.319760 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:47.323755 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:47.326771 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:47] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:47] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:47] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:47] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:47] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:26:49.556110 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:26:51.715701 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:51.718717 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:51.721701 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:51.728716 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:51.731700 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:51] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:51] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:51] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:51] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:52] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:26:56.698919 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:57.654907 : L'utilisateur destinataire de l'email est invalide +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:58] "POST /myclass/api/AddStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:26:58.120163 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:58.124158 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:58.127158 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:26:58.129664 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:58] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:26:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:27:50.365042 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:27:50.365042 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:27:50.365042 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:27:50.365042 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:27:50.365042 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:29:28.393236 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:29:28.393236 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:29:28.393236 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:29:28.393236 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:29:28.393236 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:29:28.505756 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:28] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:29:30.882085 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:30] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:29:30.940658 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:30] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:29:30.996212 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:29:31.046189 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:31] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:29:31.073192 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:31] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:33] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:29:36.340115 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:29:37.186806 : L'utilisateur destinataire de l'email est invalide +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:37] "POST /myclass/api/AddStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:29:37.653045 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:29:37.654028 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:29:37.658604 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:29:37.663626 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:37] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:37] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:37] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:29:37] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:32:34.723390 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:32:34.723390 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:32:34.723390 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:32:34.723390 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:32:34.723390 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:33:10.493777 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:33:10.494776 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:33:10.494776 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:33:10.494776 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:33:10.494776 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:33:59.097494 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:33:59.097494 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:33:59.097494 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:33:59.097494 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:33:59.097494 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:35:18.646833 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:35:18.646833 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:35:18.646833 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:35:18.646833 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:35:18.646833 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:35:48.018719 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:35:48.018719 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:35:48.018719 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:35:48.019722 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:35:48.019722 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:37:39.198103 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:37:39.198103 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:37:39.198103 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:37:39.199125 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:37:39.199125 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:37:39.426075 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:39] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:37:41.034875 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:41] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:37:42.203693 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:42.207708 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:42.211707 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:42.215692 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:42.220692 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:42] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:42] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:42] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:42] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:37:57.100440 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:58.142172 : L'utilisateur destinataire de l'email est invalide +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:58] "POST /myclass/api/AddStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:37:58.761201 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:58.763176 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:58.767178 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:37:58.769947 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:58] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:37:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:11.620244 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:11] "POST /myclass/api/Duplicate_List_Session_Formation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:11.795468 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:12] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:15.163986 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:15.167985 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:15.168991 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:15.176000 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:15.183000 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:15.186996 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:15.195576 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:15.201579 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:15.207574 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:15] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:18.611092 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:18.614103 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:18.618107 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:18.621091 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:18.626107 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:18] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:18] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:18] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:18] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:18] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:24.347262 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:24] "POST /myclass/api/Get_List_Sequence_Planning_Model_Header/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:27.170922 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:27] "POST /myclass/api/Get_Given_Sequence_Planning_Model_With_Option/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:31.905684 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:31] "POST /myclass/api/Apply_Planning_Model_To_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:31.927701 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:31] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:36.715538 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:40:41.062385 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:40:43.565016 : AddStagiairetoClass_mass_for_many_session Ligne 2 : Le code session 'licence_l1_081125' ne correspond pas à la session selectionnée : 'licence_l1_081125_dup' +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:40:43] "POST /myclass/api/AddStagiairetoClass_mass_for_many_session/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:12.888931 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:12] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:12.914945 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:12] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:12.938978 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:12] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:12.961456 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:12] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:12.987458 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:13] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:15.222128 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:15] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:18.493835 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:41:21.396301 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 13:41:24.121513 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 13:41:26.638713 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 13:41:29.327616 : L'utilisateur destinataire de l'email est invalide +INFO:root:2025-11-08 13:41:34.966613 : L'utilisateur destinataire de l'email est invalide +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:36] "POST /myclass/api/AddStagiairetoClass_mass_for_many_session/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:36.097023 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:41:36.127321 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:36.153930 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:41:36.183028 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:36] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:41:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:44:24.412357 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:44:24.413357 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:44:24.417357 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:44:24.421480 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:44:24.427441 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:44:24.428950 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:44:24.435953 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:44:24.445500 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:24] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:44:50.260760 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:44:50] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:05.378600 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:05] "POST /myclass/api/Add_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:05.474674 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:05] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:06.953873 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:06.955889 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:06.960889 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:06] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:06] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:06] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:09.722407 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:09.724425 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:09.727420 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:09.733405 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:09.737403 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:09] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:09.747432 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:09] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:09] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:09] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:09] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:09] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:12.003320 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:12] "POST /myclass/api/Get_Accepted_Insription_From_Session_id_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:16.126082 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:16] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:17.666510 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:17] "POST /myclass/api/Get_List_note_evaluation_Ressource_Affectation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:32.088866 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:32.090866 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:32.093870 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:32.097871 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:32.101870 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:32.110982 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:32.120497 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:32.123502 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:32.129497 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:32.133522 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:32.139039 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:32.148549 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:32] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:33] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:37.930751 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:37.933751 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:37.936751 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:37.940752 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:37.946751 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:37.948751 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:37.952752 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:37.963751 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:37.972751 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:37.977752 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:37.981753 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:37.989751 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:37] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:38] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:38] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:38] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:40.316472 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:40.320470 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:40.325475 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:40.326975 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:40.331984 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:40.339981 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:40.347201 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:40.357984 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:40.362981 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:40] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:41.761569 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:41] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:46.467366 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:49] "POST /myclass/api/Accept_List_AttendeeInscription/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:49.248964 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:49.250963 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:49.253965 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:53.281612 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:53.285613 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:53.289757 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:53] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:53] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:53] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:54.726394 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:54] "POST /myclass/api/Get_List_note_evaluation_Ressource_Affectation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:55.276998 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:55.280014 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:55.282551 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:55.285569 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:55.290665 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:45:55.300666 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:55] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:55] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:55] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:55] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:55] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:55] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:45:57.859792 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:45:57] "POST /myclass/api/Get_Accepted_Insription_From_Session_id_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:02.824943 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:02] "POST /myclass/api/Record_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:04.835413 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:04] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:17.707842 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:17] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:17.817005 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:17] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:23.754992 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:23] "POST /myclass/api/Duplicate_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:23.828331 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:23] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:26.407967 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:46:26.412008 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:46:26.415029 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:26] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:26] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:26] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:43.354953 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:43] "POST /myclass/api/Update_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:43.449008 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:43] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:45.394653 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:46:45.396670 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:46:45.400655 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:46:45.405655 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:46:45.409669 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:45] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:45.424654 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:45] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:45] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:45] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:45] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:45] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:48.386185 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:48] "POST /myclass/api/Get_Accepted_Insription_From_Session_id_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:53.556619 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:53] "POST /myclass/api/Record_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:46:55.063084 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:46:55] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:14.082914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:14] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:14.148430 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:14] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:17.651576 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:17] "POST /myclass/api/Duplicate_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:17.723093 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:17] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:19.145828 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:47:19.150824 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:47:19.153824 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:19] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:19] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:19] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:38.764250 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:38] "POST /myclass/api/Update_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:38.859344 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:38] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:40.868805 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:40] "POST /myclass/api/Get_List_note_evaluation_Ressource_Affectation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:41.368821 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:47:41.371874 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:47:41.373854 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:47:41.377855 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:47:41.380854 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:41] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:41.390362 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:41] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:41] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:41] "POST /myclass/api/Get_Type_Groupe_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:41] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:41] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:44.296228 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:44] "POST /myclass/api/Get_Accepted_Insription_From_Session_id_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:48.529949 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:48] "POST /myclass/api/Record_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:47:50.086179 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:47:50] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:48:03.965251 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:03] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:48:04.063288 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:04] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:48:13.891930 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:48:13.894932 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:48:13.896932 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:48:13.902453 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:13] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:13] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 13:48:13.909482 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:13] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 13:48:13.913488 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:13] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:13] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:15] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:48:18.530293 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:48:18.816039 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:18] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 13:48:18.945199 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:48:18.946185 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:48:18.949244 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:18] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:18] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:48:18] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:50:13.899917 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:50:13.900918 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:50:13.900918 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:50:13.900918 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:50:13.900918 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:50:41.649170 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:50:41.649170 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:50:41.649170 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:50:41.649170 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:50:41.650157 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:50:46.438994 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:50:47.248402 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:50:47] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 13:50:47.303052 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:50:47.303052 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:50:47.305061 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:50:47] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:50:47] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:50:47] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 13:54:39.167177 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:54:39.169177 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:54:39] "POST /myclass/api/Get_List_base_calcul_note_class_and_ue_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:54:39] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 13:55:33.615849 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 13:55:33.616861 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 13:55:33.616861 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 13:55:33.616861 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 13:55:33.616861 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 13:55:42.654472 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:55:44.431481 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:55:44] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 13:55:44.518047 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:55:44.520065 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:55:44.523047 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:55:44] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:55:44] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:55:44] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:35.545073 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.548072 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:35.555077 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.558591 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.570596 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:35.598254 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.600253 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.603252 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.607255 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.610253 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:35.619254 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:35.626253 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:35.640259 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:35] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:36.961291 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:36.965290 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:36.969289 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:36] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:36] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:36] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:42.587362 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:42] "POST /myclass/api/Update_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:42.688880 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:42] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:59.538404 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:59.922698 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 13:59:59] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 13:59:59.990565 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:59.992567 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 13:59:59.994566 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:00:00] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:00:00] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:00:00] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:01:17.907611 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:17] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:01:18.681495 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:18.682523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:18.687626 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:18.691198 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:18.692179 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:18.702238 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:18] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:18] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:18] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:18] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:18] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:20] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:01:21.097999 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:21.398839 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:21] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 14:01:21.577838 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:21.579829 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:01:21.583828 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:21] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:21] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:01:21] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:05:22.052125 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:05:22.052125 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:05:22.053647 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:05:22.053647 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:05:22.053647 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:05:48.046484 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:05:48.046484 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:05:48.046484 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:05:48.046484 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:05:48.046484 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:06:56.006082 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:06:56.007081 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:06:56.007081 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:06:56.007081 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:06:56.007081 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:07:14.823923 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:07:14.823923 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:07:14.823923 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:07:14.823923 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:07:14.823923 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:08:16.518860 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:08:16.519861 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:08:16.519861 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:08:16.519861 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:08:16.519861 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:08:50.177208 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:08:50.177208 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:08:50.177208 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:08:50.178204 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:08:50.178204 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 14:08:57.820660 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:09:00.997054 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:09:01] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 14:09:01.067059 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:09:01.069060 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:09:01.070058 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:09:01] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:09:01] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:09:01] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:16:20.671607 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:16:20.672607 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:16:20.672607 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:16:20.672607 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:16:20.672607 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 14:16:22.575796 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:16:24.506755 : Cacul_UE_Note_Finale_Standard Erreur Ponderation. La somme = 0 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:16:24] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 14:16:24.649443 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:16:24.654415 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:16:24.658408 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:16:24] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:16:24] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:16:24] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:22:38.253286 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:22:38.253286 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:22:38.254285 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:22:38.254285 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:22:38.254285 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:26:30.790702 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:26:30.791699 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:26:30.791699 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:26:30.791699 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:26:30.791699 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:26:46.459776 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:26:46.460757 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:26:46.460757 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:26:46.460757 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:26:46.460757 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 14:26:54.033538 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:54.038534 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:54.042538 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:54.045536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:54.047536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:54.054536 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:26:54.071537 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:54.075128 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:26:54.085281 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:54] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:26:55.697421 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:55.698419 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:55.702995 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:55.704993 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:55.712992 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:26:55.717993 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:55] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:55] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:55] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:55] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:55] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:26:57] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:27:02.219074 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:27:02] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 14:27:02.505449 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:27:02.506423 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:27:02.511978 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:27:02] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:27:02] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:27:02] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:28:08.466945 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:28:08.470942 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:28:08] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:28:08] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:33:48.272036 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:33:48.272036 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:33:48.272036 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:33:48.272036 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:33:48.272036 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 14:34:16.865222 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 14:34:16.866211 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 14:34:16.866211 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 14:34:16.866211 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 14:34:16.866211 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 14:35:36.807481 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:35:36.811815 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:35:36] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:35:36] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:36:44.229123 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:36:44] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 14:36:44.441478 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:36:44.442960 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:36:44.443964 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:36:44] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:36:44] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:36:44] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:04.361771 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:04.364772 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:04.368769 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:04.371770 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:04] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:04] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:04] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:04] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:05.429290 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:05.432290 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:05] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:05] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:16.633613 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:16.636701 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:16] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:16] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.697146 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:48.699146 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.707147 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:48.710146 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.719658 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.764657 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:48.766657 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:48.770658 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:48.774656 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.779657 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.785656 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:48.790658 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.797678 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.805677 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.810677 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:48.817980 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:48.820946 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:48] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:49] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:50] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:51.639536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:51.643534 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:51.647554 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:51.652536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:51.659577 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:51.665561 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:51.675664 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:51.682723 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:51.687745 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:51] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:53.388924 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:53.391074 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:53.395050 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:53.400050 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:37:53.403052 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:53] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:37:53.409058 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:53] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:53] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:53] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:53] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:37:54] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:38:03.468822 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:38:03] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 14:38:03.842758 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:38:03.844779 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:38:03.850302 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:38:03] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:38:03] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:38:03] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:06.072235 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:06.075236 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:06] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:06] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:24.510252 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.515759 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.517765 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.519766 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:24.533034 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:24.572032 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.574034 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.577033 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.579034 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.586033 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.590036 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:24.604041 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:24.609554 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:24] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:29.258078 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:29.261080 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:29.265079 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:29.268080 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:29.274078 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:29.276081 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:29] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:29] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:29] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:30] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:30] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:30] "POST /myclass/api/Get_Statgaire_List_Partner_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:33.738947 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:33.741915 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:33.745915 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:33.750914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:33] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:33] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:33] "POST /myclass/api/Get_Inscrit_List_EU/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:33] "POST /myclass/api/Get_Inscrit_List_EU_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:34.676833 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:34.680831 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:34.684334 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:34.686341 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:34] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:34.696342 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:34.696342 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:34] "POST /myclass/api/GetAttendeeDetail_perSession/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:34] "POST /myclass/api/getRecodedStagiaireImage_from_front/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:34.710340 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:34] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:34] "POST /myclass/api/Get_List_Jury_Soutenenace_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:34] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:34] "POST /myclass/api/Get_List_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:39:36.776444 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:39:36.780467 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:36] "POST /myclass/api/Get_Inscrit_List_EU_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:39:36] "POST /myclass/api/Get_Inscrit_List_EU/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:40:48.500664 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:40:48] "POST /myclass/api/Add_Update_UE_Jury_Observation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:40:48.635090 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:40:48] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:03.905021 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:03.907021 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:03.912021 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:03.916021 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:03] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:03] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:03] "POST /myclass/api/Get_List_Jury/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:04] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:11.282543 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:11] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class_From_Session_Id/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:23.015580 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:23] "POST /myclass/api/Add_Jury/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:23.122135 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:23] "POST /myclass/api/Get_List_Jury/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:24.813398 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:24.814401 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:24.819402 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:24] "POST /myclass/api/Get_Given_Jury_With_Members/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:24] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class_From_Session_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:24] "POST /myclass/api/Get_List_Jury_Soutenenace/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:37.763450 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:37] "POST /myclass/api/Update_Jury/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:37.860896 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:37.862896 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:37.865897 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:37] "POST /myclass/api/Get_List_Jury_Soutenenace/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:37] "POST /myclass/api/Get_Given_Jury_With_Members/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:37] "POST /myclass/api/Get_List_Jury/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:44.369479 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:44] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:47.987124 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:47] "POST /myclass/api/Get_Insription_From_Session_id_Reduice_Fields_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:50.365596 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:50] "POST /myclass/api/Add_Update_Apprenant_To_Jury/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:50.461466 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:50.462466 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:50] "POST /myclass/api/Get_Given_Jury_Apprenant_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:50] "POST /myclass/api/Get_List_Jury_Soutenenace/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:53.915944 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:53.919946 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:53.923942 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:53] "POST /myclass/api/Get_Given_Jury_Soutenenace/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:53] "POST /myclass/api/Get_Given_Jury_Apprenant_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:53] "POST /myclass/api/Get_Insription_From_Session_id_Reduice_Fields_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:56.671723 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:56] "POST /myclass/api/Get_Given_SessionFormation_From_Id/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:56.769168 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:56.772197 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:56.775171 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:56.779171 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:41:56.785171 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:56] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:41:56.792177 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:56] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:56] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:56] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:56] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:41:57] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:42:30.427721 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:30] "POST /myclass/api/Add_Update_Inscrit_Juy_Promo_Decision/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:42:30.496236 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:30] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 14:42:34.986054 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:42:34.990057 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:42:34.993576 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:35] "POST /myclass/api/Get_Given_Jury_With_Members/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:35] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class_From_Session_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:35] "POST /myclass/api/Get_List_Jury_Soutenenace/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:42:42.972063 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:42] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 14:42:43.606266 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:42:43.606266 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:42:43.612286 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:42:43.620272 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:42:43.622865 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 14:42:43.626848 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:43] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:43] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:43] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:43] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:43] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 14:42:45] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:31:35.251040 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:35] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:31:35.445455 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:35.446454 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:35.450958 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:35] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:35] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:35] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 16:31:43.458688 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:43.462688 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:43.465689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:43.470702 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:43.476688 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:43.482687 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:31:43.488695 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:31:43.494695 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:31:43.503204 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:43] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:31:45.447545 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:45.447545 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:45.450544 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:45.455546 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:45.458546 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:31:45.463061 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:45] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:45] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:45] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:45] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:45] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:31:46] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:32:43.321316 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:32:43.321316 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:32:43.322315 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:32:43.322315 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:32:43.322315 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:33:17.662721 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:17.665736 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:17.669720 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:17.674757 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:17.677719 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:33:17.689719 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:33:17.695725 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:17.705236 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:33:17.717244 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:17] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:33:20.017155 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:20.020152 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:20.024171 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:33:20.029154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:20] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 16:33:20.034154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:20] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:20] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 16:33:20.044154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:20] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:20] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:33:22] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:35:17.673990 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:17.678007 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:17.680989 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:17.686038 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:17] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:35:17.691524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:17] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:17] "POST /myclass/api/Get_List_Groupe_Inscrit_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:17] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:35:20.169918 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:20.172929 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:20.176928 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:20.180929 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:20.185926 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:20] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 16:35:20.192994 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:20] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:20] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:20] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:20] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:21] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:35:34.897875 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:35] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:35:35.103126 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:35.106127 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:35:35.110166 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:35] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:35] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:35:35] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:36:09.150912 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:36:09.151916 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:36:09.151916 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:36:09.151916 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:36:09.151916 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:37:19.043430 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:37:19.043430 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:37:19.043430 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:37:19.043430 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:37:19.043430 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:37:19.103733 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:19] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:37:19.276986 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:37:19.278989 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:37:19.278989 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:19] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:19] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:19] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 16:37:28.466367 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:28] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:37:28.846798 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:37:28.847829 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:37:28.850812 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:28] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:28] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:37:28] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:48:02.756376 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:48:02.757376 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:48:02.757376 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:48:02.757376 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:48:02.757376 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:48:35.775028 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:48:36] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:48:36.173299 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:48:36.175297 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:48:36.180299 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:48:36] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:48:36] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:48:36] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:49:58.069624 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:49:58.069624 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:49:58.069624 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:49:58.069624 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:49:58.069624 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:50:21.835972 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:50:21.836971 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:50:21.836971 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:50:21.836971 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:50:21.836971 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:50:26.035444 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:26] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:50:26.496657 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:50:26.501650 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:50:26.509740 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:26] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:26] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:26] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:50:48.775324 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:50:48.776326 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:50:48.776326 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:50:48.776326 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:50:48.776326 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:50:53.778559 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:54] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:50:54.156944 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:50:54.158944 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:50:54.160944 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:54] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:54] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:50:54] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:51:37.720014 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:51:37.721001 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:51:37.721001 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:51:37.721001 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:51:37.721001 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:52:34.204438 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:34] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:34.671716 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:34.674716 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:34.675725 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:34] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:34] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:34] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:52.297153 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:52] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:54.026720 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:54.670911 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:54.673913 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:54.676418 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:54.681644 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:54.686687 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:54.693655 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:54] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:54] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:54] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:54] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:55] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.393278 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.395273 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.397272 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.402606 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.412606 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.470642 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.472643 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.476642 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.479642 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.485155 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.490155 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.499154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.504154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.511156 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:52:58.516154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.520154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:52:58.521154 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:58] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:59] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:52:59] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:53:02.953133 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:02.956129 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:02.957170 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:02.965132 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:02] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:53:02.973130 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:02.979137 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:02] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:53:02.985135 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:02] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:02] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:02] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:53:02.995679 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:03.000666 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:03] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:03] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:03] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:03] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:53:05.429004 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:05.432006 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:05.435035 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:05.439004 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:05.442006 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:05.445006 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:05] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:05] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:05] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:05] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:05] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:06] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:53:50.967309 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:53:50.967309 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:53:50.967309 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:53:50.967309 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:53:50.967309 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:53:55.461847 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:55] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:53:55.933077 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:55.935077 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:53:55.945083 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:55] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:56] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:53:56] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:55:23.474487 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:55:23.474487 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:55:23.474487 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:55:23.474487 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:55:23.474487 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:55:44.074185 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:55:44.074185 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:55:44.074185 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:55:44.074185 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:55:44.074185 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:56:48.340770 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:56:48.340770 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:56:48.340770 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:56:48.340770 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:56:48.340770 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:56:48.399282 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:56:48] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:56:54.031858 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:56:54.036860 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:56:54.039859 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:56:54.046861 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:56:54.057857 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:56:54] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 16:56:54.069857 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:56:54] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:56:54] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:56:54] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:56:54] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:56:55] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:57:06.610519 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:06] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:57:07.157054 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:07.159071 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:07.164071 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:07.168059 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:07.172055 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:07.175473 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:07] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:07] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:07] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:07] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:07] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:08] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 16:57:12.372281 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:14.449080 : Cacul_Session_Note_Finale_For_calcul_Stanard -'rang' - Line : 2913 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:14] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:57:14.496373 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:14.497372 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:57:14.501373 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:14] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:14] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:57:14] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:58:37.029647 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:58:37.029647 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:58:37.029647 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:58:37.029647 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:58:37.029647 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:59:04.750702 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:59:04.750702 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:59:04.750702 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:59:04.750702 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:59:04.750702 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 16:59:28.854261 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 16:59:28.854261 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 16:59:28.854261 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 16:59:28.854261 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 16:59:28.854261 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 16:59:31.758899 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:59:32] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 16:59:32.024266 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:59:32.027267 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 16:59:32.034275 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:59:32] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:59:32] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 16:59:32] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:01:16.969366 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:01:16.970365 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:01:16.970365 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:01:16.970365 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:01:16.970365 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 17:01:20.901681 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:22] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:22.551708 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:22.555885 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:22.558888 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:22] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:22] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:22] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.615372 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.617373 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.620372 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.622372 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.635374 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.679817 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.681816 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.683815 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.687818 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.691816 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.696815 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.703816 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.707814 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.712814 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:01:28.717816 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.719815 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:01:28.725816 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:28] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:29] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:01:29] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:02:05.448072 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:02:05.448072 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:02:05.448072 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:02:05.448072 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:02:05.448072 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:02:17.363154 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:02:17.363154 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:02:17.363154 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:02:17.363154 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:02:17.363154 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:03:00.346081 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:03:00.346081 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:03:00.346081 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:03:00.347076 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:03:00.347076 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:03:25.514017 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:03:25.515522 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:03:25.515522 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:03:25.515522 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:03:25.515522 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:03:40.019207 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:03:40.019207 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:03:40.019207 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:03:40.019207 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:03:40.019207 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:03:58.218990 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:03:58.218990 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:03:58.218990 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:03:58.218990 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:03:58.218990 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 17:04:20.464195 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:20.470192 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:20.474196 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:20.478191 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:20.482193 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:20.485199 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:20.488201 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:20.495201 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:04:20.506716 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/Get_List_UE_Given_SessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:20] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:04:22.437113 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:22.439172 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:22.443155 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:22.448156 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:22.453660 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:22.454667 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:22] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:22] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:22] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:22] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:22] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:23] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-08 17:04:23.762481 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:24] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 17:04:24.107762 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:24.111764 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:04:24.117763 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:24] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:24] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:04:24] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:05:30.085838 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:05:30.085838 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:05:30.085838 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:05:30.085838 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:05:30.085838 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 17:05:36.709485 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:05:37] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 17:05:37.191638 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:05:37.193656 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:05:37.195679 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:05:37] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:05:37] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:05:37] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:06:11.286638 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:06:11.286638 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:06:11.286638 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:06:11.286638 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:06:11.286638 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 17:06:12.877855 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:06:13] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 17:06:13.242433 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:06:13.245445 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:06:13.249429 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:06:13] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:06:13] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:06:13] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:07:18.301431 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:07:18.301431 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:07:18.301431 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:07:18.301431 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:07:18.301431 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 17:07:30.420279 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:07:30] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 17:07:30.694477 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:07:30.696466 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:07:30.700450 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:07:30] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:07:30] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:07:30] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:08:41.755105 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:08:41.755105 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:08:41.755105 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:08:41.755105 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:08:41.755105 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 17:08:41.814829 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:08:41] "POST /myclass/api/Calcul_Note_Classement_Session HTTP/1.1" 200 - +INFO:root:2025-11-08 17:08:41.998710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:08:42.003743 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-08 17:08:42.005750 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:08:42] "POST /myclass/api/Get_List_Evaluation_UE_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:08:42] "POST /myclass/api/Get_List_Evaluation_Final_Note_Classement_Detail_With_Filter HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:08:42] "POST /myclass/api/Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:09:08.585356 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:09:08.585356 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:09:08.585356 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:09:08.585356 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:09:08.585356 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-08 17:09:51.018931 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-08 17:09:51.018931 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-08 17:09:51.019931 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-08 17:09:51.019931 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-08 17:09:51.019931 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-08 17:09:51.204182 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 5   part 5
Né(e) le
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION212.6711.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION212.6711.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION212.6711.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION212.6711.41  
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Note générale  

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RangMoy. ElValidéObservation
212.67
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Imprimé le : 08/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
212.67
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Imprimé le : 08/11/2025  

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\n

Note générale  

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RangMoy. ElValidéObservation
212.67
\n

 

\n

Imprimé le : 08/11/2025  

\n

 

\n

Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
212.67
\n

 

\n

Imprimé le : 08/11/2025  

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width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col widths: ['10%', '10%', '10%', '70%'] +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +INFO:werkzeug:127.0.0.1 - - [08/Nov/2025 17:09:53] "GET /myclass/api/Prepare_and_Send_Inscrit_Bulletin_Note_By_PDF/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/690f3a7c995b26cde9611a4b HTTP/1.1" 200 - +INFO:root:2025-11-09 09:36:29.963032 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 09:36:29] "POST /myclass/api/Get_Personnalisable_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-09 09:36:29.967015 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 09:36:29] "POST /myclass/api/Get_List_Partner_Document_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 09:36:36.691269 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 09:36:36] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 09:36:38.024945 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 09:36:38.028946 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 09:36:38] "POST /myclass/api/Get_Given_Partner_Document/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 09:36:38] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 09:36:48.547750 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 09:36:48] "POST /myclass/api/Get_Given_Personnalisable_Fields_By_template_ref_interne/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 09:43:04.090653 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 09:43:04.090653 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 09:43:04.090653 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 09:43:04.090653 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 09:43:04.090653 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 09:44:15.814239 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 09:44:15.814239 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 09:44:15.814239 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 09:44:15.814239 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 09:44:15.815237 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 09:44:37.570542 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 09:44:37.570542 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 09:44:37.570542 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 09:44:37.570542 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 09:44:37.570542 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 09:45:01.462005 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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\n

Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
\n\n\n\n\n\n\n\n\n

part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Bulletin_Note_part nom 1_part 1_526.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
\n\n\n\n\n\n\n\n\n

part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Bulletin_Note_part nom 1_part 1_902.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
\n\n\n\n\n\n\n\n\n

part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Bulletin_Note_part nom 1_part 1_087.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 09:55:08.921832 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 09:55:08.921832 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 09:55:15.558994 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM 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(unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+INFO:root:2025-11-09 09:56:30.768920 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 09:56:30.768920 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 09:59:48.457853 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 09:59:48.458856 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 09:59:48.458856 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 09:59:48.458856 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 09:59:48.458856 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:00:26.809786 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:00:26.809786 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:00:26.809786 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:00:26.809786 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:00:26.809786 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:00:47.461287 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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\n

Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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\n

Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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\n

Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:06:29.408035 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:06:29.408035 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:06:29.408035 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:06:29.408035 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:06:29.408035 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:07:06.249130 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:07:06.250131 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:07:06.250131 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:07:06.250131 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:07:06.250131 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:07:36.121110 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:07:36.121110 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:07:36.121110 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:07:36.121110 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:07:36.121110 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:07:41.005295 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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\n

Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
\n\n\n\n\n\n\n\n\n

part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Bulletin_Note_part nom 1_part 1_491.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
\n\n\n\n\n\n\n\n\n

part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Bulletin_Note_part nom 1_part 1_218.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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0RhuKMU/Zqs5woAbCtKhprveBAHIQQQGjEdhNo44S15MLyMfCwfVuRhT0EydN0YcEVHPLYVJKLESJ5v9wzEYLueXZKvhVCEXveRMAeA/Px8bN68qU1BVgDgt99O4bffTjcKI9we9Ho9fvzxx1Z5tIvFYjz99LN47733MHLkyGaF+Z1apkwmw7Jly7Fly1b07t2n4TeJxAzLlz+NTz/9PwwdOqxTNd/W1gnRvR3ISSAQYOLESQgPH2ky7ZUrl3DixIk29aOioiJ8++23JpdGxGIxFi5cBDc39/taPjGB3laTBsehl42hx7yCCIVqZbufq+J12F6cgoomBu/nrJ0RZPNfr1pbkRmed/ZtZFrhAeytK8dNRXmXdpRJPTzxumsgHJvMxOtBWFt0E6cr8rrNSe5mXSUO1hSj6RRmtJkVJrn4QMgO2+g0wbNnzx5kZma0fXIoFGLjxg0oLi7uUBkKCgpw8OCPrcrv6aefxcqVK9u8vUwkEmHkyJF4//0P4OPjCx8fH3z++edYvXp1qxy/7mfs7e2xbNkyk+vDHCfA9u2RyM3NbXXf++mnn5CUlGgy7ahRYzB27Nj7vi2YQG8HjhJzND2NRglCja793q+xNSU4r6oxuD7LxbeRQxcHYJyzF3ybrJcrQDhQnNqlWrKQ4/CYey8ssHOHWWMFHtm8DmtzopFW1/UBOAjAn5X5KDTyrk+5+MNFYsE6aSeRkpKCPXu+b7emePNmEg4fPtyhEKDR0dFITU0xmW7WrNl49tlnTWrlzQscDqGhofjiiw2IjPwOERFTWhURjQEMGTIU06fPMNlPUlKSceTIEeh0OpPPzMrKwu7du0xq9NbWNli0aCHs7Ozu+3ZgAr0daHjeqJBpr26qIx67i1INDkSZa2GHUCOmY0exBZ519DTIf0d1IdK7OHqZrVCM1Z4DMNnC1qDzXNCq8K+s6yju4m10PBHO1hSj6fTJSyjBKAcpBGDaeWeg1WoRGbkNJSUd07A3bfoKOTk57fs2dDqcP3/epLm7Rw8nLF68uMN7jzmOQ79+/eDl5cWOVG0DVlZWmDdvvkmnL4FAgG3bvjVp8eF5Hvv27WuVZSgiIgJDhgxljcAEevuo1KjQ1JvVHByshe3bKpGsqMBxheG+2kecvI2e7iXkODzo4gP7JuvZubweJ0symvFT7zxczSzxludABIvMDETnobpybM6L7ZT1/ObIV9chpd7wCMiJFrZwkJizDtpJXL58Gfv37+vwc8rLy7B3795WaWVNKSsra5Uz3oIFCxEQEMga7S4SHByMJ56Yb1KjLikpxt69P7QYEjYxMQH79v1gMs8ePZywcOGidltlWp7cARUV5Q2n8rX3Lz8/v83+J+2Febm3VTsnHtdrDDUWO04At3Zs3eJB+LEkDalNBOAEiSVG9fBo9j5vSzu8aNsTa+/w8tYD2FKehWluAW0Kj9vmjg4g1NYZa2XBWJ59HcX035VzFYDPy7PhZW6LJ9x6dcladrlGiXwjE4Yhtq7d7mnf9rr7e2h9tbW1iIzc1qqDSYjIpDa7Y8d2TJ48GSEhIW0uhylzOxFhxIgRXb7Hl9EyYrEYjzzyCH7++RiysjJbtILs3r0LERERGDBggMHvarUae/bsQVFRocl+9cQTT6BPnz5d861yAqxY8Qr0el2HnuPr64fffjvTJZOObhPoZdp6FKg7LwCDABxczCzuujk1X1WLPYoSg+v9Le1bfVb2nWQpa7C/qgAcGpvspzvIWlwLFnMCTHf1x9rqgkbRJG7yOpwty8Z8Wd8uNu1wmOTkhdWqGrxSnNKo9BVE+KgwCd4Wdhjp0PlepyX1ChQZrJ8T3Mys7+0Rjwjf5NyAo7DzYuALOQGe9Q2DuJPPqb969QqOHv3J4Azxpnh5eWPgwIE4cGAfWtqDXVtbi507d6J3795tOme8oCAfdXUKWFg0P1kOCuqNgIAAJlHvAXx9fTFv3jy8++6/W0ynUNRix47vEBQUBAuLxuNcVFQUDh48aFKYe3v7YPbsR7t0371QKOzwRFEg6L6JZhcJdA4v5dyAGdd5Fd1LZIadfSbAWnj3NLA6vQ4bc2OR3WTGZgbgIXt3CNvxvqfLshHbZLvbEJEEU1x8TdeJTQ88Y9UDXynKGq5pAewsy0SEqx96iLt2RigRCLBQGoQMVQ2+qCls9FuiXot3c6KwwcwS/padG0zB6Bo9ocsOPelEiY73aks69Ym9OQGepsGdOxkvK8WGDRtMCnOe57F8+XIMGzYcly5dQn5+y+cPHD16BFOnTsXo0aNbXZbS0lKIRC1/84GBgd2i/TBaI7wEeOihh/Dzzz8jKup6i2mPHTuGGTNmYNSo//aHuro67N69GzU11Sb3tS9duhRyuZxVeiNFq4vI0muRrFN32l+9TtPla8MtoeJ12J2fgA3VBYZailCM0T082mw7KFTXYUd5lsF9D9r2hIeRuO1NsRCIMMvFz3CSoFHiXHlOt9SLg8gMKzxDEWFuWN5f1XX4JCcaFdrOjX1dayTMKzgOTmLmkdxReJ7HkSNHceWK6UAeffr0xcSJk+Dj49OqEKB1dQps2vQVampa77hZV6cEZ2Ki7OHh2Satn9G1uLm5Y9GiRRCLW7ZE1dersG3bNigU/z2O+dKlizh27IjJvhQWNgSTJ0d0W1S8+16g/69AADJU1ViXcRUri5JhTDStdPGDczuOiv29PBfntapG05QAgRCzXP1bPTkYaN8Ts80ar5frAPxYkoG6Dq79tBZPCxu86dEffY2Ent1eU4xv8+I71UnO+EE4BP09HoTj70BOTg42bfrKpJlQr9fjqaeegouLMziOw4wZM+DhYTqi1p9/XsCxY8da//21ok27y+GI0XrGjh2HkSNNB5v5/fffce7cWQBAVdWtMwBMOU9yHLB8+VPsKNv7UaDzAIo0KmTXK1r9l1VfizhFOc5X5OHTzGuYm3QGaytyUGvEQjDD3AaP9AyAoI3OX1VaNXaUZRg0xmRrZwRZt/54RjuRGR4zYp7fVV+Nq910aAsHYJi9G/4h7Qf3JtqUGsDHZRk4UprZaSfS2TSz7FKkVbEvugPodDrs378fhYUFJtOOGzce48aNx+11czc3NyxfvtykZkVE+Pbbb02a529jbW1lMkpYfn4etFota8B7CDs7Oyxa9KTJbYQajRqRkZEoLS3F6dOncfbsGZP9Z8qUhzBixAhWyUbosgXpXgIRLDrRw9lGKGqXh3AdgBezrqKtxth6AHVEBpHbGmnHIjO84z0Yju1Yu71YVYCjTbZeuXIcHnX1b7Nn+IgeHphQlIyTTQTajyXpGNFDDjHX9fM2DsBUFx8kq6rwUWkmFHfUWwnxeCcvDr4Wtgi1delwXs05lZVq6u/tr43jsKdnENwknXeQjYDjIOoks2NycjK2bv26VWkXL17SaM8xx3GYPDkC33+/2+TRqTdvJuHAgR/xwgsvmJwAODk5Q6fTtWi+TU6+CY1Gw9bR7zHCw8MxderD2Lv3+xbTXblyGXv2fI9ffvnFZH+QSCRYsmQpbGxsWAV3hUAnMrayTXjPMxQDjIRIbb8pgYNlO7wFedw66rOzCROZ4VOvQejbjndU6nU4VGoYMGGUhR0G2bm2+XkuEgtMdZDiZElaYy29rhxP1pQitB3PbA8WAiGelwcjW1WL7YpS3Kkzxes1eCv7Or70D4dnB7fUuZlbw47jUN1I4+eQV19zj39uHAY7yuBzDx65Wl9fj61bv4ZSaXpnyvTpMzB0qGEgjx49euDZZ5/Ds88+Y2Jew+Hbb7di8uTJ8Pf3bzGtVCqFlZUVeL75iXViYgJSUlIwaNAgNqLfS8JFJMKCBQtw8uSvqKgob1GGfPLJxyaXV4h4LFiwEH379u22dxCLxR32cpdIJN0WpKjDAp3jjOvNPcUW8DL/35xFPW5hj1Weoehv69KuTXQxNSXYcodneoNA5ATYXZDUrmdW67V/6cl3bh/j8WNJGvrZukDUTR3KXmSGVV4DkJb6B8422bb4s6oGn+VE49++Q2HdgaNebSSWcOMEqCZ9IwvB77UlWKjXwkbIHKTayqVLl3DkyE8m092KCDbPYKvR7bFg7NhxGDduPE6f/q3F55SXl+O777bj7bf/0eLZ1dbW1vD19W9xLzrHCXDu3DmEhoayvej3GL1798YTTzyBL75Yb1IxNIVM5oE5c+Z0WzheIsLbb/8Dw4cP75gyKhB2m9MmCyzTBgaIzPCUkzcecQtAD3H74oVriceh0nSjv0XWVSCyrqJTy7y9uhCLlFXw7UatMNDSHv/2GIDF6ReR2sQj/bOqAnjlJ+IZWT9I2mkqlptbw0tsgZtqxR02IeB4fS1K1UrYWLKYzm1BoVDgq6++bDFy153aef/+oS0K/KVLl+G33061qJVwHIcdO77DlClTjWr7t3F2dkb//v1NBpfZtWsnHnroIbYf/R5DKBRi9uxHceTIT8jKyurQs5544gn4+3df+xIRpFLZ3yoCIfNybyUPmtvgcNB4LPUIbrcwB26Fed1eXdRt5c7l9ThSkt5pDmmtZZi9G95072PUj2JdSSpOdWBbnaVQhCFGHAdreT1Ol2d3+7v+3fn1119x5cplk+lcXFzxxBPzWtSoAWDgwIGYOXOWyefxPI9vv/3G4AzyRhqHSISRI0eZPNylrKwU33yzFXV1HQ9mFR8fh+zsbNYxOgkPDw8sWbKsQ7sR+vULxrRp05kF5n7X0C0BvO3iB3+L1mlt5eo6PFV00+B6oroOefW1kFm0fxlBT4QjJekope7dZrOlIhdz3YPQ08yq2/IUchxmu/ohS1WNf5VnGUwy3smNgZu5Nbza4SDGAZjg6IGvKnJQcofw5gB8VZqBSc7eXRr69n+JwsJCbN68uRWnoXGYO/cxBAUFmXymhYUF5s+fj6NHfzLpfX78+M945JFZmDRpUosTBF9fvxbDiQLA3r170LNnTzz33PMmJx3NER0djVdfXQWxWIznn38BEydONBnYhmFCaxQIEBERgUOHDuL69WttF1KiW2edy2QyVpn3u4YuBjDWQYZHXP1a9bdI3g9rHQ1jqOcQj49ybqCyA0FS8uoV2FmVj+7eNZuk1+BUaVarwvLwnRi+x1IownMewVhiZahNX9fV44PsKOS3MzxwiK0zhjbZf08AonRqHCpOY3vSW8mBAweQlJTQKi1rzpw5rdaQgoODMW/eApNroxzHYePGDSgvb95pSiaT4eGHp5l0LOJ5Hhs3bsTGjRtRU9M2B0mdToerV6/i7bffQnLyTcTHx2HlyhVYv/5zlJSUsI7SQZydnbFs2fJ23Tt06FBMmDCBnX7HNPS2I+EEWCbrhzO1pTjTZBvYr2oFduTH4wWvgW12XCMQfi5JQ3qTMK/2nADP2Uth2UkhbXkiHKkpwhVt4y1cm8rSMa2nH2xELTuUEBE685w0J7EFVnsNRGrKeZy/o0x6AD8qKyHKiQLa4QZoLRTjmZ6BOJd1DdVNpiAflaShv7UTwnvIOz3yv5Z4XKjIx0A7V9iIJH/rvp6eno6dO78zbRHhOCxevKRNGpJEIsHjjz+OI0d+QllZaYtpY2KicfToUcyfP99o5C+O4/DYY3Px88/HkJaW2uKzNBo11q//DElJiVi+/CmEhIS06JDE8zyqqqqwb98+fPnlRlRW/teHpa5OgfXrP8fVq1fx+utr0K9fPxaZrAOEh4cjImJqqyLB/dfaY4nFixfDwcGBVSAT6O2jp7k1Vkv74M+sa40iwykBbCjLxHB7KQbZ92zTM0s19dhZnm0QaW6JjQve9A2DWScF8CcCfPMTsbAgvtG2sQsaFc6X52KKq1+L9ws5rtM7hb+VA972CMXTmVeRfoeTnB7AHmVVu587zFGGCSVp2K+sbHQ9n3isybmBrebWCLRy6DShXqfXYnNuHD4uTcc8O3e87TMYtn9Toa7T6bBz5w7k5+ebHFz9/PwxderUNmtIgYGBWLhwIT755OMW7yUibNr0FcaNG9dsbG53dymWLFmKN99cY3ItVq/X45dfjuPcuXOYOHEiJk16EL17B8HVtScEAgGICDU1NcjNzcWff17A/v37kZubY/S5PM/jwoU/MG/eE1iz5g1Mnz4dlpaWbJBsB7a2tliwYAHOnTuLujpFq+6ZNGkShg+/O0FkOI5DcXERQsOCJAAAIABJREFU0tPTO+2Zjo6OXTo5YQK9GcY4eeHVqkK8W9U42loqr8enuTHYaOUAhzbEDj9dloUYXVMvYg6PuPrDojOP/OSAsc5e8ClORnITa8Dm4hSMdfKEZYvburrGrDXaUYZVymq8XpSEmjtiF3TEMG4rkuBptyCcybiIiibxEC5qVXg+9QI+8QlDSDu3F95JmUaFT7Ki8FFVPgDCF1V50GcQ3vEJ+1tq6lFRUdi1a6dJIc1xHJ555lk4O7cvpsTMmY/g4MGDyMhoeVDMz8/DgQP78eKLLxoNO8txHKZMmYITJ34xGU3sNiqVEocPH8JPPx2GSCSCubk5HB0doVSqUF1dDb1e1wrfgVtUV1dhzZrVuHEjCq+/vgY9evRgg2Q7GDhwIB599FF8++03Jvuera0dnnxy8V2bQHEch7fffqvTrDJEwLp1n2LGjBldVmZmP2oGM4EQS2T9MExkZiAMvldVYV9BEvhWiqNqnQbfl2agrkn6+Zb27QpMYwpniSWecjDUdH6vr8W1qqK7Up9iToD57kF42l6KztqRyQEY7SjFuy4BBi3BA/hNU4elaX/idFk26tsZS17D3zKxP3vzLD6qymuYgqgBbKjKx/sZV6DQ/73CjtbV1WH79kjU15uOrDd06HA88MAD7V6/lMvlmD9/fqvu3759O5KSkpr93d7eHmvWvIGgoN5tHEgJWq0WtbW1yM7ORmlpCTQadauF+Z3PsbOzYxHpOjKumplhzpy5kEpNL988/vjj6Nev310tr16vh1ar7aQ/TZeXlwn0FvCytMNb0r6wbCLSOQCfl6Yjprp1zjIXK/NxSmPo/DXXxQ82os4POCDkOEzr6Q+XJjPLKgB7SlKh4fV3pT6thCI85xGCKZ14nKqIE2CerA9W2bkZ/f26To0HMi7jzZQ/EFdT2upDYlS8HimKCnyYcRnh6Rew30gUOi2AWr0WujbsWrgX3HouXryIQ4cOtkKA8XjmmWcahXhtDw899DD69DEd3au8vAzffvst1OrmHU979eqFd95ZC0fH7tWQiQhTpz6E55573mR8ckbLBAYG4rHHHmsxjUwmw5w5c9gOg7aOh6wKWma8szeWV+bh/2qK//txA0jkdfg8NxbrrUa3uI5ap9dhb3EalE22V0VIrDDEwb3Lyi23sMXTtm5Y22TJ4KiiDE8ryhHcCTHV21UuM2v8y3MgclP/wDVd5xyrai0UY4XXQBSmXsCuJuvpt1vs05oi7FKUYpalA8LtpRhg6wJzkQSWQjEshUKoeR4qvQ4KrQpRNaU4W5mHSGUl1H8Ja2O2mNfspVjjPRj2RhwNtc0I+cNlWXCuLu6SunU2s8TEHh4tpqmsrMTWrVtb5a0+bdoMDBkypMPlcnFxwZIlS7Fq1QqTWvGxY0cxffqMZk/q4jgOYWFh+PjjT/DWW2+26iCZjsLzPGbOfARvv/02c87qDIVDKMSMGTNx/PhxJCYmGKlvPZYsWQovL29WWUygd7KJSCDEsx79cT7pDK7rG5tMtisrMKrwJhbK+jV7oEpibSl+UFU1ES/AbCdv9BB3nelOzAkw1cXXQKDnEuHHolT064R15fbS16YH3pKH4Jns6yjsJGuBm5kV1vmHQ559Ax9WGT/Jq5jXY6OiDBsVZbAVCOEjEMFdIIQ9J0Qd8SgjPa7rNKhvhcb9vpMPnvfo36yFxeiBOMTjleKULqvX52x7tijQeZ7H8ePH8ccf502uCwoEHBYsWGg0xGt7mDRpEvbsGYzLl1s+Z12pVCIychsGDBjQrCYsEAgwfvx4ODk54R//eBsxMdFd9x2JxViwYCFeeOFFODo6sgGxsyb2cjkWLVqEN95YY3BcamjoQEyd+hALItMOmMm9Ffha2uNVtyDYGjG9v1ucglSF8T20WuKxvzgNyiYCYoTIDOOcPLq83H1snLHU0nAQ+qGmECmKirvY6ThEOHniTRd/dKa7i6uZJV73GYwNroFw4wQtTlhqeD2idWr8rFFit7oWhzV1uKCtNynMewnF2O8xAC97hnbJcklHMDVBKygowMaNG0wKcyLC44/PR0hISKeVzdraGs8993yrYlqfOnUSp06dNDHhEKB///744osvMGPGzC4xzbq5ueOTTz7FqlWvMmHe2X2V4zBx4iQMHhxm0PeWLVsGV1dXVklMoHfdQPlwTz8ssnGBsImmncnr8Un2Daj0OoP7UhQV2FFraF59xEHeLZHMLIUizHU1PM0qidfjRFnmXa1TMSfAPPcgLLbr3GUHO5EET3uEYL/fCCy0doJrJwWjkHECvGjnhoO9xmBmT39YCP9exi29Xo+DB39Ebq7pkLv29g54/PHHOv0QjGHDhv11hjpMTii2bt2K4uJik0LBy8sb7733PjZt2oIRI8I75RAMe3sHLFiwELt27cb06dPZmnkX4ejoiMWLl9zhZEiYNOlBjB49hlUOE+jNDA6d9BwLgQjPe4Sgt5EtX7uUFThUlNIoxhoPwvHSTAOTcm+BCBEu3bc2NNDBDbPMbQ2u76/IRV694q62jZ1IglWe/THF3KZT20zIcRju4I5NvcZgl/cQPGZhD6927vPvLRDhFTs3HPAPx8cB4ehl5Qjub9jX09LSsGXLllvHHbfwx/N6LFiwsM2e5K3BzMwMy5cvh0QiMVmOqKhrOHLkp1adwmVtbY0JEyZg06bN+Oyz9Rg9egxsbe1aHTuciCAUChEY2AvPP/8Cdu/ejbff/gf8/Py6NDrZrfrmm/2jLoh2SIQW8+xIvPX2EB4ejgkTJt5SQCytsGDBQtjZdd/hSqbqorP/upoOqxm2IjMscZA3GkwIBEdx92/tcBSbY4W91EgZO2efsK+VPd6Th+BsVaHBbzGqakzUqhvWxau1GlQQb1AeuZk1/Cy7z7HGXmSGBa4BkFcXNhJEBCBNWQWZuXXjwVEkwQJHeaMDTngQLLtor7WnuQ0+8h6CvnesLXMAHDqh/5gJhBjv5IlwRxmSFRW4VF2IazUlSNHUIUWvRSHPAw2BeDmAE6CPQIheQglk5jYYZ++OXjbO8LO0g6CNA7uVxByrHeXoTr92XwvbZgVHcXExli9/yrTlRCzCjBkzu2z9sn//UHzwwUcoKjK9fVIgEKKurg7W1tamrWgcBzs7Ozz00EOYOHEi0tLSEBcXhytXrqCgIB95eXmoqalGfX09hEIhrKys4eTkDC8vT3h7e2PkyFHw8/ODs7Nzt4QYFYlEeOONNw3Wjxu/vwBOTk6dluft6H3Tpk1r2Rolk3VbRDwrKyssXrwEp0//hhkzZiIsLKzbvpeIiAgMGzasW2VUr169uvT5HBELes24f9AToUSrQq1WDZ1OC9xeM+cE4AQCmIskcJJYsDPV/4dQKBSorKyERqOBXq8Hx3EQiUSwtLSEk5MTc766y+h0Oqxfvx4TJ05A3779WIUwgc5gMBiMvyu1tbWwsrJisfKZQGcwGAwGg8GmQwwGg8FgMIHOYDAYDAaDCXQGg8FgMBhMoDMYDAaDwWACncFgMBgMJtAZDAaDwWAwgc5gMBgMBoMJdAaDwWAwGEygMxgMBoPBBDqDwWAwGAwm0BkMBoPBYDCBzmAwGAwGwxARqwLG/QARQaVSged5mJmZQSxmx6MyGIz2odfrUV9fDwAwNze/Z47gZRo6475AoVDgrbfewpNPLsKNGzdYhTAYjHbB8zyOH/8ZTz/9FNat+6RBsDOBzmB0EzU1Nfj552O4cSMK7u5urELu0DTy8/PATlFmMFpHQkIC/vnPf0Kr1WHRoidhZWXFBDqD0Z2kp6ehvLwUwcEhsLOzZxUCIDn5Jj788ANs3rwZPM+zCmEwTFBYWIj3338PcrkcH3zwATw8PO6p8jGBzrgvyM7OgZmZOQYOHAQLCwtWIQAOHTqEr776EsHBwRAI2FDAYLREfX09Nm3ahIqKCnz00Ufw9va+58rInOIY//Oo1WrEx8eBiODv7w+RqPXdnogamaNNCb4707dXSLYlzzvTcRzX6F6O48BxnNH0CoUCN2/ehFgshlQqa/Tb7XuM/Z+IjD73Tg3f2O/tLa+xe1tTnq56bnO09f1bWz9tKWNb3rm179KZfa8tfd1UPbVU562pY2PlNHWfXq/HrFmzsHjxYsjl8ja9W3dNmJlAZ9wHAr0eUVFRUKvr4ePj0+pBLTs7G9euXcOVK5dRUVEBBwdHjB49GsOGDYOTk5NB+sTEBJw+fQapqSkQiyUYP34cRo8eA2tr61blqdfrkZ6ejtjY2L/yrISjowPGjBmLsLAwgzwBYNu2bSgpKcaMGTNRX3/rPePj4/6yRgzE2LFj4ejo2JD+woULOH/+HOrqlLh27Rp4nsePPx7AmTOnAQDTpk1Dnz59UVZWhm+//QZCoRDLly9HYmISzpw5jczMTDz77HMICQkBEaGkpARxcXE4f/48iouLYW5uhpCQEISHj4S/v7/B4BgVdR3nzp3HgAGh8PHxxcmTJxEdHQ2VSgl/f3+MHj0GgwcPNvAa1ul02LRpE+rqFJg9+1FoNBqcPXsGsbGxePDBB/Hww9MAAEqlEjdu3MCFCxeQnp4OgYBD7959MGrUKPTp08dgMpebm4vvvtsOHx9fPPDAA7h27RpiYmKQn58HPz8/hIeHIySkv9FJIM/zKCwsxLVr1xAVdR25ubmwsrLGyJEjER4eDjc3t0bvX1paiu+++w48r8eyZcthb2+49BMfH4ejR4/C3d0dCxYsBMdxqK6uxtdfbwERYdmyZUhPT8eZM2eQlpaGxYsXY/DgMOTkZOP48V8QHx8HgEN4eDjGjx8PZ2fnVk8i8/Pzcf36NVy9eg1FRUWwtrbCyJGjEBYWBplMZjDBOH78Z0RHR2PKlCmwsbHFpUuXEB8fB41Gg5CQ/hgzZozBfXdOsuPi4nD16lUkJyejqqoK7u5ueOCBCRg8eDB++ukwSkpKMXXqVPj7+zfKNy8vr6GcxcVFsLa2xogR4Rg9ejREIhG+++47mJubY8GCBbC0tGy4T6FQIDo6GteuXUVmZiYUCgV8fHwxadIk9OnTG9u2RYKIx9y5jzX61nQ6HZKTkxEVFYUbN26gsrIC7u5SjB49GuHh4Q153Eaj0SAq6jr++OMPJCenQCp1x/jxD2DYsGFtUibaqw0wGP/TpKSkkFTqRoMHD6KSkhKT6Wtra2nz5s00YEAoeXjIKCDAn0JDQ8jDQ0YeHjKaNGkixcREN6TneZ6OHz9OgYEB5OPjTWFhgykgwI+8vDzotddeo6qqKpN5VldX0+bNm6hfv74kk7lTYGAAhYQEk6ennDw95TR16lSKj49vdE9lZSVNnTqFAgL86MknF1FAgD/5+nqTn58vSaVu5OEho2nTHqasrKyGe/bu3Uu+vt7k5eVJcrmUPD3l5OfnQ35+PhQWNohSUlKIiOj69etkZ2dBU6dG0CuvvEy+vt7k5uZKvXsHUWpqCmm1Wjp16hRNmjSRPDxk5O3tSaGh/cnHx5tkMnfq3TuIjhz5ifR6fUPeOp2O1q1bRzKZO82YMZ3CwgaRXC6lwMAAksulJJO5k5+fL3300UekUCgavWtWVhYNHTqEQkP707/+9U8KCupF7u6u5OhoS6dOnSSe5ykhIYFmz55F3t5e5OXlQSEhwdSrVwDJZO4UEOBPn376KdXX1zd67qFDh8jV1Ynmzp1LU6ZEkIeHjAID/cnDQ0YymTv5+/vS5s2bSaPRNLpPpVLRd99tp8GDB5JcLiUfHy8KDu5L3t636nX06FF06dIl4nm+4Z7Y2Fjy9/elmTNnGDzvNl999SXJZO60cePGhnsTExPJxkZCEydOoFWrVpKfnw+5ublSYKA/xcXF0qVLl2jQoIHk6Smn/v1DqG/fPuThIaO5c+dQbm6uyb6nUqlo//79NHJkOMnlUvL19aaQkGDy8vIguVxKI0YMp7Nnz9Adr0I8z9Py5cvI01NOS5YspuDgfuTl5UEBAX4kk7mTXC6l4cOH0dWrVxvlxfM8ZWdn0TPPPEN+fj4klbqRp6ec/P1v9VkvLw+aO3cOjRgxnAIDAyg7O7tROX/4YS+Fh48guVxKHh5SCgrqRV5eHiSTudPYsWNo7dq15OrqTMuXL6O6ujoiItLr9XT9+jWaNu1h8vLyJKnUjXx8vBry9/f3pWXLlpK3txfNmDGdysvLG/IsLS2ld9/9N/Xu3euv79KfgoP7NXw7Tz75ZKPvS6vV0ubNm8nPz4f8/f0oLGwweXl5kI+PF61bt460Wm2XjnVMoDP+5zlx4gS5u/ekpUuXGAiKptTV1dHatWtJLpdSRMRk+u677yguLo6Sk5PpwoULtHz5cpJK3WjatGlUXV1NREQVFRU0YEAo9evXh44fP07p6el05cqVv4TWYDp79qxJYf7GG2+QTOZO06Y9TPv376f4+Hi6efMm/f777zR//nySy6U0f/78hjyJiJKSkqhv3z4kl0tp/PhxFBkZSbGxMRQbG0s//LCXhg8fTnK5lNaseZ10Oh0RERUUFFBcXBz961//JKnUjd566y2Kjo6m2NhYSkhIaBB427dHkru7K8lk7jRp0gT6+ustdOnSJfr999+pqqqKDh48SAEB/jRo0EBat24d3bgRRSkpKXTjxg368MMPycvLgwIDAygmJqahvBqNhubMeZTkcin5+/vRq6+uovPnz1N8fBxFRUXRhx9+QIGBAeTu3pP27t3bqI4uX75M3t5eJJdLaejQIfTRRx/RH3/8QefPn6eysjKKioqioUOHkJ+fD61cuZIuXvyTbt68SfHx8bR161YaNGggeXl50KFDBxsJ2c8//4xkMnfy8JDRiy++QOfOnaP4+Di6evUqrVmzhmQyd/L0lNOVK5cb7qmvr6fPP/+M5HIpjRo1krZs2ULR0dGUlJRE165doxUrVpCnpwc98MD4RgJ1z5495O7ek955551GE507hd0rr7xM3t6edP78uYbr+/fvJze3W20xbtxY+vLLL+nixYv0+++/U35+Ps2dO4fkcint2rWTkpOTKTExkZYvX0aBgf4UGRnZYt+rr6+nDRs2kIeHjEaODKetW7dSTEw03bx5k6KiomjNmtcb8s3JyWm4r6qqiiZOnEByuZQGDhxAX3zxBV2/fp3i4uLoxIkTNHPmDJLLpTRz5kyqrKxsuC8jI4MiIiaTVOpGDz44iXbu3EFXr16luLhYOnfuHL344ovk4SEjuVxKY8eOaeiPKpWKPv10HXl4yCgoKJA++OB9unTpEiUkJFBUVBT93/99SgMG9G+YGH711ZcN7Xzp0kUKDu5HMpk7zZ8/nw4ePEg3btyg2NhYOnr0KD3++OMkl0tJLpfS6tWvNdxXUlJCS5YsJrlcSnPmPEpHjhyhuLg4unnzJp09e5Zmz55FMpk7rVy5oqGcSUlJJJO508SJE+j8+XOUnp5OJ0/+SoMHD6LRo0dRXFwcE+gMRnvR6/W0adMmkkrd6LPPPjOZft++fSSVutHcuXMazbxvU15eTk888QTJ5TLat+8H4nmeoqOjycNDRkuWLG40YUhMTKSUlBSjg/edg/jWrV+TXC6lBQsWNNJI7tQSpk6dQq6uznT48OGG67/+emuiMnPmDKMDxZEjP5G/vy8NGjSQioqK7tCUtfTPf/6DpFI3OnbsmMF9Op2O1q5dSzKZOz399NONBvJbmmYM9enTm8LCBtOZM6cbCcjbgvv9998jqdSNVq9e3TDYFRcXN2iQBw4cIJVKZZDv999/Tx4eMho/fhwVFBQ0/BYZuY1kMnd68MFJFB0d3ahOi4qKaPr0aeTj4027d+8itVpt8E6HDx8iLy8PmjDhgQaLiUKhoMWLnyR3d1fauHGjwWSvtraWli9fRjKZO23Zspl4niee5+nEiRPk4+NNERGTKS4u1iAvhUJBS5cuJXf3nrR58+aG6++88w7J5VI6evSo0b5QUlJCERGTqU+foAZLiV6vp//7v09JJnOnJUsWU0ZGRqP6rq6uosBAf+rXr2+jNs7JyaHo6OhmLQG3+95vv51qsDrduHHD6Lu89tqrJJW60fr16xuux8fHU9++fWjo0CF04cIFgz4QFxdHAwcOoMBAf4qKiiIiIqVSSS+//BLJZO60evVrlJeXZ5CfWq2mf/97LUmlbvTmm2+QVqslnufp119/JblcSmFhg+nkyZMGbazX6+nChQvUr18fcnbuQadOnSIiosLCwgYr0rp164xayyoqKmju3Lnk7t6Tdu3a1fC8zz//jKRSN3r55ZeorKzM4L60tDQaM2Y0+fh40aVLF4mI6JdffiGp1I0++OD9RmmjoqIoOzu7xbGgM2CurYz/aTQaDa5duwatVgMfn5a9UsvLyxEZuQ1isRivvLICnp6eBmkcHR0xZsxo6PU6XL58BTzPw83NDebm5rh+/ToSExMbnHWCgoLg7+/fokNMSUkJvvnmGzg5OWPVqlVGt8E4OTnh0UfnQCKRICYmuuF6TEwMBAIBHn/8CfTt29fgvgEDBkIu94BSqURZWWnD9ZqaWsTExAAgo/nV1NTg2rWr4Hkezz//fCMHII1Gg71796KiohzPP/88xowZa7BGKhaLMXPmI6isLMTJkyegVqsBAJmZGaipqUZYWBgiIiJgbm7e6D6hUIjJkyfDy8sbMTE3EBsb2/BbQkICRCIRXnzxJYSEhDSq099+O4XLly/h0UcfxSOPzIJEIjF4p2HDhsPfPxD5+fnIyclpWG+/dOkSevRwwpw5cwz2E1tbW2P06NHgeR75+QXQ6XRQq9XYuvVrCAQCrFy5En379jPIy8rKCrNnz4JIJEJ8fDx0Oh1qamqQnJwMsVjSbByEysoKZGVlQSaTQyaTNZTx4sWL0Om0ePHFl+Dt7d2ovgUCIfz8/FFSUoQLFy5Ar9cDAORyOUJCQlqMiKjRaPDNN9+A4zi88sor6N+/v9F3mThx4l/r+/FQKusAAEVFRaiursIDD9xaG27aB273faVS2RB4JS4uDt9/vwseHp545plnIZVKDfKTSCSwt3cAAISGhkIkEkGpVGLjxg3geR4vvPAixo0bZ9DGAoEAffv2hYODI4RCAXr16gUA+OOP35GUlIixY8dh2bJlsLOzM8jT1tYWYrHoL3+L3gCArKwsREZGwsnJGa+88gp69OhhcJ+vry9GjBgBrVaLxMREEBEcHBzA8zx+//13pKenN6QNDQ2Fh4dHlzvHMac4xv809fX1iI6+AUtLKwQG9moxbVpaGi5e/AO2tvbYt28fjh49YiQVh5SUZAgEAiQl3RLePXr0wBtvvIk1a1bj2WefwcqVKxERMQW2trYmy5eSkoKiokJYWVljx47vDITcbW4PDpWVldDptOB5QlpaOiQSCWQyqdF7BAIOAoEAYrEYFhaWjQR2XFwsvL19jXrr1tTUIDY2Br169WoQLLdRKGpx7NgxCAQCnDt3HqmpaQAMg9IoFHXo0UOK/Pw8qFQq2NraIj+/ABqNBoGBgc2+p6WlJYYPH4HU1BQUFRUBAKqqqpCamgorKyuDSZZWq8Xly5chEomQkZGJd9/9d7NOjqWlJairq0NtbS0AIDs7G0VFBZg5cxYsLMybqUMhAIKdnR2EQiGSk5ORmJgIgHDo0CGcPXvW6H35+fkgArKzs1BdXYW6OiVSUpLh4OBgdKJ4u40rK8sxZcqUBoGlUCgQExONwMAgowLQysoKzz33PJYvX4o1a15HYWEh5syZY9SBsinZ2dmIiooCxwlw7NjPuHDhgtF0hYVF4DgOCQnxqKtTwtLSCteuXf1r0jjAqNPb7X4nkUgaHMESExMgEokxe/ajzXqJ19fXIzk5GRzHoWdPt7/uS0RsbCyGDBmKyZMnNysUq6urkZSUgCFDhjU4qp05cwYcx2HWrNmwsbExel9tbS3S0tIgk3k0OCpevXoVhYX5cHR0wqZNmyESCY2OBdeuXWuYrBARgoODsXjxEkRGbsOzzz6Dl156GePHj4eZmRnzcmcwOkpWVhZKSorRu3cfODg4tJg2MzMTZmYW4HkeBw7sazGtWCyBg4MjOI6DUCjEo4/OgUgkxtq1/8Krr67CyZMn8eqrryEwMLDFrTfZ2dl/aXDV2L+/5TxFIjGEQhE4ToCysmKkpqbA2toGMpnxwbGmphbFxUVwcXGFi4tLo0lETU01pk59yOhAk5KSAqWyDqGhAwwEb1lZOYqKCiAWS3D69KlWlFcIiUQCnudx+fIl8DyPgQMHmahbMQBqGETLysqQnZ0NV9eeBoKgqqqqYbJz5colXL16uYUnc5BIxBAIuIb2Njc3R0hI/0YTnjs9qktKigFwkEqlEAgEqK6uhkJRC57nm5nw3fn+IlhaWkIkEiMvLxd5eTl48MEIWFsbFyxJSTchFIowaNDgBqGVnp6G6upqTJr0oIE3NXBri9WECROwefPXWLv2Hbz//rs4ffo3vPzyywgPH9li3ysqKkJ9veqOdyET/d0BQqEQGo0GyckpsLCwaHZyUlFRgaKiYtjZ2cPBwQFarRZZWdkg4iGTyZoVyrW1tUhMTICFhQV8fX0bnqXTaREQEGBUU75NamoKRCIxBg0aBFtbW9TV1aGwsBDm5uaQSt2bvS8nJwdVVZUYNGgw3NxuTSIKCvIhEolRV6fAnj27Tfbz2+UyNzfHypWrYG/vgA0b1uOpp5ZizpzHsGLFSri7uzOBzmB0hIKCAhAR+vbta3SbUFNtj+M4PPLIbKxevdqo6bbpYHp7e5WFhQUee+wx9O/fH5s3b8Lhw4eRkZGBr7/+Gn5+/kbvJyKo1bfMkXPnPo7XX3/d5PsIhUIIhUKUl5cjIyMdAwcOanZrUmZmJioqyjF27LhGwXSysrIgFkswYMAAo5pydnY2RCIxgoODDQS+Wq0Gx3Hw8/PH119/DUfHHibLbGdnB51Oh5iYGNjbO7Q4sOl0OkRH34BOp4OX160lkry8PJSWFhvdIqTT6aBQKCASibB79x7RMj2ZAAAgAElEQVQEBgaaLI+lpeVfZtIE6PV6eHp6GhV8t7bARUOjUTcsTRAReJ7HkCFD8dVXm0weysFxHGxsbJCamgqOEyAkpL/Re9RqNdLT0yEUiuDhIW8oT25uLgQCAYKCgpoNiCQSiTB58mQEBwdj584d+Prrr/HKK69g/fr1GD58RLNl43k9iAijRo3BJ5980qr+bmNjg8LCQqSnp8HOzh5ubsbbsqSkBEVFhfD29oZUKgXHcTAzk0AgEECpVDabR0VFBWJibmDSpMkN5vHb6VuqayJCTk4OOI6DTCaDUCiEWCyGWCyGVquFRqNp9t68vDzU1dXB09Ozob/rdDoAwGuvrcbcuY+Z3FMvFAobJikODg54+eWXMXJkOD799FP88MNeZGVlYdOmza2ynDCBzmAYQa/XIyYmBjyvh6+vr8kT1pycekCn0+LmzSRYWlo2a6IzZs4VCAQQCATo06cPPvjgQ7i5uePLLzdg586d+Mc//mlUI+E4Dl5et9ZECwryYWVlZXJQvU1iYiLU6noMGDCw2YEuMTEBHCdopPHV19cjISEBOp3WqHalUqkQExMNrVYDDw/D393d3WFuboEbN66CCCatHv8dNHNRUlICb29v9OzZs9lB+fz584iLi8WQIcMQEBAAAEhIiAeARu9x52TB398fmZkZqKysbHV5FAoFrl+/DqFQ2OwkQKVSITo6Cu7u0ob4BRYWFjA3t0BVVRV0Ol2rB+jy8goIhUK4uroaba+KinLEx8fBwsK8YQKo0Whw48attvD29mm2790OjiKTyfDqq6/By8sbb7zxOj7//HMMHhzWbL93dHSERCJBamoKVCoVXF1dW/ku5cjPz0NY2JBmJ5O3td6goAiYmZlBIBDAyckZt5asUqBWq41ah65fvw6JRIJRo0Y1TDatrKz++kYKoFQqjVoqNBoNrl+/jvp6JYKCggDcWo93de0JrVaLmJhYhIUNMRDMer0eFy/+CZ7nERIS0nDd1tYORDxSU9NgZWXVapO5Xq+HUCiESCRCWNgQfPnlV1izZg1OnDiOkyd/xWOPPd6lYx5zimP8Twv0qKjr0Ot5BAX1Npk+NHQA/P0DER8fh2PHjkGr1RrVAhQKRcP/4+Li8OWXG1FSUtKQzsrKChERERCLxUhISGjx4JOAgAC4urri/PlzOHHiF4OY6jzPIyMjw+BEp4yMW9pcSEiIUQGh0WiQnp4OkUgEX1+fhoFMrVYjLS0VSmV1wxplU00xKioKjo494OfnZ/C7lZUVpk+fCWtrO2zfHom6ujqjA35hYWET824xqqqqoFarUVtba1AnPM8jOTkZ//nPR9Dr9Zg79zE4OztDp9MhLS0NIpEYvr6+BgOypaUlBg0aDL1ej02bvmpYd2/6Tv/f3nlHx1Vdi/u700fSqGtmNCpWteUqG4MLmGLAlICBAAmmOLz3CxB4TkKABMgjgVASQhJqEpKQAAYC5NEMxhhsggFj44JxxUWWbFnF6l1TNeX8/pA8nhmNpJFkmZLzrWXW4mpuOefuu/c5++y9T2VlZdg929ra+OKLnUyePDWs8E4ohw5VcvhwLdOnzwgakaKiIoqKiigr28fy5cuDM7lIV3ZbW1vYseTkZAIBP9u3b+83W/T5fGzYsJEDB8qZPHlKsBCR1+tl69bPSU5OCSuuckT2amtrWbp0aVjwlVqtZt68U8jMtNHQ0NjvOUIpLh7PxImTqK2t4a233ooq7w0NDTQ3N/cbKLpcLkpLpw/oOj8S0Dhz5szgOzvttNNIT8/gueeeZfny5djtdrxeL16vF7vdzooVK3j00UdQFBVW69GiPIWFhZhMibz//mo2bdrYT3b8fj979uzhk08+ITc3n3Hj8oJ/u+SSSzAa43j66adZu3Ytbrc7OGNvbW3l6aef5rXXXiM+PoHi4vHB8+bOnYtWq2P58rf4/PPPo8prZWVl8LvsHRhs4E9/+mPQo6AoCmlpaVxxxRUEAoHgOvtYov7Vr371K6n6Jd9EmpubeeKJxxGi16DX19ezf//+fv8qKyuxWq2kpKRgMBh4//3VrF+/Ho1Gg9VqRQhBe3s7q1at4qc/vZWGhkbmzJmDoij85S9/6fuIXZSUlKAoCnZ7NytXvsvatR9z8cWXMG/evAFddiaTCY1Gy4cfrmHdunXExcWTkpIMKLS2trJixdvcdtutOBxOZs6ciUajoauri6VLn6WmppobbrghqmFubm7iqaeewu128z//syTovuzp6WHZsmW0tbWTk5NLTk4OXq8XlUqFRqOhoqKcJ554jFmzZnP55d/p55LXaDRkZGTw7rsr2bRpIx0dHVgsFnQ6HXa7nc8++4z777+fd99dybx584JejhUr3mbt2o9pbW1h48aNpKSkBF3xTU1NrFy5kjvu+BlVVYdYtOhKrr/+BvR6PS0tLfzjH3/H4XCyZMmSqFHKNpuNLVs+Z/v2bZSVlWGxWDGZTLjdbsrLy/nLX/7Cvffew+zZs4Pu/m3btvHqq69y1llnc/7534pawWvDho2sXr2KSy+9jNNOO63PbawnNTWFlStXsnHjRnw+LxaLBZVKRUdHO2vXfsIdd9zOvn1lzJ07Nziz8/v9vPnmm+zZs4eMjAxsNhter5eamhpeeulFHnjgPoQQLFp0FXPnzkWlUlFVVcUTTzzOpEmTueKKRf1mpsuXL+fuu39BRUUFU6dORa/X43K5WLNmDStXvsO0adP47nevGNCDo9FoSE1NY+XKd9i0aSM+n5+0tDQ0Gg12u51169bxs5/9lN27dzN79uzg/V9//XV27tzBdddd32+gcUTGXnzxn9TUVHPdddcHg/nS0tKIi4sLDl7Xrv2YgwcrWbv2Yx555BGeeeYfOBwOfD4fixcvJi8vL+iFAVi/fh2bNm0mOTmF1NRU/H4/9fX1LFu2jDvvvJ329nZmzpzJpZdeGpTbnJwcGhsbWL/+E95+ezmbN29m7959rF69igcffJAVK5bj9XpJTk7myiuvDK6FJycn43K52bRpAx999BFJSckkJycjhKClpYVXX32FW265GZMpkcmTJ+P1evnFL+7iX/96ORi8KYSgra2NpUuXsm/fXhYvXhw1K+KYIjOVJd9UNm3aKAoK8oPFJrKyMqP+u+qqq4I5yE6nUzzyyCMiJydLZGVlivT0ZFFcXCiyszOFzWYRJSXjxQMP3C+6u7uEEEJUVlaKSy65WNhsVlFQkCcWLrxQzJx5gsjMtIhFi64Iy6UeCLvdLv7whz8IiyVdZGVlitTURDF58kRhs1mEzWYVEyaMF48++kiwqExNTY2YMWO6OPHEE8KKdoSye/dukZeXKy66aGFYdbSenh7xxz8+IdLTk0VWVqZITo4XBQV5Yt++vUIIIVasWCFsNqt44IEHgsVoouWpr169Wpx44kyRlZUpzOY0UVRUIAoK8kRmpllYrRliyZIl4sCBA8F85yVL/kfk548T119/XV+VN6swm9PE1KmTRVaWta+dxeKhh34rWluP5vyWlZWJoqKCfu2I5LPPPhPnnLNA2GxWYbWaxbhxOWLSpBJhtWYIq9UsLrpoodi8eXMwl3zp0qV9eeJ/jXo9r9crHnjgfmGxZIg33ni939+WLl0qiot7q6KlpSWFvC+LyMnJErfffrtoa2sLy69+8MEHgzKXmWkREydOEOnpyeKUU04Wp512qsjOtonly5cHz1mz5oN+hYEi86d/8IMbhMWSIQoLC8S5554jzj77LJGdnSlOO+3UqHnl/d+lVzz//POipGSCyM7OFBkZKaKwME+MG5ctMjMtIjc3W/zv//5cNDU1BgvKLFq0SBQW5ocVDQrl8OHDYv78M8QJJ8zoJ/9ut1u8/PLL4sILLxAmk0YkJRlFamqiuOCCb4lnnnlaXHHFFcJqNQfzyENrMdx0043CbE4TWVmZwmrNEMXFhcJqzRCFhfli/vwzRHa2Tdx33339nqe9vV089tijYs6cWcJgQCQm6oXVmiEWL75GPPvss2L27FmitHSq2Lt3T7/z7rrrLmGzWfp0QUrfPc3CZrOKqVOniL///amgXO7atUvMn3+GsNksYtq0KeLiiy8SU6dOFhZLurj55h+HFYUaKxQh5EbIkm8m69Z9wqpVq4b8XXHxeL73ve+FzTB27drJO++sZNeuXTgcdtLTM5gxYwbz589n0qRJYWvdjY0NLFv2Jp99tpnGxkZyc3OZOnUql112GWZzbOuSHo+HTZs28emn69m5cyddXV1YLFamTJnCggULKCkpCc4i9+3bxz//+QJms5kbb7wp6rr7+vXreffdlRQXF3PNNYvDZmkOh4M1a9awd+9euru7MRj0/PSnP0Or1bJixdts3ryZ008/gwULFgwaN1BeXs4HH3zA1q2fU1dXh8lkYtKkyZx88snMnTs36Dru6OjgyisX0djYwEsv/Qu3283q1b3uU4/Hg9lsYcqUyZx++hmUlpaGzZY3b97E8uXLo7Yjmqv7/fffZ8uWLRw4UIFOp6O4uJhZs2Zz6qmnBiP9fT4fzz23lMrKSi666GJmzZrV71put5snn/wzbW1t/Nd//Xe/5Qe/38+uXbv6atFvo7m5GYvFQmlpKXPnnsyMGTP6zagdDgerV6/mo48+orx8P3l5+UyZMpkFC85h3brevOVrr72W4uLxCCFYvXoVn3yyjtmzZ7Nw4cKobW5vb+f999/nk0/WUlVVRWpqKtOnT2fhwoUUFhbFHAPS25bVbNu2nfb2NjIyzEyePIl5805lxowZwYC8xsZGnnqqd7vdW265NWpqZnV1Nf/4x99JTEziJz/5SVTvR0tLC21tbXR0dJCcnExqagpqtYZFi65g69YtvPvuKk488aSwczo7O1mz5gM+/PDDvowUPVOmTOGcc86ltbWVjz/+iPPOO5+zzz47anzGkaUQt9tNUlISGRkZNDc3s2jRFWg0Gv71r38FAzFD4yjWrl3L2rUfU1ZWht3eTVFRMVOmTOWMM86gqKgo2D4hBFVVVbz99tts3LiBjo4OiouL++rqnx1zfMdokAZd8o0lEPATCAwt3qHR6pFrmw6Hg0AggEajISEhYdAdnBwOB16vF71ej8FgGFERiUAggN1ux+/3o9VqgwFBkb85Egw1kIGL5TdH2njE/XrEUAkhgkF+seBwOOjp6UGtVhEXF99Pge/evZvvfvc75Obm8vrrbxAXF4cQgq6uLgKBwIDtHE47Io2xy+VCURTi4uKiDniOtFOtVg/4To/0zWC/EULQ3d2Nz+dDq9UOKiNHn8+Fy+VGr9cHjX60ew3nXbhcLjweDxqNmvj4hBHttBYICOz2bvx+PxqNhvj4+H73FUIEi9cMtNGIEAH8/gCKAmp17HHXW7du5bLLvk1qahrvvbdqwIC73ra6URQV8fG98ubz+YLPHaucALz11pvcfPOPOfHEk3jhhX8OmEng9XpxOp34/X6MRuOgWzAfkYkjvx2o5sJYIKPcJd9YVCo1oynMpNFooq7ZDjQoiHVXtcGfWTVkQZpYFHysBjlSKQ9HGR4hPj6+X5W1UOrr6+ns7OCEEy4JKkJFUWLq2+EMLI5gMBiGVKKxtDOWnbEURYmpgFD48/VGyg91r+G8i6GMTGyyN3RbFEUZsl8URYVGo+o3OFqx4m3Gjx9PScnEsHcaCATYt28fDz30W7xeL1deedWgs9lobdVoNP2ey+Vy8corr7BgwYJ+O9/19PTw2Wef8cgjvUF4V1yxaND+02q1w9IFw5UJadAlEsnXgq1bt6JSqZg9e86I9+iWfL3ZsuUz7rjjdpKTU5gzZw4nnTSLrKwsmpub2bZtG//+9/s0NjYwf/6ZLF68+JhsM/r228u59957eOGF55k9ezYzZ55IcnIyhw/XsmPHDt577z26u7u48sqruPDCC78R/Sxd7hKJZMzw+bzcdNNNfPTRh7z44stR16sl33x6C6v8lQ8++DdNTY1h6VuKopCRYWbhwoX84Ac3DlinYLhs376dJ598kg0bPqWzs6Of98NqzeTaa6/l6quvibnmhDToEonkPxaPx8POnTvx+31MnDgpZrel5JtHbx2HKqqqqqioqKCrq4vExCRycnIoLCxg3Li8ES35DIbf72ffvn3U1dVRWXkQp9NJamoa+fn55OfnYbNljfmGKdKgSyQSiUQiGRayUpxEIpFIJNKgSyQSiUQikQZdIpFIJBKJNOgSiUQikUikQZdIJBKJRBp0iUQikUgk0qBLJBKJRCKRBl0ikUgkEok06BKJRCKRSIMukUgkEolEGnSJRCKRSCTSoEskEolEIpEGXSKRSCQSadAlEolEIpFIgy6RSCQSiUQadIlEIpFIJNKgSyQSiUQiDbpEIpFIJBJp0CUSiUQikUiDLpFIJBKJRBp0iUQikUikQZdIJBKJRCINukQikUgkEmnQJRKJRCKRxILmy7hpm9dNvdtOmauT9h4XakVFgkZHviGBHEMiaTojakUZ8PweEeCgowN/wD/iZzCqteTHJxN6l2aPk6YeB4ijxyxGE+laQ/j9AwEqHO0IEeg9oECy1kiWIWHI+3oCfiocbWH3MGn15BgTw57FKwIcOAZtLIhPHvX7qnJ2Yvf1jPh8tUpFQVwKOpUKd8BPpaOdgBCjeyhFwWYwkaLVD/vUCkc7Hr8v7FiKzogthvd39N204w8Ewo5nGk2kRsjKUKzvqKelxxX8/3i1ltNSbOhU6pivYfd7aXLbEQzepwoKBkWFolKhV2tJ0RpQhrh2t6+HGlcX4sj7UsCsTyBDZxzyubp8PdQ4O8OOZejjMevjwo45/F6qnJ1H7zECUnVGMmN8f6G0e93UubpHJYpDvfcuXw/17m72Ojtp97oAhQSNFqsujmJjEsk6I4ZhvO8j19vlaKfb50EA8Wod4/Tx5Mclkaw1oB/G9SJlu9njpMzRTr3XSXePGxAYNXqy9fFMjE8lZRjPKxAccHbi8XmDxwxqDflxyagUZcjzy+xt+EJ0oFalpiA+BU3IuQI45OzEGaKjdGoNBXHJg9qRI5Q72ukJ0Qeh+ir0HrWubrq87pHPnhWF/PiUYb3rr7RB7/B5WNVUydKWA7zncfR1kxLSZTBZY+DyhHS+lVFAaaI5qmB2+Xq48cCnfOxxjPhZfmay8OuS09AqR1/axvZaLqreFva75fmzWJiRH6HkPEwuXwshAnS2IZG/j59HnsE05GBmyr4PIUR5/S51HLcWzg4TPoffy7UHN7DZbR9xG28zZfCHiWeO+r39q3YXd3YcHvH5J+niWDHpbMw6Iy1eN1eXf8K2UQwQjhj0jwtP5rTU7GGf+vChLfzV0RZ27Lvxqfx5/Kn9Bm/R+LjtMN+u3IQ9bLAlWJ0/hwUZeTE/R1OPizsqN7PeF6IkFBV7dWdSYkqLfcDl7uaEPR/QIwIx9Bug0rBAa+A0YwoXmAuZZEof0AAccnUxrewjCGnrdYkWfls4l7QhBlPVjnamln0Y8o3DmznTuThzQvjv3HbO2v8xDRGDrOHwkqWEK8eVDvu8HV3NzD+wPuwZh4fg3wUnc1Z6br+/OAM+3m06yKvNlfyfuzOqvrOptVwel8q5abmckpJNkkY34J2cAR//bj7ES80H+D9X5PV6rzlOrePbcSlclJ7HzGQbiYNcL3KStLOriTcaK1juaGG3zxOlTwRZah2XGlO41FzASck24tWDmxCfENxTtZWXupuDx2xqLf8qmMO8FNugvS6E4NaDG1npPjrgutSYxNMTzyQ5pF1+EeCx2p080VEXPJaoUvNG/mzOTMsZ/B4I7jy0hTdC9EGovgp9ltcayri1+cCIZXSqWsuKKeeSq48fMxt73FzujR4nP9u/nkWHd7IqaIiVCE2jsNvn4d6Ow8yuWMed+9dx0NkRdd6hQQFl5P9USnRdp4743UDCkBnxu7Webh6v3o7d7x2yLywRz64MMIrUjbaNI1ZS/ftlNM+hVY5tu1AUElFG3DpVlPu/4mxnWWMF/iFmiY09Lp6s34NdBPpdQxnmA33aVstWX09Q9kEBIXi7qYIAYlhvyBpr36FAwM/7Hge/7KjlhPK1/PrAJtoGmXlYIq7xj+5mXqzfizeWAUSkrEd5a4oCCaOUCWWEwqAoo5fFaPe2+708cnALl9fs4BV354D6rs7v44nuJi44tIUb9q5hU3tdVO9Vt9/LHyo/5+KabX3GnCgGV6HK7+Wx7ibOrNzMkn0fsamjnqHe0mG3nfvKNzCvfB0PdtaxOyiT/d/lYb+XP9qbmH9wE7eWfcyhCA9MVA9dxLutC/h4oGYH1e7uGM4N1z3qAZ4sUm93iQC/qt1BubNj2PfQKmOjB3WKMuZ29rgYdJffxy8PbuQfjpaQselQA1/BY92NPFi1FV8gwFedHuC5rgaer9+Hb7TuZMmXwh+bKyhztA8623i1YT/LXJ2j/yYCPl5pOYgrytfwUlcDDW7H8Wm0ENzfUcsvDmykO4bBaK9iEzzUfIBVLdXDHHj8Z+AXgmdqdvHL9uq+OWBsvOLu4mfVW2mJGFx5RYB/1OzinrYqlGHoln+6OvhV9TZaQ5Z0Itlnb+XG/Z/w687DeMRw9KzgKUcr3y/7mE/b64bdR6s93fyhajudo/XUDcK6Hie/q9pGm9fzHyN7x8XlvqWznlfsrWHHUlCYqDMyXp+ARwSodHdT5e+hPkRg81QafpQ9Fa1q6HGHCchV1DHP2kJd7ceKdiF4vLGciXEpzB+BK7j/JxNOPJD3JbcRwACMU1RoY3ySBEUdZg40itLr4Yg0mEBzhMJKRCFeiT7qP9bj3V2+Hv5yeDe/LZob1ZW4x97Kn1oOHpN77ehsYrW7K+rftvs8rG2rYZFt4oivn4FCiqKEyVAAcCFoFYJIFfdidxPnNFVySeb4mOSyLuDn14d3UhSXREl8yjGXsQwULMOQX/UxnP3kKwrxMc51vIh+krjP2c4TrZURcgwTtQZKDIkIBBVuOzU+D/UiwJGFhnhF4ee2yf3iE6qdXfym9SBKiE6IB6ZqjRTpE9ApCgc8Diq9LupFAG/Qi6hiibVkwHiHSlcXPzqwkX/3OPrNRFMVhSxFTZrWQADo9Lmp8vtpj9BKa3xueg59xpOaU5hqSh9WP7/Q3cDEhjJuzJoS03r6SPg/ewsT6vbwk9zSMdGH4xVVr8cxBhIVFWM9Rx9zg+4XgnfbaukKEwSF32dO5LuZEzD2rd35RIBd3a280VjOsq4GykSAe6wTmJyQHlWh+CIE6xR9PC9MPCvmDtMoqjF5wfsDPu6v2UGWIYHxcaMISBP92zhdH8/rJfPRxPjcY2XQC1VqXi6Zj00XF5sbSFFIUveueaVp9fyx6JSobsVDjjYur90e5lT7QUo2V5iLovq/hopXGAl/627grNZqLjbnhynqbr+XPx/eTVmMs9ihvom3WippHWS29XxLJReYCzHFuAYayZJEK/89bkaYBPlEgE6fh71dTfypqYKNvqNmvQt4sbmC8y2FMQdUbfS6ub9qK48Wn4xZaxy5qAuIDP1cnJTJXfknxTy/PZaBRo/ZpnLKMGIh4tXaMN30RWcjNRHBrHek5bEkd3pwoOgXgjJnOx+2VLO0rYrtfi+3JGczPy23nw7b2FFHS4iX0gjck57PDTmlwesFhKDc2cGqlkO83FbNLr+X7yfbOHeAdjj8Xu6t3MxHEcY8BYXz4pK5MXMi0xIzetsmeoN5N3fW81JjBW84Wgj1Y63zebiv8jP+OnE+acMICu0Ugocb91NkTGbBEGvdI8WO4I/NByiJS+bCjLwRTwNEn4cu8ujL409jnDExRs+WMmiMxNfCoAsEO93dYZ9lqdbAxZZCTCEfgkZRcVKShZmJZq60t7C6tZpLLcVRR94KfWvoocYLhTSNfsD16OPJhz0OnqjezgNFc0nW6Ed2EYV+M2ANKlI1hpg8FmOJGkjR6If18QaVkUrNjAFG8vFRXH65ujhmJmYct7Z5heCR+j2ckGgmty9qOoDgvZZDPNXdeEzucdDZwf91Hb2WHphvMPFeyJriux4727qaRhT0B5Cq1gafP5ITTBlMNZm5qvwTdgeOBqJt97qpdHUNa8b9qqOVaYf38JPc6SOOrFaUvnXMCDlJ1eq/FPlOVGtGJNtHNN4OVydhjmRFxTXWCWHKXKPAtIR0piakc7G5kFcaK7g6c0LUgUlnRPBvhqJwiWV8uHFQYHJCGpMS0rjUXMRz9Xu5LnvKgIP6T9pqecfZHvQOKIAJhfstxfx31hTiQj1UCmhVKs5My2VOso0ZNTu5r/kATSFa/TVPN5c1Vw7bq1QZ8PNg7Q4KjYkUxiWNyfusFQF+fXgXecZEpiakjVQdh0XWHyFZoxuFrBx7jotlcIvw0epOfw9Ob8+As7lppgx+mjcz5gjNryJ/7m5mad1eer4G6/+SCGXX4+Sl+n3Bd1fl6ubh+n3HaIALq1qrqAwxpFPVWn6bdxKlEYO/V5sq6BlF2uJgTEvM4Fvx4cqtQvhxD3O90Qv8vqWSt5sr5Xp63/v1RL4zEaC5xzmgociLS+L2/JlR014DCJyB8Oh/p4A6j33Q691TOIcsffQBnSvg5+mGMlpCZpwCuCU1h+9nTw035hHEqTVcl1vKjSlZ/b1KzQdpHWZalwA+6nHy2+qtwz53OPfY5HXzUPU2mgaJJ/gmMOYGXUEhN8IdJwJ+flm5mY3th49ZwEIwAvFLwhYxslYQPNRUwcdtNcdUzX0FHBDfAK0bPsgap6goVevCPoY/tVWxpasBrwjwUv0+NnnDFcG5UZSlLoYljpYeF8vba8N8L+clWpmSkMb1qeGpTy/am6mIIUp3pMRFzixE8D/hRiXC1Rgp660iwG/qvuCL7tYIY8SIs8G+XDFXRnGmQl7EUpQK+MWhLaxoPECjx8lwhvgqFBIjBnotCH5VtZW3Gito8jiHzMyIZL+9jU0hAwIFOFGj579sk2JautCr1NyUU8psdfiE690ee7++FXMAABcqSURBVL+6A9HIUFSoI9aTX+hu4YX6fUNmTgQzVIbAgEJ8xPf4oqONpw5/gfsYDpIVvloKecxd7ipF4VyThRe7m8LcUM8723m+Yh3n6U3Mj09joimdUlMGmYaEIdd+BaLf+nKd38urDeUxGbx5yZlk6hOOaTtPiUtmoi6Bh9qq8PSpxSYR4N6a7RTEJVE4zPV0IXrdv6E0+3t4rbEipgCgk5OsZI3BGjP0rn2903KI1Bg8KHnGJE5KNH8F51FHmajRc7V1Aotrd6CI3lXbwwE/T9TuYrHXw8NtVWG/X2IyMy/RwqrDu8KOxxKuuK6tlvdDZms2ReHijALUisK56XkkNR+gs0+ptQvBe82VlMSnHvOgIXfAT21EtH6WSoUmZBmsVw4FkdnhVyRn4exx8jd7S/DYNl8Pv636nCcmnB7M5ffFGDUdbQ19j7ub1xrLhxwMKyicl5ZLwjH05n3U1UhzDGbXqNJwdlpumBFUgBmmDNKaKmjte/oAsNrr4r3qLZxYb2RhfDpTEjM4wZRBuj6BhCFyuScmWqC5PGyg8ZHXxUfVW5lRt5sL4lIoTbIyM9GMWZ8wZG74ju5makLejQDON2XEvBYMYNHHc1myjU2th8LexsbOeqYnWQY9N1tr4O7UXO5tPOol6EHw+6YKJselcFZ67oAptxoltlmoW6XiWWsJd9Xvpa6vrQrwcOshpsSlstBcMKxASkF/fQwKK1urMHcPHT+SYzAxO8n69Q+KU4CzMvKY21zOWq874gNVeM9j5z2PHdoOUajWcaExiTNTx3Fyio30AaIzFZR+a+hbfB6uqNka05v5XHfqMTfoCYqaH2RPocxj5xVH76ccANb7PNx/6HP+UHxKTEVLQmfi2giB2+PzcGXNtph6/bPCk/sZ9EpnJ+4hineoVArF8SmD5rBXiQA31u0mlgTE35uLx8SgCwQVjo4hUxo1KhXFkWvCEQNGBYX5qdnc5Wjj123VweNvujpZW72V9r4PWQEma3T8IGsKdVFmIkOl/dj9Xt5sDR8cnGJIYkpfTEGOMZEbTGZ+39UQ/Ptz7TVcYZtI1jEsRuEK+Hm5bm9fsZOjTNboyYyQGeVI/mzIqx6nNbLAOp5dFZ/yacjg5E1XJ0XV2/l5/okYVZpej4UYesIbbQ39DVcHb1RvjUnWG5Osx9Sg39tRCx01Q/7uQl08J6dk9ZvVnpBk5bL4VJ5ytIZ7K1DY4nWzpe/66SoNF+hNLEjJZn5aDrYBBuAzksxcH5/B3x0t/f62zedhW1cDdNVjVmk4X2/irJQszk7PI3MAmamM4q4vTcgYlrFRgJMSzRhbDxHqu7LH4NJ2iwCXmwtp8br5feshnH2apE4EuLt2J1lGE5PiU6Oe2yNEzFUmv5WeR4ffyz2N5XT1hVd2CMG9dV+QazRxwjD0kkJ/fawCftiwLyY9eG9qHrMSLWMe43Vc0tbSdEYeK5jDzQc3stHrpmeALjvg9/K4vYXH7S2c27CX/82eximpOcMYScXwO2Xs1vnMOiN3586govwTPg+JIH7O0cr4w7u5LXf6l+oO/F3NDv7Z3TTob0rUOj4tvQBVTAFOSgy/GBsB9gvBbVWf8+EQLulzdXG8PPW8CK9P/2cyqNRcZ5vMp/ZWPuyL/PUA9SHuOYHCTy0TmGxK43AUgz7UGvLu7haedx6tSBUPLM4oCAaT6VVqFmbk8/uu+uAzlvu9rG+t5ju2icPqyR3uLpY17A8tSEgAQXWPk+32Ft52deAM+aMBuCY9f8jqb0d6YlJ8KndnTeX6qi3BiG4X8Nf2Worjkrk6ohrc8Zb143Fv1QDSHafWcE/BbFwVn/KqqwP3ANdvCfh5ztXBc64OTm7az83WiXzbWtzPQ5mg1nJvwSxcBzbwqrMdzwDXawq53pnNB/ihtYTzzYX9Bhz9iwgJsnTDz1LQa/TEKwquEDmq83rwBALohwjcNag03Jg9h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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
\n\n\n\n\n\n\n\n\n

part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Bulletin_Note_part nom 1_part 1_806.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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+INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:15:50.437645 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:15:50.437645 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:15:50.437645 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:15:50.437645 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:15:50.437645 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:15:59.367593 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:15:59.368598 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:15:59.368598 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:15:59.368598 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:15:59.368598 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:16:07.554523 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:17:42.434740 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:17:42.434740 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:17:42.434740 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:17:42.434740 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:17:42.434740 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:18:24.906683 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:18:24.906683 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:18:24.906683 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:18:24.906683 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:18:24.906683 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:19:14.133719 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:19:14.134720 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:19:14.134720 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:19:14.134720 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:19:14.134720 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:22:29.953155 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:22:29.954155 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:22:29.954155 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:22:29.954155 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:22:29.954155 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:23:33.256551 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:23:33.256551 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:23:33.256551 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:23:33.256551 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:23:33.256551 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:23:54.824760 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:23:54.825762 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:23:54.825762 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:23:54.825762 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:23:54.825762 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:26:25.309068 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:26:25.309068 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:26:25.309068 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:26:25.309068 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:26:25.309068 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:29:41.067727 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:29:41.068745 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:29:41.068745 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:29:41.068745 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:29:41.068745 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:29:41.133347 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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\n

Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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\n

Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:30:46.868585 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:30:46.868585 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:30:56.102758 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM 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(unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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0RhuKMU/Zqs5woAbCtKhprveBAHIQQQGjEdhNo44S15MLyMfCwfVuRhT0EydN0YcEVHPLYVJKLESJ5v9wzEYLueXZKvhVCEXveRMAeA/Px8bN68qU1BVgDgt99O4bffTjcKI9we9Ho9fvzxx1Z5tIvFYjz99LN47733MHLkyGaF+Z1apkwmw7Jly7Fly1b07t2n4TeJxAzLlz+NTz/9PwwdOqxTNd/W1gnRvR3ISSAQYOLESQgPH2ky7ZUrl3DixIk29aOioiJ8++23JpdGxGIxFi5cBDc39/taPjGB3laTBsehl42hx7yCCIVqZbufq+J12F6cgoomBu/nrJ0RZPNfr1pbkRmed/ZtZFrhAeytK8dNRXmXdpRJPTzxumsgHJvMxOtBWFt0E6cr8rrNSe5mXSUO1hSj6RRmtJkVJrn4QMgO2+g0wbNnzx5kZma0fXIoFGLjxg0oLi7uUBkKCgpw8OCPrcrv6aefxcqVK9u8vUwkEmHkyJF4//0P4OPjCx8fH3z++edYvXp1qxy/7mfs7e2xbNkyk+vDHCfA9u2RyM3NbXXf++mnn5CUlGgy7ahRYzB27Nj7vi2YQG8HjhJzND2NRglCja793q+xNSU4r6oxuD7LxbeRQxcHYJyzF3ybrJcrQDhQnNqlWrKQ4/CYey8ssHOHWWMFHtm8DmtzopFW1/UBOAjAn5X5KDTyrk+5+MNFYsE6aSeRkpKCPXu+b7emePNmEg4fPtyhEKDR0dFITU0xmW7WrNl49tlnTWrlzQscDqGhofjiiw2IjPwOERFTWhURjQEMGTIU06fPMNlPUlKSceTIEeh0OpPPzMrKwu7du0xq9NbWNli0aCHs7Ozu+3ZgAr0daHjeqJBpr26qIx67i1INDkSZa2GHUCOmY0exBZ519DTIf0d1IdK7OHqZrVCM1Z4DMNnC1qDzXNCq8K+s6yju4m10PBHO1hSj6fTJSyjBKAcpBGDaeWeg1WoRGbkNJSUd07A3bfoKOTk57fs2dDqcP3/epLm7Rw8nLF68uMN7jzmOQ79+/eDl5cWOVG0DVlZWmDdvvkmnL4FAgG3bvjVp8eF5Hvv27WuVZSgiIgJDhgxljcAEevuo1KjQ1JvVHByshe3bKpGsqMBxheG+2kecvI2e7iXkODzo4gP7JuvZubweJ0symvFT7zxczSzxludABIvMDETnobpybM6L7ZT1/ObIV9chpd7wCMiJFrZwkJizDtpJXL58Gfv37+vwc8rLy7B3795WaWVNKSsra5Uz3oIFCxEQEMga7S4SHByMJ56Yb1KjLikpxt69P7QYEjYxMQH79v1gMs8ePZywcOGidltlWp7cARUV5Q2n8rX3Lz8/v83+J+2Febm3VTsnHtdrDDUWO04At3Zs3eJB+LEkDalNBOAEiSVG9fBo9j5vSzu8aNsTa+/w8tYD2FKehWluAW0Kj9vmjg4g1NYZa2XBWJ59HcX035VzFYDPy7PhZW6LJ9x6dcladrlGiXwjE4Yhtq7d7mnf9rr7e2h9tbW1iIzc1qqDSYjIpDa7Y8d2TJ48GSEhIW0uhylzOxFhxIgRXb7Hl9EyYrEYjzzyCH7++RiysjJbtILs3r0LERERGDBggMHvarUae/bsQVFRocl+9cQTT6BPnz5d861yAqxY8Qr0el2HnuPr64fffjvTJZOObhPoZdp6FKg7LwCDABxczCzuujk1X1WLPYoSg+v9Le1bfVb2nWQpa7C/qgAcGpvspzvIWlwLFnMCTHf1x9rqgkbRJG7yOpwty8Z8Wd8uNu1wmOTkhdWqGrxSnNKo9BVE+KgwCd4Wdhjp0PlepyX1ChQZrJ8T3Mys7+0Rjwjf5NyAo7DzYuALOQGe9Q2DuJPPqb969QqOHv3J4Azxpnh5eWPgwIE4cGAfWtqDXVtbi507d6J3795tOme8oCAfdXUKWFg0P1kOCuqNgIAAJlHvAXx9fTFv3jy8++6/W0ynUNRix47vEBQUBAuLxuNcVFQUDh48aFKYe3v7YPbsR7t0371QKOzwRFEg6L6JZhcJdA4v5dyAGdd5Fd1LZIadfSbAWnj3NLA6vQ4bc2OR3WTGZgbgIXt3CNvxvqfLshHbZLvbEJEEU1x8TdeJTQ88Y9UDXynKGq5pAewsy0SEqx96iLt2RigRCLBQGoQMVQ2+qCls9FuiXot3c6KwwcwS/padG0zB6Bo9ocsOPelEiY73aks69Ym9OQGepsGdOxkvK8WGDRtMCnOe57F8+XIMGzYcly5dQn5+y+cPHD16BFOnTsXo0aNbXZbS0lKIRC1/84GBgd2i/TBaI7wEeOihh/Dzzz8jKup6i2mPHTuGGTNmYNSo//aHuro67N69GzU11Sb3tS9duhRyuZxVeiNFq4vI0muRrFN32l+9TtPla8MtoeJ12J2fgA3VBYZailCM0T082mw7KFTXYUd5lsF9D9r2hIeRuO1NsRCIMMvFz3CSoFHiXHlOt9SLg8gMKzxDEWFuWN5f1XX4JCcaFdrOjX1dayTMKzgOTmLmkdxReJ7HkSNHceWK6UAeffr0xcSJk+Dj49OqEKB1dQps2vQVampa77hZV6cEZ2Ki7OHh2Satn9G1uLm5Y9GiRRCLW7ZE1dersG3bNigU/z2O+dKlizh27IjJvhQWNgSTJ0d0W1S8+16g/69AADJU1ViXcRUri5JhTDStdPGDczuOiv29PBfntapG05QAgRCzXP1bPTkYaN8Ts80ar5frAPxYkoG6Dq79tBZPCxu86dEffY2Ent1eU4xv8+I71UnO+EE4BP09HoTj70BOTg42bfrKpJlQr9fjqaeegouLMziOw4wZM+DhYTqi1p9/XsCxY8da//21ok27y+GI0XrGjh2HkSNNB5v5/fffce7cWQBAVdWtMwBMOU9yHLB8+VPsKNv7UaDzAIo0KmTXK1r9l1VfizhFOc5X5OHTzGuYm3QGaytyUGvEQjDD3AaP9AyAoI3OX1VaNXaUZRg0xmRrZwRZt/54RjuRGR4zYp7fVV+Nq910aAsHYJi9G/4h7Qf3JtqUGsDHZRk4UprZaSfS2TSz7FKkVbEvugPodDrs378fhYUFJtOOGzce48aNx+11czc3NyxfvtykZkVE+Pbbb02a529jbW1lMkpYfn4etFota8B7CDs7Oyxa9KTJbYQajRqRkZEoLS3F6dOncfbsGZP9Z8qUhzBixAhWyUbosgXpXgIRLDrRw9lGKGqXh3AdgBezrqKtxth6AHVEBpHbGmnHIjO84z0Yju1Yu71YVYCjTbZeuXIcHnX1b7Nn+IgeHphQlIyTTQTajyXpGNFDDjHX9fM2DsBUFx8kq6rwUWkmFHfUWwnxeCcvDr4Wtgi1delwXs05lZVq6u/tr43jsKdnENwknXeQjYDjIOoks2NycjK2bv26VWkXL17SaM8xx3GYPDkC33+/2+TRqTdvJuHAgR/xwgsvmJwAODk5Q6fTtWi+TU6+CY1Gw9bR7zHCw8MxderD2Lv3+xbTXblyGXv2fI9ffvnFZH+QSCRYsmQpbGxsWAV3hUAnMrayTXjPMxQDjIRIbb8pgYNlO7wFedw66rOzCROZ4VOvQejbjndU6nU4VGoYMGGUhR0G2bm2+XkuEgtMdZDiZElaYy29rhxP1pQitB3PbA8WAiGelwcjW1WL7YpS3Kkzxes1eCv7Or70D4dnB7fUuZlbw47jUN1I4+eQV19zj39uHAY7yuBzDx65Wl9fj61bv4ZSaXpnyvTpMzB0qGEgjx49euDZZ5/Ds88+Y2Jew+Hbb7di8uTJ8Pf3bzGtVCqFlZUVeL75iXViYgJSUlIwaNAgNqLfS8JFJMKCBQtw8uSvqKgob1GGfPLJxyaXV4h4LFiwEH379u22dxCLxR32cpdIJN0WpKjDAp3jjOvNPcUW8DL/35xFPW5hj1Weoehv69KuTXQxNSXYcodneoNA5ATYXZDUrmdW67V/6cl3bh/j8WNJGvrZukDUTR3KXmSGVV4DkJb6B8422bb4s6oGn+VE49++Q2HdgaNebSSWcOMEqCZ9IwvB77UlWKjXwkbIHKTayqVLl3DkyE8m092KCDbPYKvR7bFg7NhxGDduPE6f/q3F55SXl+O777bj7bf/0eLZ1dbW1vD19W9xLzrHCXDu3DmEhoayvej3GL1798YTTzyBL75Yb1IxNIVM5oE5c+Z0WzheIsLbb/8Dw4cP75gyKhB2m9MmCyzTBgaIzPCUkzcecQtAD3H74oVriceh0nSjv0XWVSCyrqJTy7y9uhCLlFXw7UatMNDSHv/2GIDF6ReR2sQj/bOqAnjlJ+IZWT9I2mkqlptbw0tsgZtqxR02IeB4fS1K1UrYWLKYzm1BoVDgq6++bDFy153aef/+oS0K/KVLl+G33061qJVwHIcdO77DlClTjWr7t3F2dkb//v1NBpfZtWsnHnroIbYf/R5DKBRi9uxHceTIT8jKyurQs5544gn4+3df+xIRpFLZ3yoCIfNybyUPmtvgcNB4LPUIbrcwB26Fed1eXdRt5c7l9ThSkt5pDmmtZZi9G95072PUj2JdSSpOdWBbnaVQhCFGHAdreT1Ol2d3+7v+3fn1119x5cplk+lcXFzxxBPzWtSoAWDgwIGYOXOWyefxPI9vv/3G4AzyRhqHSISRI0eZPNylrKwU33yzFXV1HQ9mFR8fh+zsbNYxOgkPDw8sWbKsQ7sR+vULxrRp05kF5n7X0C0BvO3iB3+L1mlt5eo6PFV00+B6oroOefW1kFm0fxlBT4QjJekope7dZrOlIhdz3YPQ08yq2/IUchxmu/ohS1WNf5VnGUwy3smNgZu5Nbza4SDGAZjg6IGvKnJQcofw5gB8VZqBSc7eXRr69n+JwsJCbN68uRWnoXGYO/cxBAUFmXymhYUF5s+fj6NHfzLpfX78+M945JFZmDRpUosTBF9fvxbDiQLA3r170LNnTzz33PMmJx3NER0djVdfXQWxWIznn38BEydONBnYhmFCaxQIEBERgUOHDuL69WttF1KiW2edy2QyVpn3u4YuBjDWQYZHXP1a9bdI3g9rHQ1jqOcQj49ybqCyA0FS8uoV2FmVj+7eNZuk1+BUaVarwvLwnRi+x1IownMewVhiZahNX9fV44PsKOS3MzxwiK0zhjbZf08AonRqHCpOY3vSW8mBAweQlJTQKi1rzpw5rdaQgoODMW/eApNroxzHYePGDSgvb95pSiaT4eGHp5l0LOJ5Hhs3bsTGjRtRU9M2B0mdToerV6/i7bffQnLyTcTHx2HlyhVYv/5zlJSUsI7SQZydnbFs2fJ23Tt06FBMmDCBnX7HNPS2I+EEWCbrhzO1pTjTZBvYr2oFduTH4wWvgW12XCMQfi5JQ3qTMK/2nADP2Uth2UkhbXkiHKkpwhVt4y1cm8rSMa2nH2xELTuUEBE685w0J7EFVnsNRGrKeZy/o0x6AD8qKyHKiQLa4QZoLRTjmZ6BOJd1DdVNpiAflaShv7UTwnvIOz3yv5Z4XKjIx0A7V9iIJH/rvp6eno6dO78zbRHhOCxevKRNGpJEIsHjjz+OI0d+QllZaYtpY2KicfToUcyfP99o5C+O4/DYY3Px88/HkJaW2uKzNBo11q//DElJiVi+/CmEhIS06JDE8zyqqqqwb98+fPnlRlRW/teHpa5OgfXrP8fVq1fx+utr0K9fPxaZrAOEh4cjImJqqyLB/dfaY4nFixfDwcGBVSAT6O2jp7k1Vkv74M+sa40iwykBbCjLxHB7KQbZ92zTM0s19dhZnm0QaW6JjQve9A2DWScF8CcCfPMTsbAgvtG2sQsaFc6X52KKq1+L9ws5rtM7hb+VA972CMXTmVeRfoeTnB7AHmVVu587zFGGCSVp2K+sbHQ9n3isybmBrebWCLRy6DShXqfXYnNuHD4uTcc8O3e87TMYtn9Toa7T6bBz5w7k5+ebHFz9/PwxderUNmtIgYGBWLhwIT755OMW7yUibNr0FcaNG9dsbG53dymWLFmKN99cY3ItVq/X45dfjuPcuXOYOHEiJk16EL17B8HVtScEAgGICDU1NcjNzcWff17A/v37kZubY/S5PM/jwoU/MG/eE1iz5g1Mnz4dlpaWbJBsB7a2tliwYAHOnTuLujpFq+6ZNGkShg+/O0FkOI5DcXERQsOCJAAAIABJREFU0tPTO+2Zjo6OXTo5YQK9GcY4eeHVqkK8W9U42loqr8enuTHYaOUAhzbEDj9dloUYXVMvYg6PuPrDojOP/OSAsc5e8ClORnITa8Dm4hSMdfKEZYvburrGrDXaUYZVymq8XpSEmjtiF3TEMG4rkuBptyCcybiIiibxEC5qVXg+9QI+8QlDSDu3F95JmUaFT7Ki8FFVPgDCF1V50GcQ3vEJ+1tq6lFRUdi1a6dJIc1xHJ555lk4O7cvpsTMmY/g4MGDyMhoeVDMz8/DgQP78eKLLxoNO8txHKZMmYITJ34xGU3sNiqVEocPH8JPPx2GSCSCubk5HB0doVSqUF1dDb1e1wrfgVtUV1dhzZrVuHEjCq+/vgY9evRgg2Q7GDhwIB599FF8++03Jvuera0dnnxy8V2bQHEch7fffqvTrDJEwLp1n2LGjBldVmZmP2oGM4EQS2T9MExkZiAMvldVYV9BEvhWiqNqnQbfl2agrkn6+Zb27QpMYwpniSWecjDUdH6vr8W1qqK7Up9iToD57kF42l6KztqRyQEY7SjFuy4BBi3BA/hNU4elaX/idFk26tsZS17D3zKxP3vzLD6qymuYgqgBbKjKx/sZV6DQ/73CjtbV1WH79kjU15uOrDd06HA88MAD7V6/lMvlmD9/fqvu3759O5KSkpr93d7eHmvWvIGgoN5tHEgJWq0WtbW1yM7ORmlpCTQadauF+Z3PsbOzYxHpOjKumplhzpy5kEpNL988/vjj6Nev310tr16vh1ar7aQ/TZeXlwn0FvCytMNb0r6wbCLSOQCfl6Yjprp1zjIXK/NxSmPo/DXXxQ82os4POCDkOEzr6Q+XJjPLKgB7SlKh4fV3pT6thCI85xGCKZ14nKqIE2CerA9W2bkZ/f26To0HMi7jzZQ/EFdT2upDYlS8HimKCnyYcRnh6Rew30gUOi2AWr0WujbsWrgX3HouXryIQ4cOtkKA8XjmmWcahXhtDw899DD69DEd3au8vAzffvst1OrmHU979eqFd95ZC0fH7tWQiQhTpz6E55573mR8ckbLBAYG4rHHHmsxjUwmw5w5c9gOg7aOh6wKWma8szeWV+bh/2qK//txA0jkdfg8NxbrrUa3uI5ap9dhb3EalE22V0VIrDDEwb3Lyi23sMXTtm5Y22TJ4KiiDE8ryhHcCTHV21UuM2v8y3MgclP/wDVd5xyrai0UY4XXQBSmXsCuJuvpt1vs05oi7FKUYpalA8LtpRhg6wJzkQSWQjEshUKoeR4qvQ4KrQpRNaU4W5mHSGUl1H8Ja2O2mNfspVjjPRj2RhwNtc0I+cNlWXCuLu6SunU2s8TEHh4tpqmsrMTWrVtb5a0+bdoMDBkypMPlcnFxwZIlS7Fq1QqTWvGxY0cxffqMZk/q4jgOYWFh+PjjT/DWW2+26iCZjsLzPGbOfARvv/02c87qDIVDKMSMGTNx/PhxJCYmGKlvPZYsWQovL29WWUygd7KJSCDEsx79cT7pDK7rG5tMtisrMKrwJhbK+jV7oEpibSl+UFU1ES/AbCdv9BB3nelOzAkw1cXXQKDnEuHHolT064R15fbS16YH3pKH4Jns6yjsJGuBm5kV1vmHQ559Ax9WGT/Jq5jXY6OiDBsVZbAVCOEjEMFdIIQ9J0Qd8SgjPa7rNKhvhcb9vpMPnvfo36yFxeiBOMTjleKULqvX52x7tijQeZ7H8ePH8ccf502uCwoEHBYsWGg0xGt7mDRpEvbsGYzLl1s+Z12pVCIychsGDBjQrCYsEAgwfvx4ODk54R//eBsxMdFd9x2JxViwYCFeeOFFODo6sgGxsyb2cjkWLVqEN95YY3BcamjoQEyd+hALItMOmMm9Ffha2uNVtyDYGjG9v1ucglSF8T20WuKxvzgNyiYCYoTIDOOcPLq83H1snLHU0nAQ+qGmECmKirvY6ThEOHniTRd/dKa7i6uZJV73GYwNroFw4wQtTlhqeD2idWr8rFFit7oWhzV1uKCtNynMewnF2O8xAC97hnbJcklHMDVBKygowMaNG0wKcyLC44/PR0hISKeVzdraGs8993yrYlqfOnUSp06dNDHhEKB///744osvMGPGzC4xzbq5ueOTTz7FqlWvMmHe2X2V4zBx4iQMHhxm0PeWLVsGV1dXVklMoHfdQPlwTz8ssnGBsImmncnr8Un2Daj0OoP7UhQV2FFraF59xEHeLZHMLIUizHU1PM0qidfjRFnmXa1TMSfAPPcgLLbr3GUHO5EET3uEYL/fCCy0doJrJwWjkHECvGjnhoO9xmBmT39YCP9exi29Xo+DB39Ebq7pkLv29g54/PHHOv0QjGHDhv11hjpMTii2bt2K4uJik0LBy8sb7733PjZt2oIRI8I75RAMe3sHLFiwELt27cb06dPZmnkX4ejoiMWLl9zhZEiYNOlBjB49hlUOE+jNDA6d9BwLgQjPe4Sgt5EtX7uUFThUlNIoxhoPwvHSTAOTcm+BCBEu3bc2NNDBDbPMbQ2u76/IRV694q62jZ1IglWe/THF3KZT20zIcRju4I5NvcZgl/cQPGZhD6927vPvLRDhFTs3HPAPx8cB4ehl5Qjub9jX09LSsGXLllvHHbfwx/N6LFiwsM2e5K3BzMwMy5cvh0QiMVmOqKhrOHLkp1adwmVtbY0JEyZg06bN+Oyz9Rg9egxsbe1aHTuciCAUChEY2AvPP/8Cdu/ejbff/gf8/Py6NDrZrfrmm/2jLoh2SIQW8+xIvPX2EB4ejgkTJt5SQCytsGDBQtjZdd/hSqbqorP/upoOqxm2IjMscZA3GkwIBEdx92/tcBSbY4W91EgZO2efsK+VPd6Th+BsVaHBbzGqakzUqhvWxau1GlQQb1AeuZk1/Cy7z7HGXmSGBa4BkFcXNhJEBCBNWQWZuXXjwVEkwQJHeaMDTngQLLtor7WnuQ0+8h6CvnesLXMAHDqh/5gJhBjv5IlwRxmSFRW4VF2IazUlSNHUIUWvRSHPAw2BeDmAE6CPQIheQglk5jYYZ++OXjbO8LO0g6CNA7uVxByrHeXoTr92XwvbZgVHcXExli9/yrTlRCzCjBkzu2z9sn//UHzwwUcoKjK9fVIgEKKurg7W1tamrWgcBzs7Ozz00EOYOHEi0tLSEBcXhytXrqCgIB95eXmoqalGfX09hEIhrKys4eTkDC8vT3h7e2PkyFHw8/ODs7Nzt4QYFYlEeOONNw3Wjxu/vwBOTk6dluft6H3Tpk1r2Rolk3VbRDwrKyssXrwEp0//hhkzZiIsLKzbvpeIiAgMGzasW2VUr169uvT5HBELes24f9AToUSrQq1WDZ1OC9xeM+cE4AQCmIskcJJYsDPV/4dQKBSorKyERqOBXq8Hx3EQiUSwtLSEk5MTc766y+h0Oqxfvx4TJ05A3779WIUwgc5gMBiMvyu1tbWwsrJisfKZQGcwGAwGg8GmQwwGg8FgMIHOYDAYDAaDCXQGg8FgMBhMoDMYDAaDwWACncFgMBgMJtAZDAaDwWAwgc5gMBgMBoMJdAaDwWAwGEygMxgMBoPBBDqDwWAwGAwm0BkMBoPBYDCBzmAwGAwGwxARqwLG/QARQaVSged5mJmZQSxmx6MyGIz2odfrUV9fDwAwNze/Z47gZRo6475AoVDgrbfewpNPLsKNGzdYhTAYjHbB8zyOH/8ZTz/9FNat+6RBsDOBzmB0EzU1Nfj552O4cSMK7u5urELu0DTy8/PATlFmMFpHQkIC/vnPf0Kr1WHRoidhZWXFBDqD0Z2kp6ehvLwUwcEhsLOzZxUCIDn5Jj788ANs3rwZPM+zCmEwTFBYWIj3338PcrkcH3zwATw8PO6p8jGBzrgvyM7OgZmZOQYOHAQLCwtWIQAOHTqEr776EsHBwRAI2FDAYLREfX09Nm3ahIqKCnz00Ufw9va+58rInOIY//Oo1WrEx8eBiODv7w+RqPXdnogamaNNCb4707dXSLYlzzvTcRzX6F6O48BxnNH0CoUCN2/ehFgshlQqa/Tb7XuM/Z+IjD73Tg3f2O/tLa+xe1tTnq56bnO09f1bWz9tKWNb3rm179KZfa8tfd1UPbVU562pY2PlNHWfXq/HrFmzsHjxYsjl8ja9W3dNmJlAZ9wHAr0eUVFRUKvr4ePj0+pBLTs7G9euXcOVK5dRUVEBBwdHjB49GsOGDYOTk5NB+sTEBJw+fQapqSkQiyUYP34cRo8eA2tr61blqdfrkZ6ejtjY2L/yrISjowPGjBmLsLAwgzwBYNu2bSgpKcaMGTNRX3/rPePj4/6yRgzE2LFj4ejo2JD+woULOH/+HOrqlLh27Rp4nsePPx7AmTOnAQDTpk1Dnz59UVZWhm+//QZCoRDLly9HYmISzpw5jczMTDz77HMICQkBEaGkpARxcXE4f/48iouLYW5uhpCQEISHj4S/v7/B4BgVdR3nzp3HgAGh8PHxxcmTJxEdHQ2VSgl/f3+MHj0GgwcPNvAa1ul02LRpE+rqFJg9+1FoNBqcPXsGsbGxePDBB/Hww9MAAEqlEjdu3MCFCxeQnp4OgYBD7959MGrUKPTp08dgMpebm4vvvtsOHx9fPPDAA7h27RpiYmKQn58HPz8/hIeHIySkv9FJIM/zKCwsxLVr1xAVdR25ubmwsrLGyJEjER4eDjc3t0bvX1paiu+++w48r8eyZcthb2+49BMfH4ejR4/C3d0dCxYsBMdxqK6uxtdfbwERYdmyZUhPT8eZM2eQlpaGxYsXY/DgMOTkZOP48V8QHx8HgEN4eDjGjx8PZ2fnVk8i8/Pzcf36NVy9eg1FRUWwtrbCyJGjEBYWBplMZjDBOH78Z0RHR2PKlCmwsbHFpUuXEB8fB41Gg5CQ/hgzZozBfXdOsuPi4nD16lUkJyejqqoK7u5ueOCBCRg8eDB++ukwSkpKMXXqVPj7+zfKNy8vr6GcxcVFsLa2xogR4Rg9ejREIhG+++47mJubY8GCBbC0tGy4T6FQIDo6GteuXUVmZiYUCgV8fHwxadIk9OnTG9u2RYKIx9y5jzX61nQ6HZKTkxEVFYUbN26gsrIC7u5SjB49GuHh4Q153Eaj0SAq6jr++OMPJCenQCp1x/jxD2DYsGFtUibaqw0wGP/TpKSkkFTqRoMHD6KSkhKT6Wtra2nz5s00YEAoeXjIKCDAn0JDQ8jDQ0YeHjKaNGkixcREN6TneZ6OHz9OgYEB5OPjTWFhgykgwI+8vDzotddeo6qqKpN5VldX0+bNm6hfv74kk7lTYGAAhYQEk6ennDw95TR16lSKj49vdE9lZSVNnTqFAgL86MknF1FAgD/5+nqTn58vSaVu5OEho2nTHqasrKyGe/bu3Uu+vt7k5eVJcrmUPD3l5OfnQ35+PhQWNohSUlKIiOj69etkZ2dBU6dG0CuvvEy+vt7k5uZKvXsHUWpqCmm1Wjp16hRNmjSRPDxk5O3tSaGh/cnHx5tkMnfq3TuIjhz5ifR6fUPeOp2O1q1bRzKZO82YMZ3CwgaRXC6lwMAAksulJJO5k5+fL3300UekUCgavWtWVhYNHTqEQkP707/+9U8KCupF7u6u5OhoS6dOnSSe5ykhIYFmz55F3t5e5OXlQSEhwdSrVwDJZO4UEOBPn376KdXX1zd67qFDh8jV1Ynmzp1LU6ZEkIeHjAID/cnDQ0YymTv5+/vS5s2bSaPRNLpPpVLRd99tp8GDB5JcLiUfHy8KDu5L3t636nX06FF06dIl4nm+4Z7Y2Fjy9/elmTNnGDzvNl999SXJZO60cePGhnsTExPJxkZCEydOoFWrVpKfnw+5ublSYKA/xcXF0qVLl2jQoIHk6Smn/v1DqG/fPuThIaO5c+dQbm6uyb6nUqlo//79NHJkOMnlUvL19aaQkGDy8vIguVxKI0YMp7Nnz9Adr0I8z9Py5cvI01NOS5YspuDgfuTl5UEBAX4kk7mTXC6l4cOH0dWrVxvlxfM8ZWdn0TPPPEN+fj4klbqRp6ec/P1v9VkvLw+aO3cOjRgxnAIDAyg7O7tROX/4YS+Fh48guVxKHh5SCgrqRV5eHiSTudPYsWNo7dq15OrqTMuXL6O6ujoiItLr9XT9+jWaNu1h8vLyJKnUjXx8vBry9/f3pWXLlpK3txfNmDGdysvLG/IsLS2ld9/9N/Xu3euv79KfgoP7NXw7Tz75ZKPvS6vV0ubNm8nPz4f8/f0oLGwweXl5kI+PF61bt460Wm2XjnVMoDP+5zlx4gS5u/ekpUuXGAiKptTV1dHatWtJLpdSRMRk+u677yguLo6Sk5PpwoULtHz5cpJK3WjatGlUXV1NREQVFRU0YEAo9evXh44fP07p6el05cqVv4TWYDp79qxJYf7GG2+QTOZO06Y9TPv376f4+Hi6efMm/f777zR//nySy6U0f/78hjyJiJKSkqhv3z4kl0tp/PhxFBkZSbGxMRQbG0s//LCXhg8fTnK5lNaseZ10Oh0RERUUFFBcXBz961//JKnUjd566y2Kjo6m2NhYSkhIaBB427dHkru7K8lk7jRp0gT6+ustdOnSJfr999+pqqqKDh48SAEB/jRo0EBat24d3bgRRSkpKXTjxg368MMPycvLgwIDAygmJqahvBqNhubMeZTkcin5+/vRq6+uovPnz1N8fBxFRUXRhx9+QIGBAeTu3pP27t3bqI4uX75M3t5eJJdLaejQIfTRRx/RH3/8QefPn6eysjKKioqioUOHkJ+fD61cuZIuXvyTbt68SfHx8bR161YaNGggeXl50KFDBxsJ2c8//4xkMnfy8JDRiy++QOfOnaP4+Di6evUqrVmzhmQyd/L0lNOVK5cb7qmvr6fPP/+M5HIpjRo1krZs2ULR0dGUlJRE165doxUrVpCnpwc98MD4RgJ1z5495O7ek955551GE507hd0rr7xM3t6edP78uYbr+/fvJze3W20xbtxY+vLLL+nixYv0+++/U35+Ps2dO4fkcint2rWTkpOTKTExkZYvX0aBgf4UGRnZYt+rr6+nDRs2kIeHjEaODKetW7dSTEw03bx5k6KiomjNmtcb8s3JyWm4r6qqiiZOnEByuZQGDhxAX3zxBV2/fp3i4uLoxIkTNHPmDJLLpTRz5kyqrKxsuC8jI4MiIiaTVOpGDz44iXbu3EFXr16luLhYOnfuHL344ovk4SEjuVxKY8eOaeiPKpWKPv10HXl4yCgoKJA++OB9unTpEiUkJFBUVBT93/99SgMG9G+YGH711ZcN7Xzp0kUKDu5HMpk7zZ8/nw4ePEg3btyg2NhYOnr0KD3++OMkl0tJLpfS6tWvNdxXUlJCS5YsJrlcSnPmPEpHjhyhuLg4unnzJp09e5Zmz55FMpk7rVy5oqGcSUlJJJO508SJE+j8+XOUnp5OJ0/+SoMHD6LRo0dRXFwcE+gMRnvR6/W0adMmkkrd6LPPPjOZft++fSSVutHcuXMazbxvU15eTk888QTJ5TLat+8H4nmeoqOjycNDRkuWLG40YUhMTKSUlBSjg/edg/jWrV+TXC6lBQsWNNJI7tQSpk6dQq6uznT48OGG67/+emuiMnPmDKMDxZEjP5G/vy8NGjSQioqK7tCUtfTPf/6DpFI3OnbsmMF9Op2O1q5dSzKZOz399NONBvJbmmYM9enTm8LCBtOZM6cbCcjbgvv9998jqdSNVq9e3TDYFRcXN2iQBw4cIJVKZZDv999/Tx4eMho/fhwVFBQ0/BYZuY1kMnd68MFJFB0d3ahOi4qKaPr0aeTj4027d+8itVpt8E6HDx8iLy8PmjDhgQaLiUKhoMWLnyR3d1fauHGjwWSvtraWli9fRjKZO23Zspl4niee5+nEiRPk4+NNERGTKS4u1iAvhUJBS5cuJXf3nrR58+aG6++88w7J5VI6evSo0b5QUlJCERGTqU+foAZLiV6vp//7v09JJnOnJUsWU0ZGRqP6rq6uosBAf+rXr2+jNs7JyaHo6OhmLQG3+95vv51qsDrduHHD6Lu89tqrJJW60fr16xuux8fHU9++fWjo0CF04cIFgz4QFxdHAwcOoMBAf4qKiiIiIqVSSS+//BLJZO60evVrlJeXZ5CfWq2mf/97LUmlbvTmm2+QVqslnufp119/JblcSmFhg+nkyZMGbazX6+nChQvUr18fcnbuQadOnSIiosLCwgYr0rp164xayyoqKmju3Lnk7t6Tdu3a1fC8zz//jKRSN3r55ZeorKzM4L60tDQaM2Y0+fh40aVLF4mI6JdffiGp1I0++OD9RmmjoqIoOzu7xbGgM2CurYz/aTQaDa5duwatVgMfn5a9UsvLyxEZuQ1isRivvLICnp6eBmkcHR0xZsxo6PU6XL58BTzPw83NDebm5rh+/ToSExMbnHWCgoLg7+/fokNMSUkJvvnmGzg5OWPVqlVGt8E4OTnh0UfnQCKRICYmuuF6TEwMBAIBHn/8CfTt29fgvgEDBkIu94BSqURZWWnD9ZqaWsTExAAgo/nV1NTg2rWr4Hkezz//fCMHII1Gg71796KiohzPP/88xowZa7BGKhaLMXPmI6isLMTJkyegVqsBAJmZGaipqUZYWBgiIiJgbm7e6D6hUIjJkyfDy8sbMTE3EBsb2/BbQkICRCIRXnzxJYSEhDSq099+O4XLly/h0UcfxSOPzIJEIjF4p2HDhsPfPxD5+fnIyclpWG+/dOkSevRwwpw5cwz2E1tbW2P06NHgeR75+QXQ6XRQq9XYuvVrCAQCrFy5En379jPIy8rKCrNnz4JIJEJ8fDx0Oh1qamqQnJwMsVjSbByEysoKZGVlQSaTQyaTNZTx4sWL0Om0ePHFl+Dt7d2ovgUCIfz8/FFSUoQLFy5Ar9cDAORyOUJCQlqMiKjRaPDNN9+A4zi88sor6N+/v9F3mThx4l/r+/FQKusAAEVFRaiursIDD9xaG27aB273faVS2RB4JS4uDt9/vwseHp545plnIZVKDfKTSCSwt3cAAISGhkIkEkGpVGLjxg3geR4vvPAixo0bZ9DGAoEAffv2hYODI4RCAXr16gUA+OOP35GUlIixY8dh2bJlsLOzM8jT1tYWYrHoL3+L3gCArKwsREZGwsnJGa+88gp69OhhcJ+vry9GjBgBrVaLxMREEBEcHBzA8zx+//13pKenN6QNDQ2Fh4dHlzvHMac4xv809fX1iI6+AUtLKwQG9moxbVpaGi5e/AO2tvbYt28fjh49YiQVh5SUZAgEAiQl3RLePXr0wBtvvIk1a1bj2WefwcqVKxERMQW2trYmy5eSkoKiokJYWVljx47vDITcbW4PDpWVldDptOB5QlpaOiQSCWQyqdF7BAIOAoEAYrEYFhaWjQR2XFwsvL19jXrr1tTUIDY2Br169WoQLLdRKGpx7NgxCAQCnDt3HqmpaQAMg9IoFHXo0UOK/Pw8qFQq2NraIj+/ABqNBoGBgc2+p6WlJYYPH4HU1BQUFRUBAKqqqpCamgorKyuDSZZWq8Xly5chEomQkZGJd9/9d7NOjqWlJairq0NtbS0AIDs7G0VFBZg5cxYsLMybqUMhAIKdnR2EQiGSk5ORmJgIgHDo0CGcPXvW6H35+fkgArKzs1BdXYW6OiVSUpLh4OBgdKJ4u40rK8sxZcqUBoGlUCgQExONwMAgowLQysoKzz33PJYvX4o1a15HYWEh5syZY9SBsinZ2dmIiooCxwlw7NjPuHDhgtF0hYVF4DgOCQnxqKtTwtLSCteuXf1r0jjAqNPb7X4nkUgaHMESExMgEokxe/ajzXqJ19fXIzk5GRzHoWdPt7/uS0RsbCyGDBmKyZMnNysUq6urkZSUgCFDhjU4qp05cwYcx2HWrNmwsbExel9tbS3S0tIgk3k0OCpevXoVhYX5cHR0wqZNmyESCY2OBdeuXWuYrBARgoODsXjxEkRGbsOzzz6Dl156GePHj4eZmRnzcmcwOkpWVhZKSorRu3cfODg4tJg2MzMTZmYW4HkeBw7sazGtWCyBg4MjOI6DUCjEo4/OgUgkxtq1/8Krr67CyZMn8eqrryEwMLDFrTfZ2dl/aXDV2L+/5TxFIjGEQhE4ToCysmKkpqbA2toGMpnxwbGmphbFxUVwcXGFi4tLo0lETU01pk59yOhAk5KSAqWyDqGhAwwEb1lZOYqKCiAWS3D69KlWlFcIiUQCnudx+fIl8DyPgQMHmahbMQBqGETLysqQnZ0NV9eeBoKgqqqqYbJz5colXL16uYUnc5BIxBAIuIb2Njc3R0hI/0YTnjs9qktKigFwkEqlEAgEqK6uhkJRC57nm5nw3fn+IlhaWkIkEiMvLxd5eTl48MEIWFsbFyxJSTchFIowaNDgBqGVnp6G6upqTJr0oIE3NXBri9WECROwefPXWLv2Hbz//rs4ffo3vPzyywgPH9li3ysqKkJ9veqOdyET/d0BQqEQGo0GyckpsLCwaHZyUlFRgaKiYtjZ2cPBwQFarRZZWdkg4iGTyZoVyrW1tUhMTICFhQV8fX0bnqXTaREQEGBUU75NamoKRCIxBg0aBFtbW9TV1aGwsBDm5uaQSt2bvS8nJwdVVZUYNGgw3NxuTSIKCvIhEolRV6fAnj27Tfbz2+UyNzfHypWrYG/vgA0b1uOpp5ZizpzHsGLFSri7uzOBzmB0hIKCAhAR+vbta3SbUFNtj+M4PPLIbKxevdqo6bbpYHp7e5WFhQUee+wx9O/fH5s3b8Lhw4eRkZGBr7/+Gn5+/kbvJyKo1bfMkXPnPo7XX3/d5PsIhUIIhUKUl5cjIyMdAwcOanZrUmZmJioqyjF27LhGwXSysrIgFkswYMAAo5pydnY2RCIxgoODDQS+Wq0Gx3Hw8/PH119/DUfHHibLbGdnB51Oh5iYGNjbO7Q4sOl0OkRH34BOp4OX160lkry8PJSWFhvdIqTT6aBQKCASibB79x7RMj2ZAAAgAElEQVQEBgaaLI+lpeVfZtIE6PV6eHp6GhV8t7bARUOjUTcsTRAReJ7HkCFD8dVXm0weysFxHGxsbJCamgqOEyAkpL/Re9RqNdLT0yEUiuDhIW8oT25uLgQCAYKCgpoNiCQSiTB58mQEBwdj584d+Prrr/HKK69g/fr1GD58RLNl43k9iAijRo3BJ5980qr+bmNjg8LCQqSnp8HOzh5ubsbbsqSkBEVFhfD29oZUKgXHcTAzk0AgEECpVDabR0VFBWJibmDSpMkN5vHb6VuqayJCTk4OOI6DTCaDUCiEWCyGWCyGVquFRqNp9t68vDzU1dXB09Ozob/rdDoAwGuvrcbcuY+Z3FMvFAobJikODg54+eWXMXJkOD799FP88MNeZGVlYdOmza2ynDCBzmAYQa/XIyYmBjyvh6+vr8kT1pycekCn0+LmzSRYWlo2a6IzZs4VCAQQCATo06cPPvjgQ7i5uePLLzdg586d+Mc//mlUI+E4Dl5et9ZECwryYWVlZXJQvU1iYiLU6noMGDCw2YEuMTEBHCdopPHV19cjISEBOp3WqHalUqkQExMNrVYDDw/D393d3WFuboEbN66CCCatHv8dNHNRUlICb29v9OzZs9lB+fz584iLi8WQIcMQEBAAAEhIiAeARu9x52TB398fmZkZqKysbHV5FAoFrl+/DqFQ2OwkQKVSITo6Cu7u0ob4BRYWFjA3t0BVVRV0Ol2rB+jy8goIhUK4uroaba+KinLEx8fBwsK8YQKo0Whw48attvD29mm2790OjiKTyfDqq6/By8sbb7zxOj7//HMMHhzWbL93dHSERCJBamoKVCoVXF1dW/ku5cjPz0NY2JBmJ5O3td6goAiYmZlBIBDAyckZt5asUqBWq41ah65fvw6JRIJRo0Y1TDatrKz++kYKoFQqjVoqNBoNrl+/jvp6JYKCggDcWo93de0JrVaLmJhYhIUNMRDMer0eFy/+CZ7nERIS0nDd1tYORDxSU9NgZWXVapO5Xq+HUCiESCRCWNgQfPnlV1izZg1OnDiOkyd/xWOPPd6lYx5zimP8Twv0qKjr0Ot5BAX1Npk+NHQA/P0DER8fh2PHjkGr1RrVAhQKRcP/4+Li8OWXG1FSUtKQzsrKChERERCLxUhISGjx4JOAgAC4urri/PlzOHHiF4OY6jzPIyMjw+BEp4yMW9pcSEiIUQGh0WiQnp4OkUgEX1+fhoFMrVYjLS0VSmV1wxplU00xKioKjo494OfnZ/C7lZUVpk+fCWtrO2zfHom6ujqjA35hYWET824xqqqqoFarUVtba1AnPM8jOTkZ//nPR9Dr9Zg79zE4OztDp9MhLS0NIpEYvr6+BgOypaUlBg0aDL1ej02bvmpYd2/6Tv/f3nlHx1Vdi/u700fSqGtmNCpWteUqG4MLmGLAlICBAAmmOLz3CxB4TkKABMgjgVASQhJqEpKQAAYC5NEMxhhsggFj44JxxUWWbFnF6l1TNeX8/pA8nhmNpJFkmZLzrWXW4mpuOefuu/c5++y9T2VlZdg929ra+OKLnUyePDWs8E4ohw5VcvhwLdOnzwgakaKiIoqKiigr28fy5cuDM7lIV3ZbW1vYseTkZAIBP9u3b+83W/T5fGzYsJEDB8qZPHlKsBCR1+tl69bPSU5OCSuuckT2amtrWbp0aVjwlVqtZt68U8jMtNHQ0NjvOUIpLh7PxImTqK2t4a233ooq7w0NDTQ3N/cbKLpcLkpLpw/oOj8S0Dhz5szgOzvttNNIT8/gueeeZfny5djtdrxeL16vF7vdzooVK3j00UdQFBVW69GiPIWFhZhMibz//mo2bdrYT3b8fj979uzhk08+ITc3n3Hj8oJ/u+SSSzAa43j66adZu3Ytbrc7OGNvbW3l6aef5rXXXiM+PoHi4vHB8+bOnYtWq2P58rf4/PPPo8prZWVl8LvsHRhs4E9/+mPQo6AoCmlpaVxxxRUEAoHgOvtYov7Vr371K6n6Jd9EmpubeeKJxxGi16DX19ezf//+fv8qKyuxWq2kpKRgMBh4//3VrF+/Ho1Gg9VqRQhBe3s7q1at4qc/vZWGhkbmzJmDoij85S9/6fuIXZSUlKAoCnZ7NytXvsvatR9z8cWXMG/evAFddiaTCY1Gy4cfrmHdunXExcWTkpIMKLS2trJixdvcdtutOBxOZs6ciUajoauri6VLn6WmppobbrghqmFubm7iqaeewu128z//syTovuzp6WHZsmW0tbWTk5NLTk4OXq8XlUqFRqOhoqKcJ554jFmzZnP55d/p55LXaDRkZGTw7rsr2bRpIx0dHVgsFnQ6HXa7nc8++4z777+fd99dybx584JejhUr3mbt2o9pbW1h48aNpKSkBF3xTU1NrFy5kjvu+BlVVYdYtOhKrr/+BvR6PS0tLfzjH3/H4XCyZMmSqFHKNpuNLVs+Z/v2bZSVlWGxWDGZTLjdbsrLy/nLX/7Cvffew+zZs4Pu/m3btvHqq69y1llnc/7534pawWvDho2sXr2KSy+9jNNOO63PbawnNTWFlStXsnHjRnw+LxaLBZVKRUdHO2vXfsIdd9zOvn1lzJ07Nziz8/v9vPnmm+zZs4eMjAxsNhter5eamhpeeulFHnjgPoQQLFp0FXPnzkWlUlFVVcUTTzzOpEmTueKKRf1mpsuXL+fuu39BRUUFU6dORa/X43K5WLNmDStXvsO0adP47nevGNCDo9FoSE1NY+XKd9i0aSM+n5+0tDQ0Gg12u51169bxs5/9lN27dzN79uzg/V9//XV27tzBdddd32+gcUTGXnzxn9TUVHPdddcHg/nS0tKIi4sLDl7Xrv2YgwcrWbv2Yx555BGeeeYfOBwOfD4fixcvJi8vL+iFAVi/fh2bNm0mOTmF1NRU/H4/9fX1LFu2jDvvvJ329nZmzpzJpZdeGpTbnJwcGhsbWL/+E95+ezmbN29m7959rF69igcffJAVK5bj9XpJTk7myiuvDK6FJycn43K52bRpAx999BFJSckkJycjhKClpYVXX32FW265GZMpkcmTJ+P1evnFL+7iX/96ORi8KYSgra2NpUuXsm/fXhYvXhw1K+KYIjOVJd9UNm3aKAoK8oPFJrKyMqP+u+qqq4I5yE6nUzzyyCMiJydLZGVlivT0ZFFcXCiyszOFzWYRJSXjxQMP3C+6u7uEEEJUVlaKSy65WNhsVlFQkCcWLrxQzJx5gsjMtIhFi64Iy6UeCLvdLv7whz8IiyVdZGVlitTURDF58kRhs1mEzWYVEyaMF48++kiwqExNTY2YMWO6OPHEE8KKdoSye/dukZeXKy66aGFYdbSenh7xxz8+IdLTk0VWVqZITo4XBQV5Yt++vUIIIVasWCFsNqt44IEHgsVoouWpr169Wpx44kyRlZUpzOY0UVRUIAoK8kRmpllYrRliyZIl4sCBA8F85yVL/kfk548T119/XV+VN6swm9PE1KmTRVaWta+dxeKhh34rWluP5vyWlZWJoqKCfu2I5LPPPhPnnLNA2GxWYbWaxbhxOWLSpBJhtWYIq9UsLrpoodi8eXMwl3zp0qV9eeJ/jXo9r9crHnjgfmGxZIg33ni939+WLl0qiot7q6KlpSWFvC+LyMnJErfffrtoa2sLy69+8MEHgzKXmWkREydOEOnpyeKUU04Wp512qsjOtonly5cHz1mz5oN+hYEi86d/8IMbhMWSIQoLC8S5554jzj77LJGdnSlOO+3UqHnl/d+lVzz//POipGSCyM7OFBkZKaKwME+MG5ctMjMtIjc3W/zv//5cNDU1BgvKLFq0SBQW5ocVDQrl8OHDYv78M8QJJ8zoJ/9ut1u8/PLL4sILLxAmk0YkJRlFamqiuOCCb4lnnnlaXHHFFcJqNQfzyENrMdx0043CbE4TWVmZwmrNEMXFhcJqzRCFhfli/vwzRHa2Tdx33339nqe9vV089tijYs6cWcJgQCQm6oXVmiEWL75GPPvss2L27FmitHSq2Lt3T7/z7rrrLmGzWfp0QUrfPc3CZrOKqVOniL///amgXO7atUvMn3+GsNksYtq0KeLiiy8SU6dOFhZLurj55h+HFYUaKxQh5EbIkm8m69Z9wqpVq4b8XXHxeL73ve+FzTB27drJO++sZNeuXTgcdtLTM5gxYwbz589n0qRJYWvdjY0NLFv2Jp99tpnGxkZyc3OZOnUql112GWZzbOuSHo+HTZs28emn69m5cyddXV1YLFamTJnCggULKCkpCc4i9+3bxz//+QJms5kbb7wp6rr7+vXreffdlRQXF3PNNYvDZmkOh4M1a9awd+9euru7MRj0/PSnP0Or1bJixdts3ryZ008/gwULFgwaN1BeXs4HH3zA1q2fU1dXh8lkYtKkyZx88snMnTs36Dru6OjgyisX0djYwEsv/Qu3283q1b3uU4/Hg9lsYcqUyZx++hmUlpaGzZY3b97E8uXLo7Yjmqv7/fffZ8uWLRw4UIFOp6O4uJhZs2Zz6qmnBiP9fT4fzz23lMrKSi666GJmzZrV71put5snn/wzbW1t/Nd//Xe/5Qe/38+uXbv6atFvo7m5GYvFQmlpKXPnnsyMGTP6zagdDgerV6/mo48+orx8P3l5+UyZMpkFC85h3brevOVrr72W4uLxCCFYvXoVn3yyjtmzZ7Nw4cKobW5vb+f999/nk0/WUlVVRWpqKtOnT2fhwoUUFhbFHAPS25bVbNu2nfb2NjIyzEyePIl5805lxowZwYC8xsZGnnqqd7vdW265NWpqZnV1Nf/4x99JTEziJz/5SVTvR0tLC21tbXR0dJCcnExqagpqtYZFi65g69YtvPvuKk488aSwczo7O1mz5gM+/PDDvowUPVOmTOGcc86ltbWVjz/+iPPOO5+zzz47anzGkaUQt9tNUlISGRkZNDc3s2jRFWg0Gv71r38FAzFD4yjWrl3L2rUfU1ZWht3eTVFRMVOmTOWMM86gqKgo2D4hBFVVVbz99tts3LiBjo4OiouL++rqnx1zfMdokAZd8o0lEPATCAwt3qHR6pFrmw6Hg0AggEajISEhYdAdnBwOB16vF71ej8FgGFERiUAggN1ux+/3o9VqgwFBkb85Egw1kIGL5TdH2njE/XrEUAkhgkF+seBwOOjp6UGtVhEXF99Pge/evZvvfvc75Obm8vrrbxAXF4cQgq6uLgKBwIDtHE47Io2xy+VCURTi4uKiDniOtFOtVg/4To/0zWC/EULQ3d2Nz+dDq9UOKiNHn8+Fy+VGr9cHjX60ew3nXbhcLjweDxqNmvj4hBHttBYICOz2bvx+PxqNhvj4+H73FUIEi9cMtNGIEAH8/gCKAmp17HHXW7du5bLLvk1qahrvvbdqwIC73ra6URQV8fG98ubz+YLPHaucALz11pvcfPOPOfHEk3jhhX8OmEng9XpxOp34/X6MRuOgWzAfkYkjvx2o5sJYIKPcJd9YVCo1oynMpNFooq7ZDjQoiHVXtcGfWTVkQZpYFHysBjlSKQ9HGR4hPj6+X5W1UOrr6+ns7OCEEy4JKkJFUWLq2+EMLI5gMBiGVKKxtDOWnbEURYmpgFD48/VGyg91r+G8i6GMTGyyN3RbFEUZsl8URYVGo+o3OFqx4m3Gjx9PScnEsHcaCATYt28fDz30W7xeL1deedWgs9lobdVoNP2ey+Vy8corr7BgwYJ+O9/19PTw2Wef8cgjvUF4V1yxaND+02q1w9IFw5UJadAlEsnXgq1bt6JSqZg9e86I9+iWfL3ZsuUz7rjjdpKTU5gzZw4nnTSLrKwsmpub2bZtG//+9/s0NjYwf/6ZLF68+JhsM/r228u59957eOGF55k9ezYzZ55IcnIyhw/XsmPHDt577z26u7u48sqruPDCC78R/Sxd7hKJZMzw+bzcdNNNfPTRh7z44stR16sl33x6C6v8lQ8++DdNTY1h6VuKopCRYWbhwoX84Ac3DlinYLhs376dJ598kg0bPqWzs6Of98NqzeTaa6/l6quvibnmhDToEonkPxaPx8POnTvx+31MnDgpZrel5JtHbx2HKqqqqqioqKCrq4vExCRycnIoLCxg3Li8ES35DIbf72ffvn3U1dVRWXkQp9NJamoa+fn55OfnYbNljfmGKdKgSyQSiUQiGRayUpxEIpFIJNKgSyQSiUQikQZdIpFIJBKJNOgSiUQikUikQZdIJBKJRBp0iUQikUgk0qBLJBKJRCKRBl0ikUgkEok06BKJRCKRSIMukUgkEolEGnSJRCKRSCTSoEskEolEIpEGXSKRSCQSadAlEolEIpFIgy6RSCQSiUQadIlEIpFIJNKgSyQSiUQiDbpEIpFIJBJp0CUSiUQikUiDLpFIJBKJRBp0iUQikUikQZdIJBKJRCINukQikUgkEmnQJRKJRCKRxILmy7hpm9dNvdtOmauT9h4XakVFgkZHviGBHEMiaTojakUZ8PweEeCgowN/wD/iZzCqteTHJxN6l2aPk6YeB4ijxyxGE+laQ/j9AwEqHO0IEeg9oECy1kiWIWHI+3oCfiocbWH3MGn15BgTw57FKwIcOAZtLIhPHvX7qnJ2Yvf1jPh8tUpFQVwKOpUKd8BPpaOdgBCjeyhFwWYwkaLVD/vUCkc7Hr8v7FiKzogthvd39N204w8Ewo5nGk2kRsjKUKzvqKelxxX8/3i1ltNSbOhU6pivYfd7aXLbEQzepwoKBkWFolKhV2tJ0RpQhrh2t6+HGlcX4sj7UsCsTyBDZxzyubp8PdQ4O8OOZejjMevjwo45/F6qnJ1H7zECUnVGMmN8f6G0e93UubpHJYpDvfcuXw/17m72Ojtp97oAhQSNFqsujmJjEsk6I4ZhvO8j19vlaKfb50EA8Wod4/Tx5Mclkaw1oB/G9SJlu9njpMzRTr3XSXePGxAYNXqy9fFMjE8lZRjPKxAccHbi8XmDxwxqDflxyagUZcjzy+xt+EJ0oFalpiA+BU3IuQI45OzEGaKjdGoNBXHJg9qRI5Q72ukJ0Qeh+ir0HrWubrq87pHPnhWF/PiUYb3rr7RB7/B5WNVUydKWA7zncfR1kxLSZTBZY+DyhHS+lVFAaaI5qmB2+Xq48cCnfOxxjPhZfmay8OuS09AqR1/axvZaLqreFva75fmzWJiRH6HkPEwuXwshAnS2IZG/j59HnsE05GBmyr4PIUR5/S51HLcWzg4TPoffy7UHN7DZbR9xG28zZfCHiWeO+r39q3YXd3YcHvH5J+niWDHpbMw6Iy1eN1eXf8K2UQwQjhj0jwtP5rTU7GGf+vChLfzV0RZ27Lvxqfx5/Kn9Bm/R+LjtMN+u3IQ9bLAlWJ0/hwUZeTE/R1OPizsqN7PeF6IkFBV7dWdSYkqLfcDl7uaEPR/QIwIx9Bug0rBAa+A0YwoXmAuZZEof0AAccnUxrewjCGnrdYkWfls4l7QhBlPVjnamln0Y8o3DmznTuThzQvjv3HbO2v8xDRGDrOHwkqWEK8eVDvu8HV3NzD+wPuwZh4fg3wUnc1Z6br+/OAM+3m06yKvNlfyfuzOqvrOptVwel8q5abmckpJNkkY34J2cAR//bj7ES80H+D9X5PV6rzlOrePbcSlclJ7HzGQbiYNcL3KStLOriTcaK1juaGG3zxOlTwRZah2XGlO41FzASck24tWDmxCfENxTtZWXupuDx2xqLf8qmMO8FNugvS6E4NaDG1npPjrgutSYxNMTzyQ5pF1+EeCx2p080VEXPJaoUvNG/mzOTMsZ/B4I7jy0hTdC9EGovgp9ltcayri1+cCIZXSqWsuKKeeSq48fMxt73FzujR4nP9u/nkWHd7IqaIiVCE2jsNvn4d6Ow8yuWMed+9dx0NkRdd6hQQFl5P9USnRdp4743UDCkBnxu7Webh6v3o7d7x2yLywRz64MMIrUjbaNI1ZS/ftlNM+hVY5tu1AUElFG3DpVlPu/4mxnWWMF/iFmiY09Lp6s34NdBPpdQxnmA33aVstWX09Q9kEBIXi7qYIAYlhvyBpr36FAwM/7Hge/7KjlhPK1/PrAJtoGmXlYIq7xj+5mXqzfizeWAUSkrEd5a4oCCaOUCWWEwqAoo5fFaPe2+708cnALl9fs4BV354D6rs7v44nuJi44tIUb9q5hU3tdVO9Vt9/LHyo/5+KabX3GnCgGV6HK7+Wx7ibOrNzMkn0fsamjnqHe0mG3nfvKNzCvfB0PdtaxOyiT/d/lYb+XP9qbmH9wE7eWfcyhCA9MVA9dxLutC/h4oGYH1e7uGM4N1z3qAZ4sUm93iQC/qt1BubNj2PfQKmOjB3WKMuZ29rgYdJffxy8PbuQfjpaQselQA1/BY92NPFi1FV8gwFedHuC5rgaer9+Hb7TuZMmXwh+bKyhztA8623i1YT/LXJ2j/yYCPl5pOYgrytfwUlcDDW7H8Wm0ENzfUcsvDmykO4bBaK9iEzzUfIBVLdXDHHj8Z+AXgmdqdvHL9uq+OWBsvOLu4mfVW2mJGFx5RYB/1OzinrYqlGHoln+6OvhV9TZaQ5Z0Itlnb+XG/Z/w687DeMRw9KzgKUcr3y/7mE/b64bdR6s93fyhajudo/XUDcK6Hie/q9pGm9fzHyN7x8XlvqWznlfsrWHHUlCYqDMyXp+ARwSodHdT5e+hPkRg81QafpQ9Fa1q6HGHCchV1DHP2kJd7ceKdiF4vLGciXEpzB+BK7j/JxNOPJD3JbcRwACMU1RoY3ySBEUdZg40itLr4Yg0mEBzhMJKRCFeiT7qP9bj3V2+Hv5yeDe/LZob1ZW4x97Kn1oOHpN77ehsYrW7K+rftvs8rG2rYZFt4oivn4FCiqKEyVAAcCFoFYJIFfdidxPnNFVySeb4mOSyLuDn14d3UhSXREl8yjGXsQwULMOQX/UxnP3kKwrxMc51vIh+krjP2c4TrZURcgwTtQZKDIkIBBVuOzU+D/UiwJGFhnhF4ee2yf3iE6qdXfym9SBKiE6IB6ZqjRTpE9ApCgc8Diq9LupFAG/Qi6hiibVkwHiHSlcXPzqwkX/3OPrNRFMVhSxFTZrWQADo9Lmp8vtpj9BKa3xueg59xpOaU5hqSh9WP7/Q3cDEhjJuzJoS03r6SPg/ewsT6vbwk9zSMdGH4xVVr8cxBhIVFWM9Rx9zg+4XgnfbaukKEwSF32dO5LuZEzD2rd35RIBd3a280VjOsq4GykSAe6wTmJyQHlWh+CIE6xR9PC9MPCvmDtMoqjF5wfsDPu6v2UGWIYHxcaMISBP92zhdH8/rJfPRxPjcY2XQC1VqXi6Zj00XF5sbSFFIUveueaVp9fyx6JSobsVDjjYur90e5lT7QUo2V5iLovq/hopXGAl/627grNZqLjbnhynqbr+XPx/eTVmMs9ihvom3WippHWS29XxLJReYCzHFuAYayZJEK/89bkaYBPlEgE6fh71dTfypqYKNvqNmvQt4sbmC8y2FMQdUbfS6ub9qK48Wn4xZaxy5qAuIDP1cnJTJXfknxTy/PZaBRo/ZpnLKMGIh4tXaMN30RWcjNRHBrHek5bEkd3pwoOgXgjJnOx+2VLO0rYrtfi+3JGczPy23nw7b2FFHS4iX0gjck57PDTmlwesFhKDc2cGqlkO83FbNLr+X7yfbOHeAdjj8Xu6t3MxHEcY8BYXz4pK5MXMi0xIzetsmeoN5N3fW81JjBW84Wgj1Y63zebiv8jP+OnE+acMICu0Ugocb91NkTGbBEGvdI8WO4I/NByiJS+bCjLwRTwNEn4cu8ujL409jnDExRs+WMmiMxNfCoAsEO93dYZ9lqdbAxZZCTCEfgkZRcVKShZmJZq60t7C6tZpLLcVRR94KfWvoocYLhTSNfsD16OPJhz0OnqjezgNFc0nW6Ed2EYV+M2ANKlI1hpg8FmOJGkjR6If18QaVkUrNjAFG8vFRXH65ujhmJmYct7Z5heCR+j2ckGgmty9qOoDgvZZDPNXdeEzucdDZwf91Hb2WHphvMPFeyJriux4727qaRhT0B5Cq1gafP5ITTBlMNZm5qvwTdgeOBqJt97qpdHUNa8b9qqOVaYf38JPc6SOOrFaUvnXMCDlJ1eq/FPlOVGtGJNtHNN4OVydhjmRFxTXWCWHKXKPAtIR0piakc7G5kFcaK7g6c0LUgUlnRPBvhqJwiWV8uHFQYHJCGpMS0rjUXMRz9Xu5LnvKgIP6T9pqecfZHvQOKIAJhfstxfx31hTiQj1UCmhVKs5My2VOso0ZNTu5r/kATSFa/TVPN5c1Vw7bq1QZ8PNg7Q4KjYkUxiWNyfusFQF+fXgXecZEpiakjVQdh0XWHyFZoxuFrBx7jotlcIvw0epOfw9Ob8+As7lppgx+mjcz5gjNryJ/7m5mad1eer4G6/+SCGXX4+Sl+n3Bd1fl6ubh+n3HaIALq1qrqAwxpFPVWn6bdxKlEYO/V5sq6BlF2uJgTEvM4Fvx4cqtQvhxD3O90Qv8vqWSt5sr5Xp63/v1RL4zEaC5xzmgociLS+L2/JlR014DCJyB8Oh/p4A6j33Q691TOIcsffQBnSvg5+mGMlpCZpwCuCU1h+9nTw035hHEqTVcl1vKjSlZ/b1KzQdpHWZalwA+6nHy2+qtwz53OPfY5HXzUPU2mgaJJ/gmMOYGXUEhN8IdJwJ+flm5mY3th49ZwEIwAvFLwhYxslYQPNRUwcdtNcdUzX0FHBDfAK0bPsgap6goVevCPoY/tVWxpasBrwjwUv0+NnnDFcG5UZSlLoYljpYeF8vba8N8L+clWpmSkMb1qeGpTy/am6mIIUp3pMRFzixE8D/hRiXC1Rgp660iwG/qvuCL7tYIY8SIs8G+XDFXRnGmQl7EUpQK+MWhLaxoPECjx8lwhvgqFBIjBnotCH5VtZW3Gito8jiHzMyIZL+9jU0hAwIFOFGj579sk2JautCr1NyUU8psdfiE690ee7++FXMAABcqSURBVL+6A9HIUFSoI9aTX+hu4YX6fUNmTgQzVIbAgEJ8xPf4oqONpw5/gfsYDpIVvloKecxd7ipF4VyThRe7m8LcUM8723m+Yh3n6U3Mj09joimdUlMGmYaEIdd+BaLf+nKd38urDeUxGbx5yZlk6hOOaTtPiUtmoi6Bh9qq8PSpxSYR4N6a7RTEJVE4zPV0IXrdv6E0+3t4rbEipgCgk5OsZI3BGjP0rn2903KI1Bg8KHnGJE5KNH8F51FHmajRc7V1Aotrd6CI3lXbwwE/T9TuYrHXw8NtVWG/X2IyMy/RwqrDu8KOxxKuuK6tlvdDZms2ReHijALUisK56XkkNR+gs0+ptQvBe82VlMSnHvOgIXfAT21EtH6WSoUmZBmsVw4FkdnhVyRn4exx8jd7S/DYNl8Pv636nCcmnB7M5ffFGDUdbQ19j7ub1xrLhxwMKyicl5ZLwjH05n3U1UhzDGbXqNJwdlpumBFUgBmmDNKaKmjte/oAsNrr4r3qLZxYb2RhfDpTEjM4wZRBuj6BhCFyuScmWqC5PGyg8ZHXxUfVW5lRt5sL4lIoTbIyM9GMWZ8wZG74ju5makLejQDON2XEvBYMYNHHc1myjU2th8LexsbOeqYnWQY9N1tr4O7UXO5tPOol6EHw+6YKJselcFZ67oAptxoltlmoW6XiWWsJd9Xvpa6vrQrwcOshpsSlstBcMKxASkF/fQwKK1urMHcPHT+SYzAxO8n69Q+KU4CzMvKY21zOWq874gNVeM9j5z2PHdoOUajWcaExiTNTx3Fyio30AaIzFZR+a+hbfB6uqNka05v5XHfqMTfoCYqaH2RPocxj5xVH76ccANb7PNx/6HP+UHxKTEVLQmfi2giB2+PzcGXNtph6/bPCk/sZ9EpnJ+4hineoVArF8SmD5rBXiQA31u0mlgTE35uLx8SgCwQVjo4hUxo1KhXFkWvCEQNGBYX5qdnc5Wjj123VweNvujpZW72V9r4PWQEma3T8IGsKdVFmIkOl/dj9Xt5sDR8cnGJIYkpfTEGOMZEbTGZ+39UQ/Ptz7TVcYZtI1jEsRuEK+Hm5bm9fsZOjTNboyYyQGeVI/mzIqx6nNbLAOp5dFZ/yacjg5E1XJ0XV2/l5/okYVZpej4UYesIbbQ39DVcHb1RvjUnWG5Osx9Sg39tRCx01Q/7uQl08J6dk9ZvVnpBk5bL4VJ5ytIZ7K1DY4nWzpe/66SoNF+hNLEjJZn5aDrYBBuAzksxcH5/B3x0t/f62zedhW1cDdNVjVmk4X2/irJQszk7PI3MAmamM4q4vTcgYlrFRgJMSzRhbDxHqu7LH4NJ2iwCXmwtp8br5feshnH2apE4EuLt2J1lGE5PiU6Oe2yNEzFUmv5WeR4ffyz2N5XT1hVd2CMG9dV+QazRxwjD0kkJ/fawCftiwLyY9eG9qHrMSLWMe43Vc0tbSdEYeK5jDzQc3stHrpmeALjvg9/K4vYXH7S2c27CX/82eximpOcMYScXwO2Xs1vnMOiN3586govwTPg+JIH7O0cr4w7u5LXf6l+oO/F3NDv7Z3TTob0rUOj4tvQBVTAFOSgy/GBsB9gvBbVWf8+EQLulzdXG8PPW8CK9P/2cyqNRcZ5vMp/ZWPuyL/PUA9SHuOYHCTy0TmGxK43AUgz7UGvLu7haedx6tSBUPLM4oCAaT6VVqFmbk8/uu+uAzlvu9rG+t5ju2icPqyR3uLpY17A8tSEgAQXWPk+32Ft52deAM+aMBuCY9f8jqb0d6YlJ8KndnTeX6qi3BiG4X8Nf2Worjkrk6ohrc8Zb143Fv1QDSHafWcE/BbFwVn/KqqwP3ANdvCfh5ztXBc64OTm7az83WiXzbWtzPQ5mg1nJvwSxcBzbwqrMdzwDXawq53pnNB/ihtYTzzYX9Bhz9iwgJsnTDz1LQa/TEKwquEDmq83rwBALohwjcNag03Jg9h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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
\n\n\n\n\n\n\n\n\n

part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Bulletin_Note_part nom 1_part 1_519.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None] +DEBUG:xhtml2pdf.tables:Col 0 has width 30% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 10% +DEBUG:xhtml2pdf.tables:Col 4 has width 40% +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: ['30%', '10%', '10%', '10%', '40%'] +DEBUG:xhtml2pdf.tables:Col 0 has width 30% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 10% +DEBUG:xhtml2pdf.tables:Col 4 has width 40% +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: ['30%', '10%', '10%', '10%', '40%'] +DEBUG:xhtml2pdf.tables:Col 0 has width 30% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 10% +DEBUG:xhtml2pdf.tables:Col 4 has width 40% +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: ['30%', '10%', '10%', '10%', '40%'] +DEBUG:xhtml2pdf.tables:Col 0 has width 30% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 10% +DEBUG:xhtml2pdf.tables:Col 4 has width 40% +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: ['30%', '10%', '10%', '10%', '40%'] +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col widths: ['10%', '10%', '10%', '70%'] +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col widths: ['10%', '10%', '10%', '70%'] +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col widths: ['10%', '10%', '10%', '70%'] +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col 0 has width 10% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 10% +DEBUG:xhtml2pdf.tables:Col 3 has width 70% +DEBUG:xhtml2pdf.tables:Col widths: ['10%', '10%', '10%', '70%'] +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:34:47] "GET /myclass/api/Prepare_and_Send_Inscrit_Bulletin_Note_By_PDF/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/690f3a70995b26cde9611a3b HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:36:37.024803 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:36:37.024803 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:36:37.024803 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:36:37.024803 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:36:37.024803 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:38:20.478127 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:38:20] "POST /myclass/api/Update_Partner_Document/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:38:20.542134 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:38:20] "POST /myclass/api/Get_Given_Partner_Document/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:39:48.349666 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:39:48.350638 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:39:48.350638 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:39:48.350638 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:39:48.350638 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:43:44.007676 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:43:44.007676 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:43:44.008679 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:43:44.008679 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:43:44.008679 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:44:03.524469 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:44:03.524469 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:44:03.525471 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:44:03.525471 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:44:03.525471 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:44:12.418670 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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: ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:48:55.838911 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:48:56.046413 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 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+DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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+DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:50:19.833854 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:50:19.833854 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:50:19.833854 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:50:19.833854 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:50:19.833854 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:50:51.231486 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:50:51.231486 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:50:51.231486 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:50:51.231486 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:50:51.231486 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:51:45.069099 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:51:45.069099 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:51:45.070096 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:51:45.070096 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:51:45.070096 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\base_class_calcul_note.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:52:52.643790 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:52:52.643790 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:52:52.643790 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:52:52.644777 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:52:52.644777 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 10:53:16.540765 : Security check : IP adresse '127.0.0.1' connected +DEBUG:matplotlib.pyplot:Loaded backend tkagg version 8.6. +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 1189 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 2994 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 374 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 286 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 263 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 387 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 436 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 351 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sBIT' 41 4 +DEBUG:PIL.PngImagePlugin:b'sBIT' 41 4 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 364 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0. +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgia.ttf', name='Georgia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\impact.ttf', name='Impact', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CURLZ___.TTF', name='Curlz MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALN.TTF', name='Arial', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 6.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUABI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\wingding.ttf', name='Wingdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegUIVar.ttf', name='Segoe UI Variable', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSR.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarab.ttf', name='Candara', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRITANIC.TTF', name='Britannic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHV.TTF', name='Franklin Gothic Heavy', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTEXTRA.TTF', name='MT Extra', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MATURASC.TTF', name='Matura MT Script Capitals', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunsl.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdana.ttf', name='Verdana', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 3.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGSOL.TTF', name='Niagara Solid', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelb.ttf', name='Corbel', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSB.TTF', name='Berlin Sans FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERB____.TTF', name='Perpetua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\NIAGENG.TTF', name='Niagara Engraved', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABK.TTF', name='Franklin Gothic Book', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JOKERMAN.TTF', name='Jokerman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicbd.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILLUBCD.TTF', name='Gill Sans Ultra Bold Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoesc.ttf', name='Segoe Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailub.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OUTLOOK.TTF', name='MS Outlook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILB____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsunb.ttf', name='SimSun-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrii.ttf', name='Calibri', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoepr.ttf', name='Segoe Print', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAVIE.TTF', name='Ravie', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\KUNSTLER.TTF', name='Kunstler Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILSANUB.TTF', name='Gill Sans Ultra Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibriz.ttf', name='Calibri', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\IMPRISHA.TTF', name='Imprint MT Shadow', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbel.ttf', name='Corbel', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuiz.ttf', name='Segoe UI', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbell.ttf', name='Corbel', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIST.TTF', name='Calisto MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibri.ttf', name='Calibri', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTB.TTF', name='Calisto MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjh.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASMD.TTF', name='Eras Medium ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candara.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrima.ttf', name='Ebrima', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCM____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAI.TTF', name='Book Antiqua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaral.ttf', name='Candara', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhbd.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAMDCN.TTF', name='Franklin Gothic Medium Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriai.ttf', name='Cambria', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCB____.TTF', name='Tw Cen MT Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consola.ttf', name='Consolas', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrib.ttf', name='Calibri', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARABD.TTF', name='Garamond', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUB.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolab.ttf', name='Consolas', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTILI.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\RAGE.TTF', name='Rage Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARLRDBD.TTF', name='Arial Rounded MT Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSDI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSD.TTF', name='Lucida Sans', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ebrimabd.ttf', name='Ebrima', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariali.ttf', name='Arial', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 7.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKB.TTF', name='Rockwell', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BROADW.TTF', name='Broadway', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CBI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ONYX.TTF', name='Onyx', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCK.TTF', name='Rockwell', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEB.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BKANT.TTF', name='Book Antiqua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeprb.ttf', name='Segoe Print', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LATINWD.TTF', name='Wide Latin', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palabi.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADM.TTF', name='Franklin Gothic Demi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFI.TTF', name='Californian FB', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Inkfree.ttf', name='Ink Free', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEDI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICB.TTF', name='Century Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\micross.ttf', name='Microsoft Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbd.ttf', name='Times New Roman', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COOPBL.TTF', name='Cooper Black', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTI.TTF', name='Calisto MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHIC.TTF', name='Century Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCRIPTBL.TTF', name='Script MT Bold', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FORTE.TTF', name='Forte', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKBI.TTF', name='Rockwell', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRADHITC.TTF', name='Bradley Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiab.ttf', name='Georgia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERTIBD.TTF', name='Perpetua Titling MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYB.TTF', name='Agency FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_B.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyi.ttf', name='Microsoft Yi Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BSSYM7.TTF', name='Bookshelf Symbol 7', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyhl.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITED.TTF', name='Lucida Bright', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolai.ttf', name='Consolas', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\INFROMAN.TTF', name='Informal Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SHOWG.TTF', name='Showcard Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRLNSDB.TTF', name='Berlin Sans FB Demi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspab.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HATTEN.TTF', name='Haettenschweiler', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSI.TTF', name='Goudy Old Style', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoescb.ttf', name='Segoe Script', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisym.ttf', name='Segoe UI Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuii.ttf', name='Segoe UI', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRAHVIT.TTF', name='Franklin Gothic Heavy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCC____.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSPCL.TTF', name='MS Reference Specialty', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgun.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbi.ttf', name='Arial', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 7.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VLADIMIR.TTF', name='Vladimir Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF-Italic.ttf', name='Sitka', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLI.TTF', name='Bell MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguili.ttf', name='Segoe UI', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisbi.ttf', name='Segoe UI', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisli.ttf', name='Segoe UI', style='italic', variant='normal', weight=350, stretch='normal', size='scalable')) = 11.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ALGER.TTF', name='Algerian', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelz.ttf', name='Corbel', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ariblk.ttf', name='Arial', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 6.888636363636364 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANS.TTF', name='Lucida Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucit.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framdit.ttf', name='Franklin Gothic Medium', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIL_____.TTF', name='Gill Sans MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OLDENGL.TTF', name='Old English Text MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtext.ttf', name='Myanmar Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comic.ttf', name='Comic Sans MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Nirmala.ttc', name='Nirmala UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comici.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-MEDIUM.TTF', name='Dubai', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAX.TTF', name='Lucida Fax', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarali.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\pala.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-REGULAR.TTF', name='Dubai', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbi.ttf', name='Trebuchet MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ENGR.TTF', name='Engravers MT', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesi.ttf', name='Times New Roman', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILI____.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PRISTINA.TTF', name='Pristina', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXD.TTF', name='Lucida Fax', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICI.TTF', name='Century Gothic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanz.ttf', name='Constantia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKB.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanab.ttf', name='Verdana', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 3.9713636363636367 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BRUSHSCI.TTF', name='Brush Script MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSBI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARNGTON.TTF', name='Harrington', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNI.TTF', name='Arial', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 7.613636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\webdings.ttf', name='Webdings', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mingliub.ttc', name='MingLiU-ExtB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELL.TTF', name='Bell MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candaraz.ttf', name='Candara', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\malgunbd.ttf', name='Malgun Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelUIsl.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BAUHS93.TTF', name='Bauhaus 93', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiai.ttf', name='Georgia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CASTELAR.TTF', name='Castellar', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuisl.ttf', name='Segoe UI', style='normal', variant='normal', weight=350, stretch='normal', size='scalable')) = 10.0975 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOSB.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITEI.TTF', name='Lucida Bright', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguiemj.ttf', name='Segoe UI Emoji', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCCB___.TTF', name='Rockwell Condensed', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeui.ttf', name='Segoe UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\lucon.ttf', name='Lucida Console', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothL.ttc', name='Yu Gothic', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTL.TTF', name='Copperplate Gothic Light', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TEMPSITC.TTF', name='Tempus Sans ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuib.ttf', name='Segoe UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SimsunExtG.ttf', name='SimSun-ExtG', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARA.TTF', name='Garamond', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbd.ttf', name='Courier New', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAGNETOB.TTF', name='Magneto', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERI____.TTF', name='Perpetua', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRSCRIPT.TTF', name='French Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSI.TTF', name='Bookman Old Style', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibli.ttf', name='Segoe UI', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\STENCIL.TTF', name='Stencil', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebucbd.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguisb.ttf', name='Segoe UI', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PLAYBILL.TTF', name='Playbill', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PALSCRI.TTF', name='Palace Script MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASLGHT.TTF', name='Eras Light ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_PSTC.TTF', name='Bodoni MT', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLECB.TTF', name='Gloucester MT Extra Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNB.TTF', name='Arial', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 6.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriab.ttf', name='Cambria', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCEDSCR.TTF', name='Edwardian Script ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CHILLER.TTF', name='Chiller', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\consolaz.ttf', name='Consolas', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\JUICE___.TTF', name='Juice ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mvboli.ttf', name='MV Boli', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BASKVILL.TTF', name='Baskerville Old Face', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\javatext.ttf', name='Javanese Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palai.ttf', name='Palatino Linotype', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALISTBI.TTF', name='Calisto MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMIT.TTF', name='Franklin Gothic Demi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VINERITC.TTF', name='Viner Hand ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PERBI___.TTF', name='Perpetua', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\monbaiti.ttf', name='Mongolian Baiti', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahoma.ttf', name='Tahoma', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERTI.TTF', name='High Tower Text', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arial.ttf', name='Arial', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 6.413636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msyh.ttc', name='Microsoft YaHei', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=900, stretch='normal', size='scalable')) = 11.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\tahomabd.ttf', name='Tahoma', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCM_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LHANDW.TTF', name='Lucida Handwriting', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PER_____.TTF', name='Perpetua', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCBI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\courbi.ttf', name='Courier New', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbelli.ttf', name='Corbel', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKEB.TTF', name='Rockwell Extra Bold', style='normal', variant='normal', weight=800, stretch='normal', size='scalable')) = 10.43 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASDEMI.TTF', name='Eras Demi ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\mmrtextb.ttf', name='Myanmar Text', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOTHICBI.TTF', name='Century Gothic', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COLONNA.TTF', name='Colonna MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothM.ttc', name='Yu Gothic', style='normal', variant='normal', weight=500, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCB_____.TTF', name='Tw Cen MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\couri.ttf', name='Courier New', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEBO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugib.ttf', name='Gadugi', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibrili.ttf', name='Calibri', style='italic', variant='normal', weight=300, stretch='normal', size='scalable')) = 11.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguibl.ttf', name='Segoe UI', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWAD.TTF', name='Leelawadee', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FELIXTI.TTF', name='Felix Titling', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\times.ttf', name='Times New Roman', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\himalaya.ttf', name='Microsoft Himalaya', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SitkaVF.ttf', name='Sitka', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LBRITE.TTF', name='Lucida Bright', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PARCHM.TTF', name='Parchment', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\sylfaen.ttf', name='Sylfaen', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constan.ttf', name='Constantia', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCCEB.TTF', name='Tw Cen MT Condensed Extra Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_BLAR.TTF', name='Bodoni MT', style='normal', variant='normal', weight=900, stretch='normal', size='scalable')) = 10.525 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\TCMI____.TTF', name='Tw Cen MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\framd.ttf', name='Franklin Gothic Medium', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\palab.ttf', name='Palatino Linotype', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-LIGHT.TTF', name='Dubai', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\georgiaz.ttf', name='Georgia', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\PAPYRUS.TTF', name='Papyrus', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GARAIT.TTF', name='Garamond', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTURY.TTF', name='Century', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\bahnschrift.ttf', name='Bahnschrift', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENTAUR.TTF', name='Centaur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BERNHC.TTF', name='Bernard MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ROCKI.TTF', name='Rockwell', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ERASBD.TTF', name='Eras Bold ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Gabriola.ttf', name='Gabriola', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG2.TTF', name='Wingdings 2', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SansSerifCollection.ttf', name='Sans Serif Collection', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNTI.TTF', name='Elephant', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LCALLIG.TTF', name='Lucida Calligraphy', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\gadugi.ttf', name='Gadugi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRADMCN.TTF', name='Franklin Gothic Demi Cond', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GLSNECB.TTF', name='Gill Sans MT Ext Condensed Bold', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GIGI.TTF', name='Gigi', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LEELAWDB.TTF', name='Leelawadee', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\AGENCYR.TTF', name='Agency FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CB.TTF', name='Bodoni MT', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCBLKAD.TTF', name='Blackadder ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taile.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msgothic.ttc', name='MS Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CENSCBK.TTF', name='Century Schoolbook', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constanb.ttf', name='Constantia', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\constani.ttf', name='Constantia', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MTCORSVA.TTF', name='Monotype Corsiva', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ntailu.ttf', name='Microsoft New Tai Lue', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\simsun.ttc', name='SimSun', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cour.ttf', name='Courier New', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\POORICH.TTF', name='Poor Richard', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\taileb.ttf', name='Microsoft Tai Le', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFR.TTF', name='Californian FB', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKBI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILC____.TTF', name='Gill Sans MT Condensed', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GILBI___.TTF', name='Gill Sans MT', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FTLTLT.TTF', name='Footlight MT Light', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ARIALNBI.TTF', name='Arial', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 7.8986363636363635 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FRABKIT.TTF', name='Franklin Gothic Book', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_CI.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPE.TTF', name='Lucida Sans Typewriter', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\OCRAEXT.TTF', name='OCR A Extended', style='normal', variant='normal', weight=400, stretch='expanded', size='scalable')) = 10.25 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SegoeIcons.ttf', name='Segoe Fluent Icons', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambria.ttc', name='Cambria', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\corbeli.ttf', name='Corbel', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\timesbi.ttf', name='Times New Roman', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LSANSI.TTF', name='Lucida Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segmdl2.ttf', name='Segoe MDL2 Assets', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\l_10646.ttf', name='Lucida Sans Unicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LTYPEO.TTF', name='Lucida Sans Typewriter', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelaUIb.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\VIVALDII.TTF', name='Vivaldi', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SCHLBKI.TTF', name='Century Schoolbook', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanai.ttf', name='Verdana', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 4.6863636363636365 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LFAXDI.TTF', name='Lucida Fax', style='italic', variant='normal', weight=600, stretch='normal', size='scalable')) = 11.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\arialbd.ttf', name='Arial', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 6.698636363636363 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDOS.TTF', name='Goudy Old Style', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\cambriaz.ttf', name='Cambria', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HTOWERT.TTF', name='High Tower Text', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MOD20.TTF', name='Modern No. 20', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MSUIGHUR.TTF', name='Microsoft Uighur', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOS.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOOKOSB.TTF', name='Bookman Old Style', style='normal', variant='normal', weight=600, stretch='normal', size='scalable')) = 10.24 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\phagspa.ttf', name='Microsoft PhagsPa', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_I.TTF', name='Bodoni MT', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BELLB.TTF', name='Bell MT', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\symbol.ttf', name='Symbol', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhbd.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\msjhl.ttc', name='Microsoft JhengHei', style='normal', variant='normal', weight=290, stretch='normal', size='scalable')) = 10.1545 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\verdanaz.ttf', name='Verdana', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 4.971363636363637 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\DUBAI-BOLD.TTF', name='Dubai', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\seguihis.ttf', name='Segoe UI Historic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\HARLOWSI.TTF', name='Harlow Solid Italic', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\GOUDYSTO.TTF', name='Goudy Stout', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothB.ttc', name='Yu Gothic', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ELEPHNT.TTF', name='Elephant', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\BOD_R.TTF', name='Bodoni MT', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\REFSAN.TTF', name='MS Reference Sans Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\comicz.ttf', name='Comic Sans MS', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\YuGothR.ttc', name='Yu Gothic', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ANTQUAB.TTF', name='Book Antiqua', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\SNAP____.TTF', name='Snap ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\WINGDNG3.TTF', name='Wingdings 3', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\trebuc.ttf', name='Trebuchet MS', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\LeelawUI.ttf', name='Leelawadee UI', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\Candarai.ttf', name='Candara', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\calibril.ttf', name='Calibri', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\segoeuil.ttf', name='Segoe UI', style='normal', variant='normal', weight=300, stretch='normal', size='scalable')) = 10.145 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\CALIFB.TTF', name='Californian FB', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\COPRGTB.TTF', name='Copperplate Gothic Bold', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MAIAN.TTF', name='Maiandra GD', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\FREESCPT.TTF', name='Freestyle Script', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\MISTRAL.TTF', name='Mistral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: score(FontEntry(fname='C:\\Windows\\Fonts\\ITCKRIST.TTF', name='Kristen ITC', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05 +DEBUG:matplotlib.font_manager:findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Continue\\Ela_back\\Back_Office\\venv\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\ttf\\DejaVuSans.ttf') with score of 0.050000. +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n \n \n \n \n \n

 

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BULLETIN DE NOTE
Entrée Scolaire: 2025/2026
Promotion : Licence L1 08/11/2025
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part nom 1   part 1
Né(e) le 30/07/2025
 
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

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Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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\n

Note par matière / UE  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Matière / UERangMoy. ElMoy. Ens.Observation
INITIATION A LA PROGRAMMATION57.511.41  
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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

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RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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Note générale  

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RangMoy. ElValidéObservation
57.50doit redoubler d\'effort
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Imprimé le : 09/11/2025  

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/myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:54:19] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:54:21.126165 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:54:21] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:55:40.765185 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:40.768189 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:40.772189 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:40.777189 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:40.782695 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:55:40.791698 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:55:40.802696 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:40.810695 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:40] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:55:47.069219 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:47.074227 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:47.077225 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:47.081223 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:55:47.086739 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:47.090746 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:55:47.098739 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:55:47.115739 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:55:47] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:56:04.844236 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:56:04.847239 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:56:04.853239 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:56:04.858238 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:56:04.862236 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:56:04.868239 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:56:04.887235 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 10:56:04.894730 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:04] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:56:55.025509 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:55] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 10:56:55.096677 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 10:56:55] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:59:30.704535 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:59:30.704535 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:59:30.705551 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:59:30.705551 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:59:30.705551 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 10:59:59.603594 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 10:59:59.603594 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 10:59:59.603594 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 10:59:59.603594 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 10:59:59.603594 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:00:20.545744 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:00:20.545744 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:00:20.545744 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:00:20.545744 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:00:20.545744 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:01:11.693742 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:01:11.693742 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:01:11.693742 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:01:11.693742 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:01:11.693742 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:01:58.147491 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:01:58.147491 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:01:58.147491 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:01:58.147491 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:01:58.147491 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:03:33.705724 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:03:33.705724 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:03:33.705724 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:03:33.705724 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:03:33.705724 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 11:05:13.408511 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:13.409511 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:13.412512 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:13.418512 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:13.421511 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:13.425509 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:13.455508 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:13.462511 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:13] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:21.587530 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:21.590535 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:21.594534 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:21.600535 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:21] "POST /myclass/api/Get_Competence_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:21] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:21.609022 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:21] "POST /myclass/api/Get_List_Manager_Ressource_Humaine/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:21.614020 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:21.619525 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:21] "POST /myclass/api/Get_Competence_Level/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:21] "POST /myclass/api/Get_List_Profil_Ressource_Humaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:21] "POST /myclass/api/Get_Related_Target_Collection_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:21] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:23.488078 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:23] "POST /myclass/api/getRecoded_Employee_Image_from_front/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:24.302757 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.305756 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.310307 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.315308 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.321284 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.325285 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_Given_Ressource_Humaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_List_Manager_Ressource_Humaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/getRecoded_Employee_Image_from_front/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:24.342284 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.346271 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_List_Profil_Ressource_Humaine/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:24.355287 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.358269 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_List_Ressource_Humaine_Affectation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_Related_Target_Collection_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_List_Employee_Contrat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:24.365269 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:24.370270 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_Partner_Group_Purchase_Price_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_List_Employee_Suivi_Pedagogique_No_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_Matrix_Acces_Right/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:24] "POST /myclass/api/Get_List_Survey_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:05:26.040957 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:26.044958 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:05:26.046958 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:26] "POST /myclass/api/Get_User_Access_Scope/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:26] "POST /myclass/api/get_partner_class_Without_Scope_Action/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:05:26] "POST /myclass/api/GetAllValideSessionPartner_List_Without_Scope_Action/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:06:01.859332 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:01.863339 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:01.866338 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:01.871338 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:01.879848 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:01] "POST /myclass/api/Get_List_Manager_Ressource_Humaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:01] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:06:01.887850 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:01] "POST /myclass/api/Get_Competence_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:01] "POST /myclass/api/Get_Competence_Level/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:06:01.900849 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:01] "POST /myclass/api/Get_Related_Target_Collection_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:01] "POST /myclass/api/Get_List_Profil_Ressource_Humaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:01] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:06:59.619866 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:59.623868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:59.630161 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:59.634200 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:59.640166 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:06:59.641164 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:06:59.662225 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:06:59.671225 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:06:59] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:07:30.109347 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:07:30.113852 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:07:30.116963 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:07:30.119857 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:07:30.128859 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:07:30.130861 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:07:30.143860 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:07:30.146861 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:07:30] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:08:40.502708 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.504712 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.509718 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:08:40.514717 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.525228 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:08:40.552095 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.555115 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.557098 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.562099 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.565098 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:40.571618 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:08:40.615212 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:08:40.629253 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:40] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:08:42.040143 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:42.044145 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:08:42.048179 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:42] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:42] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:42] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:08:43.764573 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:08:43] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:09:06.571332 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:09:06] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:09:06.635985 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:09:06] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:12:34.506141 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:12:34.511150 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:12:34.515150 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:12:34.518152 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:12:34.525660 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:12:34.534221 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:12:34.548220 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:12:34.559266 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:34] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:12:40.609798 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:12:40.613875 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:12:40.617905 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:40] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:40] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:40] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:12:43.361080 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:12:43] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:15:24.896731 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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CONVOCATION EVALUATION
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A l\'attention de part 5   part nom 5

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Vous êtes convoqué pour une évaluation de type : Examen.
L\'epreuve se déroulera du 11/11/2025 12:30 au 11/11/2025 15:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 09/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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ttx9kB7oARSbstqdiAxrubiiy9e/KDUZTFixIji29/+dvF6jWLljM4hE1onoKCVxNCJxx0/ScGtVqTRhx4WJbhrtTvVgtalVGw6paH3lNS1R+pDbRaYa6Atar11BsdrVA+6GlZefoXYa/vUkxNllZoVujSOOuqoSGijKnLkCfvvv3/xjW98o/jZz35WeSajq8iE1glQztASpSUnyXHDo4+0NKuvudrqHRq/pnKdvlnS2Z/SoCqywrLLxof/byboAhi+8y7FSccfP4lkUzX+/Nlncc6Bxv33ewER6AoZOHBgJLSzzjorxtMSDjnkkGLqqacuXnrppcozGV1FJrROwI/wwAMOiD2KZH0S6OnrdTz7jDMrzyCND4rbbh1fXHnFFcWEUrsQa+7kE0+KzeD6ObUBUYRQXElqm+UxYcKEaKkYywavvfpaVKEw0ehnP5u83Qe4alq27r7rruLKK6+IY/fKI/lYO3fdcUdU2zBoheDhisstH+cI/Ptf/4ok+2awQB3Hddde26qDRrXX5+iJaWn6vBLI9pnXX3stNpub5JRalCxcLUvXh214kBdK8J4bwvtJCHEra8G1oCHHGk4QZ9IOZrbCtddc0+pmagV7/rnnw3WqT3zNAq1uCyywQIyVvVU1ZpDLOVP4PRhhmNE9ZELrJMhVa9bWGI5E9COS8SHmaCHDhMcmFCuvsGK02jSLU+7Yfdfhxd8DqVGw1VitWdpnNGOLBZ195lnxOWqxpLtJ5OhL/P7ll0cXTEO756nIvvTi5HdylhapH83xmsM1zO8xfLeosKFUgGoF9RCvLbvU0vF9SE2sSo/jyuH//T14rbWKmaabPpDHNTHrRh7J+bJK7Z/8ESAXTeaOy3EfHlxuIM7ovc7N5whTgvM2Wcp7nf+Siy0eruXEsXkJelldky2GbR7/1iR/4nHHRRWT+eeeJ/6b9uXYqH78pIaqbbPBTYp1Nm+4XtV9uiNHjoz1aO/X6E3N6BwyoXUSMlXkghDCRx/9KloLCGvYJptG6wSBbLDeesWcs85W3HLTzTGmRjfMTMlLLrooih8efcSRUWLHSLaHHngwWj2nnXpqVKhYZsBSxeWXXlY8+cQTMWhPOYJkkB87i4c8D6KqbmwXj2PB0QD7RSC3zYcNi+oYXGMqE/6f/I/Xvnf++ZHwBq64UiC0X8XPIhuqGCP23CsORmFZcYmJNl595VXxbyoXSIXFSdEDuTjHX/z8F9FaYgUOXGnluO1HH300Cj9yIQ0Kds2WW3qZcE4vxqG/yJCqSXUxKcttgfnmLYZuOCT+fd+99xazzjhTsd7gwcXLwYrUkG8bdOLWXXudYsnFF49Tqpod48ePj4Q2dOjQyjMTscsuu0QLrZY6cEbnkAmtCzjogAMjsXDfLr/ssijYaI4lICFWkAWZ1CQeDKSFLJIg4p2BMPxtelLCmFNOjduhFptgAPJss8wcR+VxXU864cRIcIazfPy7SWcZiN3df//9USNss0CurBykSSljv2ABcJMfCK8Dkl1p+RWiy8lC+02F0Ej4fPJxy/g5U6XE2FhaZKyd57CNN4lDfa8O7ue++4yIIo+sQgSJqFmsW262eSTPDdZdP36GC/lEsE642OsE6+/SSy6J7rp9seCq41801hZaYP5i441aFr5hKa71NcFiLEN8jTqu7SDxZsfYsWMjoW233XaTxM+cx3rhhjVPsFw7Ip2e0TYyoXUBjz3ySCQfAobbbr11scA887beXZ995tlIOttvs21rgsBAXuSy1x57xL9pdtUjNPGohNPHnBbft8aqqxXbbb1NJLYdtt0uZlSrM4AmMbGmNg9kRrrH+332xhtuiJLZYnzPlSaVs6S4a4nQjNwzET3Fo8waRXJcym222iqO5nNOtvtksLB+99vfxalMhq0gK8fGajLUZN999okWmOf3G7lvMT6QqmMjUrl9OH7bMh+UG55mmiZUExphyLlmm32ycXrNRmi+D+RdD2PGjGlNCJQhPjhkyJBi5kDauUm9+8iE1gVE2erVVy/ISLNgtttmm1byQhaIAhmkhXZqsLpi0qDyYzb6zQLfdaed49/A5URorJ8EwXiksMduu7daeyynJGedoIREHE98Kk2Gop5L0lrMj7ouCw3pgcQB62iV6HJOJLTVVlk1LMoWQrPQuHTzB7KWDACEJYngWIzYA0Tef/El4nVARmkmp1kFpsdTsaW/xj3lOqf6sj9/9ue4gFl1ZVQTmilS3PX9R+0X9+/x29/+NsbWmoHQJHuQFCvrimBFp++pGgcFSxOhfa+UTAJS6msEK3f2cMPraMlPRn1kQusiTCufdqqpopw2kcQyDAMWR+LSDdlg/Sgtve5a68T4Fbzx+hvRimP9iLdZ5CZMfecb34huWoKMKAlw2zI6b9gmm0Rp68sumfgeQD5mTxrB53XurvosJDr+1ltjhnDxhReJpGLwC3dTgmDpJftHUpFZXbRfvxjjKlsZ3FXzNpWqbDJ0aIxjsUgJK7KyNlx//bg9x7fNVlvGshZxQc+T3W6xQveMi9z18rfkA8VbNXBp/mkZYm5zhvchU3B86wXicgMwf9TjhOOOj27boGC5LjT//F9q7Omiiy6KROUx11xz1SXX4cOHF1/72tci6ZXBsps/nMOywb034T2je8iE1kWYiH5+RZG1LF0NAvasK3LXpjeR3U5kBqySG66/PtZQkdqmIvvC8y8UZ5955iTlCkAvi5Ui/mbOAGL4wdsTq8wTLPwTjjsuFv4iWMkGUt1KOeCxRx6N+9p3xIjinrvvjllKcTlkIzD//UCkV1919STJBqQx4dHHomu56847R3IyYZ5Vctkll4Rj2jUeE+vSXACquo7VOZtZYEpV6k/0GdanbdiWbZbnjCY434suuCAmGxIkRJS62JfPG1IDYpimv9cadTcloG5szjnnjGQ2SyBc/54SrPFqqxNYaF//+tdjtrMMvx2Etnqw+DO6j0xoPQg/7OpsZBksq1o//lrw3ra2BQjI++qhM/srI51H9WfrHZPn6x1H+kw5MN4ReH+tY/iywJo69NBDi//3//5fzFzec889MQ4mY1kNx67W7H/+538mIzRZ6GmDS7399tu3WUjcFbC2kT2r0X6Ui6RuhGa5jo1GJrSMjC6A5bnEEktE5YzzzjsvFiCTBRo0aNBkxITEEZai2meeeabybAtYeSw7WdBGgdV9d7DC991332LuueeOGVT6a/avuNexsCRZvm0lMnojMqFlZHQB48aNi0SEKCSCAFEgEEmLauy3337RQqNUW8aNN94YXdHLSrHTtvDQQw9FN7WeheV1+3JsCy20ULHFFlvE1qrRo0cXu+++e7QivcaylIi49dZbY6KlryATWkZGJyGjvddee0Vi2GyzzWJgH8HUIzQu5xFHHBHfX22hHX/88cV0003XocZ0rVEsQJahAu9qIEey3gsuuGBxzTXXxOlf1VC6s+WWW8Z9Oh4Ep+Wtr+ArQ2iamX//ySfdmp79ox/+KGYNywN2O4zwo/bDTo8vCwYC6zH99UeTKn04Jouy3rGl41bWIZifejctRNckyeFwoW4bH7b/655TEknHUu9YexpctSShzfqBRGjUZ6trBEEMjXta3YDOLURAHalBe+KJJ+I2ZpxxxtiJUcbDDz9crLXWWsWGG25YPPvss5Vna0O3hffZlsc+++xT85h7I/o0ofnB+6IVoypRUD2v+t0C7Apk7VStK3jtLE4/bWwsVzCIV8X9LjvtVFxy0cU177SdgXPkggj4thfotfxV3pv2/nBwTcrgdiiHUM+meb0M2USlGIp+773nnmK2784clUXUnN1w3fWxpGLsaS3XxKR0RcTV228U1LRtPmyzYovw2HTjjWOhrwzolCzdYGVpVeJCnnNOS4cIcOtkO2uR+WGHHRbdvHIDuljXkksuGcmuPSCh1VZbLRIQIj399NMrr7QQLJFIMt5+7x0Bq0yZiW0Z0tJXauD6NKFdeP75sfZqrtnniEWYKtPXWn2N4uILL6q8o3M48/RxsfhVmUJnMXznXeNntSXtstPOxYDwQ1Y0O3znnTskOVQPWq2WX3qZ4sD992+X0EC5hJalatICbVczTDNtsdfuu1eeaanId8yzByK/9+67I3kedsihsbQCkJzzGFO5JvuOGBkJrtb2G4ErLteXOmPsA9XTukb413VdbZWBxU+mUIEtEkME//3f/92atXTtDz744OhyKmGphsSBz2hPS2AVDRgwoDjppJMqz9QG8uFmUrq1DY9jj20RCXBDu/fee6PVZh+dwc0331x85zvfids74YQTOvT7aXb0WUKz0FWvq54nfZO+LI3gZfPa+8456+xibFiQquqrK70fDz/YscEiI5Nz7NFHRwtt7JgxlVeL2BhtqrjnNFLXm5q+x/Dd40J/qjKujFQQi1FRapJe1sytgZ0ckXqvcixG07v6sdODJcRStHg1fas9m37qqaPVd/+998Vzk7nSbqUX1Pu1WlH6AL2eswYL66EHJ7egxFwU+660wgpx2/Dee+/FImAFuwp9dSUgq6Qscs1VV8em+tMq10StmwJawekE21Wf5lhYbu2Vn7SFq664MvaKnlGxUNSt6UCYcbrpiksuvjiGFB4O56a42f7uDt8pUlYHR/HDsafv343E8Tz22GPx/5U32MYpJ54Yrfh6GUBzAZCAYL4hJwk77rhjzCLWKr84++yz42fuumuiwgi3sV+/fm12OigPETdLRJYepLwdn/Nl5Rm4Uq9Uph6ECyQNbE9crS+gzxKaRm4tM/oY6y0g0jwayRdbaKFi6f4DotyPglDkAdddc01c4Bb0CssuV/RfbPFIQInQnnvu2agiQS6HxTXXHHMUxx97XM07XSI0Wl+AKFZcfvm4PcW0T4fntQnZH7d47mBVbrDuulFayF34iMNGx+PTAYAIL734kkBg9xaLLbxwlONxjI5FfI9G2BKLLBq3M2DJJSLBkNz54ovPo8tZj9Asjs2DW2x7yBn0hSIsVhm89eZb4Zr1i/2dzhPx1iK05HIiVm1gi4TPkAyy7TPHjYuvVcP2tGElMq2FRGga5sGi3mmHHeJ3rVD48ccmxK4I595/8Zbvy3eCjEkzcZfTudFz87pC4FdffiV+x66j72Hw2mvXdMO45mJlSEA5RDn2tffee8fMYtK+KyNZaLfffnvlmZa4V//wffqO60HMTVwuEVlyOREneSnJBoQn2N8VCyupgLAs3+kFqiXtoc8SmubnmYNrckZwE2vBj8iit9ieDz8GdUSar7lPN914Y6yetygQhsWpiVoMzOviYbDJRkMjmamm1wmwblgE5HVqVfLrx0RoiPbmm24KbueOYVszxnYmlhi5n9lnniU2ctt3tLymmSYsxmMLEj8Dllgy9o7qq/zNr38TBSQlOqh8fHf66Yvttt66ePH5F6KlQRvt0YcfidvVZsUdcx7iTDoN6hEaiOul/QKCd84C0oB8+803f7FVRQ+uHqEhMpbKWmsMig3sSJZuGUtvkWCV1FrE4nP03tYZtGZdsUOEZn/Dd9k1Xqtjjz6qmHuO2SN5IXPXhbyR75NopTYvRCoJQkZp5hlnKA4LriGwdLmrdwQL9sxxZ0QrTwzwD7//fbC8351M2ihhq0DmSIC2WYqBummaraniv1bnwh133BE/k9xC7xeM10HQFi699NL4OQ8WoX3PEW6c3F3kuUK4iYnP1TvW9uA34pgRZXUGtjeizxIaGecW16Q2oZHSsXD3DAs2QTvSjNNOF9UsLA7upR7GhPPPPS8ubtvUIM66o8d1wvHHx15M/YnkdR4sxUkSEJqFznrwWHrAgKi+odnbnRG56lPkQgEl2/kCOZLj+ehXHxVbb75F3DdCOOuMM1sXEjdquuByWogp6/dxWMxcPFYUzTNWR7/5F4gDbo8cPbpNQnvzjTejBUjT//XXXg+EsHyxViCYdFwIbaGwra2Di9IWoSEVmVBWJYvn5ODGnXLiSXF7ekw1r1djmy22LGYJBON7ExOsBYQm6cBKdM2QFXf7kUownIXHeqP+QWSTxbvQAgtGtw7JacJfdeVVohXuBoUIJTeQKVUPN6idg+tIj64WEJFuAATD1StbcRtttFFsNK/l+pmM7jPHHHNM5ZkiuntiV21BfC0RmrkDJ4breOSRR7bGvlhn5ba6rmDnnXeO23rggQcqz/Re9FlC0z9JedWP/U9/nDwlTaMMoY0IbkICqZ2ZgrWjaZpgoYW6RXBTEhBJIjQ/ZISmcVt/pB5DUjkeb4dFX41koZHS1l8pfpFcYSqtSyy6aJwzkNQqIqEF94ySB1fQMBMa+sjBMe4ZtgeIGaEhksBoLVXpwdKcMyxO1thdd95RDB3SIsbIxWqP0GCbQFZij9RmHbPsZ0JnCE0pB0JbKrhVnneN9t93VHHAqP2Kn747ucqsZIv3k2MSm6sFhDbLjDPFa+G6vfPjd1pDBNzPLTYdFrch3nlnsIo01FMMSVnQg/Y/oFgwkJYe3KUCIR16UIu15magnEVzPbcYEdYavsICVvKAADSUp+8L1g/fn0yk76saLFyfkTgArUg+X61eCynG57uk4rFpIN5dd901fv6SSy6Jvz1kuEq4uZVnW3QW6QZ4dLhWtn11Sbqqt6LPEpp6K9LVCMg0ppdeeDEG0h8JrtAbb7wRhQUXCIt2zWBuc3+4R2Ip3i9wy0Xx+vLhRydlLjhL8tnr44LLiYxIViM0ahZgJJzt1vpBpxharYZsP+D1w8JjSaUgs6A3wj0p3JHFbd6vzBIQg2OhDFxppThzQJDb+5SBWGyykJIhLBHWigVD4QJJdJTQiDCKLYnXsVhS3A86SmgC3q4ZeR8k/Ga45vC3QD6uUSLzMsSeSBvRmytXr1vYyMr3EF1sMbTgLlaD2gcy42ZyG1nZNNgWDC5ymkPA8nJ9VgnWmxtSivX5DUgI2RfLeZqppoqkVw3freJVBLBouAmJzYFz5f4puK11bo7dIJRhw4bFvyUilg/WarV1Ja6mNi2NtNMnqk3pwgsvjGUfKXiv9er99xsj2W0KVSLL3o4+S2hA/sZdmEWDLFhBFpusJpw1blwxb1gA3MYVllsuvkbRATFYrEcdcUSU2Vk8fA6B9F9siWKGqQPJnHBi/LxYm8Xhjr9quFsikR223bZmPGOn7XeIckMsl1oQYxFbsshWWWnFSFrcvl9++Mu4UO0fgVqgSiiOOerI+DmLltvl2EkMiaMZvoJkxAfFo7hm4nPabmQ5p/n2t4OrOrlbnCBhgcimm/o7xbprrT1J1o7lSt4HubtGAvG2l2YHSMLIuiZ1XHJIrD3nxV32fXhPrUxgLXifwDh3Tu3XOuusU3zra1+PmeBqIMT11103hgqQ6DprrhVvauruqKOA70YNm9gZiaMUwLe9/oF8HSPrbNmlBkQpo2o4np3CzQMB6N3kxoLtiGkho1pAloL7Jqa7bty8ZK0lKPcQVyMzxKJDdiuF712h7PXXXx/3SZkj7bNRcCzc2epi3d6IPk1oYMGTfD76yCMjQUnnlxUHHnrggeLYY44pjgiWiwLSdMcFP0Iu4ujDDouTkLiBSLL8Q1d+wYo6PLyHq6rMw3ar8dwzz0bN/+q2mDJefvGl4pSwsLhTF4c7stgZWCykd0YHF/LoI4+KRJoWIogfOT9lCuJnrI3Tx44tjj7qqJiweO7ZZ4rxt9wag9VKRCQl0rZrgRXix+19r7w8ae8hF0sZCEuHy2LWgPela6IMxnkmEUrvMUNAnNE1OuWkk+ICTe5OW2AtcanEpSxmD8FrNW/lQb1lvBOs8NPGnBpczmPCMT4ZLWKuZPl7PSZcFwmAcWMnFqe+EazX9D1K+ogl1gLLMcWcEFqKLSIZMTV9lLW+f/tfKtxgEBKXUdlFuTgWXHPEMn24AZuf4H3fDTcmNyLXwTBipN5eJ0Bn4Hw2DzdACYdarVK9DX2e0DJ6JxAeC2XjjTeOE5Fk8rQbLRcs6a7on3EDufYkwk22Yg13tUxhhx12iITG4ko3KC4lIqrntrHsEAfFC1YY8itnet081w3Wpe2Krflb4Ss31j64oMjc5xqZjXRdJBrEz2qFSnobMqFlNC0ODO6x9iJV8SrsVcuLKdUreG0LssISLLKaEiQXBQu4K2B9OS7EoxYsdQUgR5X8bQXWkbLPKfdQf8a1T2BxLh6OzeusN7Afz7Gi1LtdcMEFxXXXXddhd72jELftyjVtRmRCy2hKUI7gfqm7Qhq3BTfXYi+3DnUGLB6zHYQPlLp0B6cF116AXlIgWVl33nlntCAF++shFdd6kOQuw6yB9BpSRFqSD8o2kgvLmuKGNxKSDY6lrVBIb0ImtIymA2tF8Fz1uhYqrqISBQHyerGzKYk0wWmGGWZoPZ4rr7wyWmhlq6saYl/UaX12/1KdHfc6WX3qy9SscbdtXyV/T8GxmzilqV12vC+gVxKau5dslfqj6ocMZRnubuRsBPxTjEBRp6D7ezVqgHoC+juVUEhGSO9XB8QdswLbX4S7vXPoCHyG1ZG25ZpYBJQevqjcxZ2795RLIMrwuuC9EoD2gvT/CPtTha9jotpKsB3STIan/CXsrz189umn8b21YmG+VzEd8aKUBZTxQwTVWUFwPSUmJCuqz+E/8bh+H/flOrSHzz79rOW4KkXL1eC2KjlJfZmykYL3wB1sa0gKqIVDUqw7emUJEjzI2jY1q/tujzrqqFjiUU5mNBo33HBD3Kfe1L6CXklo2oL0La65+hqx586EIANvtc3svuuulXe14MLvXRBLBR4ouRlqsRTd3nHbxL66ngKi0bWgFKClRmr5SWZvalMauuGGsZjTQylBvSr1BPV0yiZSg7b4zRabbR4/r4zkqCOPjMT4+Refx7ow6h7lUhKEJPsr46iOTnFxrdqpBIvUlKe555gzll+Y/K7mDpCIYTFKX5SaDF5r7djmVA9333lXHJ9njJ7SiptuuLHySkvGjYv1ja9/PT58n5r5JQYE4KutH9X9A8N77Ne2ZKLL8N0rxfD62oPWLJ55un4wXX+nbTku5Tfq6xJcm4svuii2n3ld3y53mDWlrhEMEBbAr76hlqEmkEosEilbXsg2ZXIV5iJnbiCrrdEuZoJ9LLbYYrGNqiwk0NvRKwnt5PCjJxuj7kp9mYWs7cjfqtETWAA6BqoJwoJXh2SCeU/Dj1V1vMr37513XhzAq68SoYBU+SEHHVzcctNNxbHhrmzBkMZhedQCK1MRrXo0Vt3nYbFtV+kMOPOMM2K9mx5WjfeggV0NGhWJBIXF/cJ1U0+mfk0haT0rDiFrI3KNFbPusuNOsbDVtCVQCKsIV0eF81N0SystVbuXIRMoKK/Ql6qIurqFF1gwNryD2ripvv3tmAhQCa8vdkD//nGyksxg+ZogdfNAjQrUo+lGIXPp3ECczLXcbJNNohqK5ng9rX/4/eRWIcJeasn+cZ7qJRdeVKy28iqxX1UhMjz80MPxHDcZunEkyTlmnS32UiKgq666Kr5H98Cq4TdY7zqCmwrtMedXJhFEJx5nexrfxdpkM9PErEYDSbIov/Wtb8VOhBSj6wvo1TE0agOan1lg1GTLcFe97977Yk0XAnM3T1+cmi0V/x0htFdfeTXWVdUjmAR1TPoVq3/QLJiy9aOo00J7tmIteC25SgKzrBJ9is6tFhTmKppFHsAaYvkRsfRDFX+RxdOnCCrzNx06NJJk2uYPAomOGjGiGHvqmNgvitCMoKsFtXcsHJ0BwF1HkPZn27TT/K3mC8ztVNiqHq8aaWjw9wLBgJuNvs4LK8N31193veJrwdWUBZQIoKLxnammirGpai1+zeQKpkkkgRo8f6cOAiMCKWs89mhLkH7HQPS+89TzWcaFYXE7rjQIetzYsfFvXQmgQR/xp66CocE65jYiIEF1GUKERE67LXAfZWrVfJWLWIUi1JfZHrJToCsp0hY5dgdq52RSdS4k0YG+gl5PaNxO7TWpEjzBlHAL252bNYNELr+0ZRBFRwnNHXVQsDbKFk890N1yl6+V/v5dICrKDwpQWRVbBvetXBgrLvPKKy8XZ59xZnAZ54/HV8/VINCo8p5yBeg/1RCf1DFYbSxA5532wTUtt10lYvc3y6stQtMJgKCOqzRVc29db430iFFNl46EdDwtah7fbb3WZSAG+3uw0gTNrUMUhxx4ULQE5w9EZlGnWq69grXt702Cy1kNljgyTMSp2FcLmOvDKnZcWrdSD+exRx0dJ8mLnVaDy+2mQMASbg5kwiLbf9SoSCprB8vfNU9SQYeFm+R/VwhNszlrlPtp6HBb+OEPfxhjaD53ZkX+CLTaIRfPe5D1TtezJ3BxsNbth35bR6S/0w3ZemMBs2jFalNjfnvx1ymJPkloRBcpWmh9kb15JVgZJoP7mxtqcXaE0Cx8VeNUIF6riDCW8Z/wn1Yg3QJIQ+zFEFxEIXieYIjv/IFcuWqIJok8JliE+kZnDFYBWWkEVwviMyaVrx3I5I+VgLouiOnCYkq9lGJn3DrSR3/6Y0vjNLfTAtWjWYbm6/YIjcVDASPF60gZaQ9afeCqxUsvvhTdNFYlIoWzzzwrEtqF57dYXQmuJetUS1UiVsSGSDT0s8BYZ1xOC9/NRIznf4Jrd3CVxA63e4fttovXKwlN2iZC23/ffeMNxPlT20hlFUkpJVldZWyz5VYxxvn4hMfj36SP3AxH7LV3/I05X6GNlCw45+yz43EhBS1ZDz74YAzqJ3e3Ht56661WlYwDwneeQD3Dc1xrfZupj7Mn4BjVwBmSUhabrAXnLkwgacCi8zlFzrOF35Jj5WIjX3HE9jyYKYU+SWisFgvFoiNDY8EKZrOOkJ0WpY66nG2BFbXzjjtFy0zA2I9+uaWXiWKRt958S+VdLfEebqsYF2sRqVm0CbFd6KabY1sT62rjIRtNouKQ4HwHrb56se1WW7VaggQYWWiJ0Fgn5H8QTcqYandiYTjvMjpCaGJGCCoRmju6vlJJmDdeez0u9oErTSQ07/P+6sZud3FuqmuUCE0gXqKBJcRd427NFMiTa6aui6z01wPJiZGVgRxNX+cWJkITJ6U6cmAgCkQuDiZxlAhN/24k2op7W4aYpOuTCE3Dv+uy38iRMWsrXovwEqFpWSoT2rXXXhuPleVDv+z555+vaWFfHr4r7Us+p1RCVlrLlMlRMpopY9pTYEkmOaI03KUWkJPeYhbczME69/62Hm48ZhqUOx++LPRJQuPaITQW2fHHHBvdDYtZDIcaakcttPZgkYp7Cd6StVl+mRY5GHMa//Ln2oJ7p5x0chRklBmsBdI9Fl6t2IYFJfGx9RZbtGbTxAann3qa2KcKXELkPXSDIfFv0AdogSaV14SOEBpXjlt4eEWx9u0334qBf1YNt0N8jpLvjyrXn7XFRX3ogclnChx68MExHndX5bojPcmZcYEgiAyKl80XiIWFqk1omkBQ3P1ajfQHHXBgtMjS7ALqwjMFq+P0MS1KKGSANOWnhMPBgehc1/vuaVGrLYObzILV7wpXBgL1+0i9ngbEuE7KQ0CWXBbWYpa1TOobYn/+RW612qoSmSBucTQqxeJnMrgmr/ck/FZZfiwr06GQT9lVTP9/U1g7FENSjFDygzKvJAXilc3Vw5qsPO/x4DKrHaS592WiTxIaxViLWuzDD8tXpQ4sZRZTDE2Gzt2eW6WCXGN3NcTOWHlpbFs93HP3XcWywTqrjqEpyxDIZy1RmmWlCFaL0wDrSeCdFBDzfvWBA4t5gtVSq4A0LtRg+rOKUlO04+JiyuApa0DaXFuB7QTlKWJorMQyOkJoZIuiUkY4rth+c/750TIShIcjRx8Rg/FaicRUWEWs1VqV55rqvZcYpePfftttoxLGcccdF12xdcJCQ3DbbrNNtGT6LbBAvEmkWE0ZZjz4DvfdZ0Qk+h222zbGSZM776ZlX+efd15UK+EWU/z9qNKqVIY6Re8VS3NcBB7LiQ7bck1ZeYjAtr4b9p0Ws3o0bVAyscogZA+rG8hZnVtvvXV8r8wiUmOlSQBQuu1psBjXXnvtWCunZKTct+k1cTFlIsjYOSErQpasTjdoay2B9+B8JC5YekpYfEbtoHOqpzY8JdCrCc2PL6b+w4IToC6Dbr3FKnZFNsj/c+ngsPAlTP3tqQKh3R1/oFL6U4cFVJ2Z++tf/hrcwxWKb4cvrL3eP6KN3LNyRhPosokbKddYOPzoSf+oS0uFnldfeVU8NvVgguIsS1I89ZICxx9zXFxs5fmOyIVVZD+xvCC4QeUYHit1vrnmbtUkS6CCgRS4b21l1Iyos13uon+5xKmkgOuMYFlx3LIF5p2vuPbqiUWjZShMlQWddabvBisvHOusswXraHRx6KGHxmA5a5O7znphrbHmWEu14PqxElldvv+5wnGxnJKl4UbGVUSYjpvIowRHLVigJNvTcfmM40okzzJL5+gai69tWLHK0kOLlkWPoFhq1STseJEJC8e1o4XmcxQ4zBkoW0s9AXE67qN+0nI4w34lMwYPHtxKSuJ7XE5ICaR6EJOmdEtFxOd9d7aVBv9MafRqQrMIxR0MiKiusPeaEgOunXQ8GaDk43MLLeZPPv4kEscd4Qfl9XLxacKERx+NmTGB5q7AtKX7wkI99+yz40PcqLwfx8ByOTu4g0oxxJdYa/WAlJDTAftNbJ1xrlwvweprg+vFGk1w3BbjFsOGTVb0+cc//ilaaZRf21pQimhNUpI5vj5sv/payMixZFmH5jO0tQh++5vfFjdef33clmJn1hOJHHd6NwOzLalW7BSsJN9fPWIHBCleSknYxKty5hje++l7McbouGyrreMSy/I9OC7fUfW18tsRy5NU8B2xXFItGgUNPaaORzO5AtvqCn+Bc9aPLgjHecstt8ShKsikpxvDNbRzGal5vF8RhXStERvrENGxHLn9yLX6OnYEkg1KUlwP7qeuDpbdlEavJrSvKk46/oRo1cletgckN0dwN5PgYjMBiWoBYtGI3XB7NHhb6M0Ox2vxeiTNMgtYPdm5NeKjEgmIL2nxKVNBsD0t2SMWK8bHgpKsAIQlfpesMu7+2LFju51djcmniqUmG0pQYEojE1ovhLu/MoRrr7q6+FeVi1uGH66snoB5W5bOlwlTwzWhy6yJ8Sh/EKvraResu2CRJUJbc801I0EhBLG05K4lODfS2Yilp6r/a0E4YM8994zkwiIEvwmdCMsss0w89oUXXjgW+VZblF0Bq5ayrrIO23ajmpIT7SETWsaXBmULYkksMg/V9kQNkUOzg0XGNbZwZQ1BUF1tVjUZc0W5m+11EjQSrEUTpbiSSRnXdXUDkZnlFmqzarR6iZuRoS6ui+SIUEKKF08JZELL+NIg9iYZ4CH2JBhdzqY1M7hXSQpIQkCMjRVmpkC1G6nzAVlz86aE5SlQrx4OoZApEmNFqmrdlGNwkVlpyf1tNLTfpQJicbVafb09hUxoGV8KLGyxJlk1i4xlU6t2q1nBQnPsFq0yDJal/2elQZm41HVpSq+VdGo07ENgH2kpE1ErSADB/E7Hx72XoKhVuN0oSLAgd98rd7faBe9JZELr4+B6dNXkl22lXdYRq8J77EdWt6NgPVhkiKGrSrRfFpBEqtlShyXg7/+5cqrm77vvvujOSXooZdDE3tOQLaWYK44nrucYXdeBAwfGY3PTaLSLWQ9uVvbpMW5c7WHfPYE+S2gffPCLWAahH0/B5A3XXT9ZYPy1cJclq6PHrhralQwU1gSteNPQ2t4Gpr72r+qWp47GqC677LLYatVWGUkCy0DRr2HBHcGbb75Z9OvXL/7glQ7oGrg8uElkidT8/exnE7XP1BsqvTBcWdkE9ylBkJs0k+Jg9XvicmUoc1E0PWKffVoKqdtJjljwBivbl33WK2EwqCQpZKRHUtLw/wpTUzmE9+n37EmkEiZDZByHQD+3099cY8mBVLIxJTBhwoSYsVbaooF/Srja0CcJTUP6umuvHfsm/Zj323dUMTL8oMndJFjU22+zTfGdb32r2HHb7SrPtkCRrILdVVdeJbYUmSM5+tCW1p/ehM//+c8oJpmmaztnEkf12q6qoVVK0Sq12vbAOiPceMRhh1eeqQ81ULJh3BGxlpNPPikWBtO0Mz1eh0fSsPOdGQA9MGzbsSu83WfPvYp//buFmLS16ZRA2muusUax8ZAhrUq4b7/1drHsgKVi5b95pAp/6c7VwzPPPB23v9kmm8baxX1HjqyrasxtS+1BHuJTfndqImVrk6qGh6nnPQnlH7KJ6sxkGPWWarNCbFxP8wo6oqrRSIiFyqA6f9p2PV1rl9AnCU1FuIWopSjBHax8l9BYrRF8k6FD47/lWZt+zMQCSWInWIT17jKsk5dferl45qmnJxkC60tkTaSCTp+32KqLNstADBqun3v2uUkKWOmDKegUjC5/XiO2/ficCe7Oo1xAysJIVobz0VjO6vzzZ5+1djW0HP9Lkx2/GrbFFlmk7o/x88+/iNfRZ7U6qcw/UoV9ZbvOlxiAyetiOQmuQSobECzXoaED4a1AQMCSTteaesm8c84VC3ZBCYpeUh0YrGhtVoqiQZM/ocs7KvVPWta0U7letklfbYN116t5Pq7RBuutV2y52eatrzuGet85YUdBd+fAAipbYM71oIMOil0AylDcUNoq6u0OHJ+uhG233Ta2i1HrkFxBZixEQpKJ4KckeAfG8bk+1HinVOa6TxKaim9yPONLihfVoB9G7VTHwJKLLlaMCT+EBJ0B7ub1ppyXoa4IKZLRXnuNQcHFW63Vurjt1lvDglozkEQLMalH2mjDDeq24JCI3iDcZVX2rxlcPVYljA/bMUV9ow2HRKUOFougrh/zDttuH6yPgwJJ7RU1yohdanVKmbZ9gst9zNFHR8LjlmkDog6yyUZDY5aLO+f/0/GvEY4/9UO2RWhI8KAD9o8WENlwZEHlY7NgqZwTXDV3aD2yrK71Bw+OPbcEN0GMiSvGwjGFnCuItBCj7ZZJhEw4ee1kXUscaCPTIXDn7XfEljE9sKBbhGyQodHAyj42nHsCYUnXp7o2yndI1n2eOecIVvu2sVuA+KSe4HrQwmSxejgX7T9lIEj7EcPsycXsBjRq1Kh4HLsHT4I1aKAMQhND+7LqD/1m0kBmZS1TKtPZJwkNcey4/fbhBzpXbISu7vNEBiutsELrD596xeqrDIwDNeDXv/4oLnCkpvm6rfS2xujbb7s9Lrhf/eqXMWZFMQPooOn7Sw3R9msB6jOthrv6issuF6WsHa8ygEQs3JjXXn0t3uXvuvPO2MBNBQNWX3W1KIukXeejj34diVmTNqKGoYEEd9t1eLSaPKc3dYdwN9cKhADcvTWvx+MPi0+TO3kiaIvQLrvkknh9rrv2umidmWae1GWpM1CBXaTfQsUjwUJgHY8aMTLq+h8dCEaJRpKcViN1+/jxsfMBkVNIMW4OAYNYljkF6RjowNGdcw21ktH3TxOLEIc+1t122TWqqujhRU4J1DRY4yy5MpAC8UnflanqPiMWWP27SfA9yhpqME+KEwaOTGk4DrVt9s8KMnuBFLg6sCkZL6uHpPMmGVGOe/Yk+mxSwJ3+/HPPiaqlLIdEAHDrLbfEYSLcGTAAQwzngQcmZtpMMTK7gDTOMv0HBGttcknpBNYIkcdbb745WljkrkFjtf2kRnHuIWUQfZvV0INpQb1Zo/0EkZn4/dgjjxYXfO/8qN2VpKfXCIS274gR8f/BPpDmGRXS3HTjTWIMEBA9cjikSjCxfPzrDw7HH6xDqEdorD9ijUmW290XUaWAuMfAQE5ianpFCUGedMKJxcwzzRS1s5CBhAPZHPVQXCaiio899mhsMNcEfkFFIBI5lQnN9yo2yvrzYHGlGwbi5DLuMXy32M+K0MrX2oAWv4WkoZZgsbmGZhiwCAlhUul4553aVe7cfllNyYx1gnXqfNWfJVd7SgDhnx8sTvsWi3STEMejXJJ6lr9MsLKvCJ6IpIDvPFtoDcKHH3wYXTeL3F0LOVCXmHv22aMVZlFKIFBt2Gv3yWVcBIW33nKrYtWwQMsKFgm0uijIGsZh2Mn6gdC4izAZoYUvlUVRi9BYBAOCpVWO24FFcuzRx0TiIkRIKcRgkURoLMKyW8VKWSa4gawcqCY0FhAXNUFTd8vxb9py/NzDcLeHeoTGsnOOe4cF7YdL+cOCSmTmsXBwC5HHtlttHVUxVllp5RigZplxxfQVKnFQM1WG89106MbRjQdJHTeIFDdEVJIA1197bXzYRxKXdJy+S5+REGHJlWWUJEiWW2rpyeZPsI4PPfiQqO4hgcDKJRlUrU6SIF7GOlOOcNppp8XznZJxItfCMGLHkK63WJ16r3Ks8suGUIA4nlhattAaCMFyMjliW6RgxJHIxSgBOOP0M+KDAmuMr/xo8ruymZ5kcapluFkEKX6UYhVcF5pmIFZmX+mO6V8uT9kNSqDvNe+cc4ZjndQdejpYOCYQja/04slW2WbZQhuxd0usDbhJ8841d+t4uEkI7dNPo9uXLDTHjwAs4hSI33348Bj3gjYttOAaI3FIMRwxsVSbNcsss0QLzXuRljgKUUDV8kAvzPs0eZfhOCiDbLfNNvHvq6+8slgwXHvuMLBSF1to4eKF556PSRLxtBTrdPNaMFyr64MbDIjRTSBh9GGHx/NP7mwZFtySiy4etfLaA7kjpRiC/WJnMrVqv6ZElwPSpObLtU9ZVseiCb1eicmXBao22sNkfdtKhDUSfZLQKNFSpHgw/NjuufvuOAHJ3dqPlmIsscNXX550ipCxaiSc1a4R/DvtlFOLh8Od2P8L7K8XLBdxmTJYEzGYHiwcZEcWh5sjFgQWr7s+RVSketD+B0QF1mrlWBDHYW0hVlJATz35RFyYMoT95l8gBq2Vkxx2yKFR4/+8c1pKLyxQQX66aq+++kosRVlx+eVb67E22mDDqL8GfvCOd/11BgdCeC5aO8ocZAId/w2BVJcIBJYImWQ4/a9aP0a1YoQouWjkciysb37jG9Ei4/ZwNWafZdZYrU66RqW8vr5E/ApPZQnFnq74/hVRspzb61qRR0ozU52H2CIrW6ZTAsOMUAvb+Wy80Uax/u2F55+LiRHXXkYYyJoj/2uDNeN7XHyRReMMhnpgmSFPSaE3Xn8jJh4E9ashqcHa9J3ZF0IXN+xpCW03B/VlLFtupvgdMiVlxPpuNrBkHatZoylJ1dPok4Sm5IE09LLBvfDYOVhQLwbLh0Wi+PK4Y46NsZgyxKgU0HIHSe1sMHjdmMGjmMrCqed+KDngprFGjguuH3WLo45ouctze5SA2MagYEmx2OiYIdlaeCdYh9xhLqM4EWFFpHnm6eOKFcKiHrL+hpG4uIySACB7KHAuBuRzCKo8hGVMIGbCkylzKPOqvs6De6vvDlnH4w9ultjVURUhTMc5auTkvYnA7TzpxBOjm5xiZ6sFy84kJxaZUoZvBStCBnC68P9LBNdQoiBBRbtFKYbm+Fwjx29otEJZ31WCZIb6NLFMbm6Swga1ZkIC6seED5RzJCC9c4IVLputXMV36zupB6RgNsNK4f1uIqsGYuc2lUsuZESVY2jtSRYR0vO+nrSQXA/FvIhUwapjIBg5cuTIKLvUjOAW+10YsFJt5fcU+qzL6cf858/+HB9pcVjUCKJeTdC///XvqFLqfb6A+PngnrSX+mbBpPf57L++mPh+f5svkH7sXqu3f3Cs9uszqard++M2/vq3lu1X9vPF519Eq44Sr78dQ/UPx3udV4L3ISPb8/9Q7/j/8+9Jz6UajktcUhaL+6Ncw3Mp86alSXsTt4z6b9ofsLwQmnot+3U8zruea5K+j1pS4QjXa7WI1z7dvJxzef/1gPB0KyxcKQpVClH+HKuMiyeDV0ZHtt1V+E3Q6teH6TE03KzFzBTSNnPL2BnBwncNiT1OKXwlYmh9FX7oKy63QkwUfJnQ2uKHS95ZZiu5oO7Q6txqQfDa4uSSNhNcU7plLCF6XixMiq8JtwYL19wABas9SWIJbsDasbjsjkeje3Ljy7M9mxFJRujYyszYKYFMaL0YLJsTgjV0843123l6GhY1IUFFlBZ6ynbSOWsr4ybju35wI2U9mykzd3dws1XcU1tNA3lZkQlnnXVWDHRPiWNGZtxJWUJkhhhIlC+44ILF8OHDK+9qTvCQJIJY6eKlUwqZ0Ho5EMqUsBTagyJPmUtN0EhgyJCJY/TqwVQhiQHxp2bBBRdcEGvMlKIgNedCVpqLzHU1h1PcqqdjQm5WyIzOv1gZd978AZYZC5gL3cxgVcp4UyJ5qjKHdUqg4YQmhuLOIv6SIPj8s/d6RkyuDPv2Q6iHeFx1Fn9bsbVq2Ee9/aTzr4e2jqEa9lHvmNo6Btvv6H7ae29H9lNGipsoOnWXTmj9XVT241+uqloqrqnXOnr9ewqOQUsTC42Cbuo3ZZGJYSE05RlJATahre+p1jUqo9Zn/U38kutLXZYE0b333tvafF4eUt2soKbiZmVWZ61McU+hYYTmjqHafbddd41V5CP33qe1pmuXnXaOjb+16n86Cq05bf0wHn/88WL3sO9tttqquOrKKyd5r/oghavqmw4+8ICY0UzwI1WysdXmmxf7BOtCVXs9+PHdefvtxU7bb1/sGH74Ks/LP0ZlGnvutlvMtml7+vzziUFqLUYG6m652WbFAfuNiiUY9SCOowhUC5Ks5+MTJvaU2t+9wS3aZccdY4nG7eNvm4RwFJnKVjrXo0Yf0abKgmyhIlT1ZLK/5bIU1++G668vttt667ivRx5+qPJKC1gPBgf77JhTTo4tSaA5Gglw1xKUhIwKVo1zV/uXMswynTKkawQrxGtUNDT5NwLq1JxT6qst46477ihOOfHEqN7hO1EmIymhY2GvioWpzisJOHqwkChYILlUFoKwTYLym/O7f/qpidllIEt1wH77xe/izDPGTfL7l/zQkaBNzm8mNd9LHgkjLL7YYpFYzS41WZ4MEGuHkGS9xEkzQaxR6Y44Wr0bYk+gYYR26sknRxUECgd0pPyAU2uR3rknH3+irhXQHpQo+OLrjZLzY1D/dciBB8bjUEuUGsARgLILaXs/IK092pOSAoH364VUn7TT9jvE0oByWUAZ2qcWXrBfceLxJ8R6Kft55KGH42sUTLVJ+fEpt4j1TIEoE/Qyaiynv6Y2bPBaa8WMWS0obzD1W7/i3nvsWSy1xBKx3QaMxNMjqXtA36GCX/MsQdmB6zR4zbXjuSrNQEi13CMuoqJgE8Zl9ZZfepmowpEI2lg63RVmfioJ6R8WmFo6+Ph3H8dOgS3DTcD5LL1k/7hwLXDTtVldV4abCui0WDXcpXfeYafivHPPLRZfeJFINIAULVo9oIjFTUKpTHf7EB2HXt5pw3aVe7hBlKG5X5uZazM0uMaUWZZbdtmoPJsITNbWsaW/FYfusMMOUW471XwpySFs4F+EtuyAAa2qLQZM+74VXfttOe9jw/eVoPdVx4O14ne3wjLLRvUQlo1WIWS65qBB0TiYZ6654zGsv+56rX2rzQ5dC1z16qb9nkZDCM3ioHKgdaYW3JlMJbdY/LjcCd2lX3/t9UkULfwYNCqXBRdZfpQxyPkgrmQJlIGwDL+1faTJUltv7XWilfH8s4HsAjncXwlMWpQG9SJJjeUqzYkLws/DQkKMimqroVzA4mBFxL/DtrU57bDNtvHv/UbuG+vRUumAQtA1V1s9Li61UX74qVj09UBOhuzqKa0GkkO+RAbBMapJQ16gSHjXYPFy6Z2rQtMtw48eHn7oodiYnmqxiFIqLH28Rh8qK9Yk8aQ8QZbHkGN/W7C6BfRVwqd/+lPUI0stU5dcdHG8CbxfadpPjepiYXobZQjTdlnGfht6Y4FumXYlRb1cp28Ht+R/wp1cnIUIQCTRMS1T2buKtwMp+L3oBnH+5bo8QD6uY7J0hoe/EYjAu2NHyINWHxQ7ARBzGobiPTwB0D+qvm3smDHxbzdbnSZ6VkHLFZUQc0jT336Hvl+zSL3GWgVdEAjvsEMPja6uGB69NccnpmffEi6KrHsLuJnOod5Nu6fQEEL7ayAnxZmq0H1Z1VAZT/VBpb7gquZn7h03dIdwV4azzzwr3sk3D+b5SsG8/l5FhFAhqR+KH6aF7o5WBsJgXZx8UssPCZJMjFYjLoEG9VQ5n9QaWGYTHn0s9kWmdiM/oM3DD52ZX42fvPuTaD1YzAnHBaJVEPrpp3+K1tDRpTvw5cHldAcWC9E6hdDeq1h+CH7FcI6svGq88cbrxdyzzxHdoATWhuuiB1HRZ1oI4E5PE4yrMubkU8JCWSa6T8DSQdAXXTC5/PO+wWLcMBB0coMMijXZnQDi++//LB4DWZ8ELVG+L3VaCnlV56faOha4nlWtUlRoBbG5ur4bfZwkeRKQruZzpPvow4/EoluuCX0x27Nd59sdnBhuBr4Xx+VmUN2Mj9DKx79LcOsdg4Z02Vmu3V677xlfA2KUSEU9lZs3vPjiC7FT4vHHJ94sttpii2i1FsV/YjcD6yxZh488/HAkWS6wm6r2tOeeeza+BizeRQOZq6xHBMAlR67c8rPDte1tmJKuZkLDXM5Hwo+TkoQ7j17Fcne9uxYyUpPkLuwOrSKcXhOSc9dbcrFFozQOXHLhRdENYMmZF3jUkUfGz1gAv/5o0nS5mJH+yLIKqzYad3qxG8S1QiCP1GfHMqQtdtABBxTXXn1N/Gy5C8DCVW1fHad4/rnnozV3U0kmRlcA4qTesHRVI7T4mrsusqQK4fU0k5ELGGV9dplcyZQlSewwxVTg8EMOjS1OTwS3nVV11RUt7hwgbMflRiJuSe016frr3bSgxYrKYG2K81l8yaLkZqvUV7VPWgjplONPlGHpi/3m17+JpM89THFK8UDXAaGLPQmss5aJSFargbjW2sEs8KuuuKKYZeaZI1mQvfHd7BbcwU2GDu2QSm4tCCW4uaTaPC67G1pqYAcWvJYpclHv/+z9YsYZZiimn266aDGq8eJuLtV/QLjhjA6/kwNjLJG1JjGQQESybA3DAaP2i83/n3z8STE4uKis9BRmERv0Gxa28ODyJnki4YQBwW1HXMpGgDv+3ZlmiseydUXOKaN9NIzQgDrpiL32iq6L5uVUq3PySScXqw0cGIPO3BQkIhCfQC1iycUWL6656prinrvvCQRwZvHd8CNL7T1665YKP8rf1hjSmgitbLlx7VhHb7z+enEKQgsuTwp4Sy5stMEGMaDNzdLoXCY0rTU0tVgXZbirLhrey9pK4GpZyH7UFo14UwIVC8fw8osvtRBaeJ2bBbYtmJ6axstIhKavMYEMuBvAU088GS29FB8EfYoIzbW2gNZaY1Cr5eFcnXtS3khIhOY7+mflPH/+/s9je5XWJ61GCC1pqgFXUZ8kFwqhsawToVl8VCx2CJYVckp1W6r3KWWM3Gciof0okAZCE2qgNMtVnX666WPjupuOAPmmG2882fXnBrMAXYsjDjuseL50fcq44/bbozWffjvIiDSU5v+EfcJvlP4aq2jJ8B2xgjYP1wKScGO/YLmzFFldWrGqkQhN7DSBJehmyb2uJrTXX30t/Fb6F3fdcWcroQmxIErdFLom3HhdUzf5FSvFySzejI6joYQGzEwLj7V29BEt7SGnnHTKJIQWLZ0bW9QgALmwyOhYkfBxV/V48YUW3aoLKi5kLfkeixZZCConcPdYJsgOGS671FKt5MriWyVYi+PGnl48eP8DgQwXKl6pNBVzDwSKuQrVsBC5qlde8f3KM0WMn3AdWUICwGVLSE+j/SpXoRiB3JKVIC5IrpqSbDVeeemlSGhlMkF8MmksWgR18YUTeyKJHLo2LC0uMEs41SixZn0Pho9UY6+wTZZQsuZ++IMfFIuGG8PmwWrjajoG7mGCJA+r5p//989i1512igs9kQ7xSb2aG4YbhUV4TyVJwRLdfNNhxfBddo5/w7NPPxO3bTFTsO23wPzRRWWdaFTnopYVMhK4xhddcEFx4gknFMcfd1xw+SbVNAO/PdaX7YsBugmsFqy1OWaZJYp4BnaJ70tJIplkirniZqmxnOKrc1g3EBMgmJQoKePZp5+OhEZ8M4FqyXbBvdZqJtnC2k9uF2sXeT77zLMxpodQxeeUtwwIvyt9ozLaPAPH5Bg0npctwIz20RBCcxeq/tItliQBQ864LUI7c9wZ0VWVGaoFChgWbbJwqiEovkNp0AmVWvEex/XQA0hr4dbAsIU09xxzxsUqxiZLeHPlWH71y1/FbNMZgeyqYUGxNg4/tGVYih8qC0dJA0gOEBdMP2AuDxWOf4UF8cSECdES5DIDS3becIdmTVRD7EnD9zlntcRM/vrXv0QtNkkCBLLuOuvETGqC+NS2gQTglptvjgtFtgycI7f3qRqlC2cHK1hMMEkbORZul4X02KOPxWzv2Epwnvu3VnBl07lTpUCsSViRysgCwSrSXygG9HpJpJJkD/WOZDWyVt0YBIvFFFlo3E37PTRcMzeis8LvoStwXckHIZKbb7o5qpWY9kXrTYwPmSq5KCcFVN5r9k6lGOJkjkUpSVtwo2Itu2GCm5okATEAGH3oYfG8UxILGYt1SvK8+867wUKbp1g2nCslCu1imut5JkpDENn/BquRSGd1hjajbTSE0ARKWVRiZ2JMLC7qn5dfell83WJkwcQYmh/xPPNM4gIk64c09KMPP1zcW3E7U3r8umuvjW6KxVAtnwx333V3dDOoKbRIP/eLnwEN3ciVmylG58ctRsZSA/EdstQUIrgIKyyzXGsCoRq2vVBwRS4L58U6W2TBhYrHJ7RYUoL4jmFccDuVTCDtKy5vseZYKuJVyiRkHlk3Ske4FrXAcmN1kq9xLZdbeqnirTffjK8pp7A4L7rwong9HMNDD7RYUqSwuVGsOfuhdbbT9jvWbNoWn1w23ERYanfcfkeM8ZlURMdMtpLMEquSiCKpcseT3Kv3fvpe0T9YfqPCtSPL47vdI2yHnA1SKxdSmhNgO4cHN5H7Z+GOOaUlMwhGDCJDJDIbFYngln3wQdcmFLGQSUO9VLHsE2STbX/11VaPQoxuCkPC78HNY+lwDbYPrmW6EZ0QLEDvnX3W2aL7yxrdf99RNW+2spLLBSv85ptuimUrSD7VF775Rkum1U3Azdv1S+Uq6hWRqISIwcSugfik6UwLhd+NBMXMwWrcbuttosUprkgxxvedCa5tNITQLBjaWRuut34csuHuZyGkhSSeJGAu6CtOooaqPJEJpKS3D1YWORzkgzxSjMZC3T9YXSRuLr34kvhcGd4nHsPFUFph3+kHCu6IMnOUKQ4I1o3yjAQk627KNWHyc5/qgYXEchKg51I4r/9ULFP7Yw201LmtN1lxLxIQu3EMZIrKxb3VkFChfzYoLED6YoQME/ygueCCz0pV7g4kXbaO6XjtvP0O0eWSRW2rbon7w8UTuN82WNPKEnasWJxuJkjNMXDXyCSVoa6QRer104LFdmNYtOq2KEFU47577i02Ccfqup1/7nkxTJDAUttlx52KbwSXUyN4OT7YGYgLSmiwav5SydwmcKfXCtcLUXlsv9328ffl2iBwOm0JqdNh3cGDY0zM+DtlQ8mCK8MNSTmNa+BmXE7kAD2+YRtvEuOa55x5VgwFEGLUlM8qHRbWiWuPrPx+FaFKAiwZbhZqAt3M0kN9p3rB8m8qY3I0NIaWXM8UCO0s2vt8rVhGGT5X77Np2/XQ3rbLaOsYu3MM1WhrP+0dQ0f3471uPHovLeQTg5VT3m5Hz5Wr5PMsnPLNJKH83mqwYFlOPi9+lDoJGgWab2nknEdS+LglWG5qzB4OXgE4PplMWmfKWDqKjlwjN0PijKxYccrUsO2zLFqk6thWDJaaco2MrqHhSYGM3of3g8WqpUczMdnkzgIhkbWxIPUcdhasjjQhSIC8kVLWLM1BgwbFbXPl/CuTCYpWxavUCiYgmHqSR10Fi1uihAWLzFJxLriZmHDuuLj83//+xKRTRueRCS0jWg7cPQHqrrTWIA0yQKrZy10enQFXTKZTCUVZf6w7YCmywhC18getS4gjTTLn9hnQm4qLewLIUfZWWQYyq5bp1iGBVB0XPbmM7iETWkYcVGJBGf7RFbBwTPehXNtVKLhWi+Y4jMRrBLh5SIxlxMUzOg9pUrFA3BICspw9BbFfViC3VnysWs5bUoIckHMmS5SSYBldRya0jDhT0qKiKNEVSAj4vDhQqk3rChTk2o5G8JSF7g6UQ9ieuBS3Gqn5m4S2obymi9cK9jcCyExcEZkhK5nzcmxRgkCszvEgck3pZbLL6BoyoWW0Vsdzz7qCNPCWtE13QBeN6yuW9M4771Se7TyIC4pL0RJzXKkPkgKE7XtO2QT12Z5wN2U/kTOrlYIHt7NMVmKGyM55Og43hFQMndE9ZEL7ikPsKqlJkEymlX/XXXe1qaNWBouMtaPavrvKpILn3ED9oOJ6XcElJKLWXz+ej4cuBNOSgIS158SzjKJLYgGNBII0WAWZIrNyT3OC60vfzHlyeXuLJFBvQCa0ryhUycu2DRw4MKpLWOhzzjlnlNDxt8B5uUC2HmTpZBEF3btrZSjXSNYiC6azYCGussoqccSbAlXbocefilFJ86jz4uolfblGIsXsJEfE6WqVn+h7Vcjr2BBvueE9o/vIhPYVhHjNqaeeGgPk3CKLiyXDYmEZjRgxIj5HIrs9cO+QYFLL6C4IAjouswnaQ7n2yzkhCgTGXeVOOof99tsvunhiaIQTWUYTqoqEGwHEjiiRmTmUtcgd4Y0ZMyYel2uWel4zGodMaF8xUHfgbqnJ4mLSxzeDEiEl90jjNyvHNPD2Fr8CVFZPR8ivI7A97pr9a8+CaqKUrURejl3dm0LUww8/PJY/kH4GcTPEofIfEK8KfYNGGg3kNWzYsNh1oGi3XkLDDE1k7bh6o75Zb0AmtK8QkIVK/KjIGtxE2lv6cLma3LEy0gi3cePGVZ6pDYoRCO3ckh5ddyATiKwE7xGAzKsuhtTwTlMulTp4OBdWpmPgJqdM4oUXXhjLNdJxOT+j9hoJgX43ASUZMqduFLKbtaC0JY34875a3RQZ3UcmtK8IuFwHHHBADESzfmQUQUbO39UuHovG/EcDbpOlVAtHHXVUjLl1plWoPahDs/CnnXba+C+yMFIOlFmQqGZdpoHGHo6hTKqKc5Gd83SOCO3Oqr7X7sB2BPMVy7IMZTXrlYAQnUxxMy1eFE7qtUpldA+Z0L4CYIWdd955sUyANTZ27NhWC0E2E2lx2aohwM1SSlnCaohNaWZHOI2crclylIlMREWeO0EngmC6f5WLpISGc0tzDEAJCvcOiXM7xc8alU1ERlrEdBmwAo8//vi6pC9u5tpzR43AY3V2p1Yvo21kQuvjQDqas2UhLX4B/6RNBvomkQFLqwyLlpwNsqARVsuiECtChjKlaYpWI0CmiCVp3wbtlmNoLEEZRPtW34WovM+8ynIfqlmW3FCxQv9yQRsFGVJkpuH9zDPPrEtmrLjnn38+Zl5ZcRIxjbxOGZMjE1ofhxiPSUwWvbhZdeM3ElDcWavdiMa+hShGVAtcLAkFA3AbCRlLVp9jduxlOH61W2JVWoUMsvU+7md5DoQp7pQtvCbhUd1D2VVIkshmujko3m3L6kO6w4cPj8fgM11p/M/oHDKh9XEcccQRcUEhiFo1Ty+99FKMVaXgf9kSE+sRR+Mq1apJU0jLuuPWNTLILYvJlXPcu+yyyyQumuMrF6smyWzCkuX4mGOXLWXhNUrBQpmFNia6cddee21dgc4ErqZjY8USdczoeWRC68MQBJ+vogaLJGqRjkJPbpmJ59VAJKwbcbRahagWqW030p1jZWmSt10Phbbc5npgrXkfty6NmAPnKq6nTKURULSrx1RcTjN/2W2vBR0YLF+JiTR0OaPnkQmtj4JFtc8++8TFLnBfr82He4ewCDPWgliRbdRqa2pUD2cZ3DTxPJOQzCeQzewIoYnj9VQ/pHgcvTjWqHOtFU8sg2vJknNczqO992c0DpnQ+iiosApaKyZtS19MwoAVoe6sFmjeW5j6D6vBkmKxNLonEoFx58Tn9EO2ZQ0lpRCKGo0qySiDu6rAmNudSkfaAndY8J/LLP5HFikT2pRDJrQ+CA3SFriFLgbVFsTQZAHpdtVCqrgnUlgG8hDwFqeyaBsNrid9tTXXXHOSmFk1koUmOVB2ObsLLqtGd+Uj4nPc9/aAiPXHpunxVDS0RGVMOWRC62NANEoJWAjzzz9/65i6ehAbY8nViqHBaaedVtNCI7stsyjo3lOlCLKrLKN6rURQ1lBri/g6A/sTF0T0+jKT/n97YFUmpQ/dALlEY8ojE1ofg4HKFiFXELG11zCuaFbWrp7LmZqpq8seWFA6DBBaWzGu7kCpA7ezXjaRFaXDwfGx5pBsd6EURceBbdp2Z7KTyVp0zN3Rc8voOjKh9TGoqreoqLGmOZptQRbQ+8vV+JDiPiw0Ra5pMlICN1MGVX9kT7hVJH8QMyuwrfIIxb+ytILw3U0K6LfURSFJctxxx8UMcEfBvTS7gFXXkVhbRs8gE1ofguA8iwlBsc46AqQne0dupxaSBVQdQ5PJa8tVbQSQJWunLZdTJT4S6Yp+Whl6VwlAigmy0MpFuu2B9ZqKl1lpPTl0JaNtZELrI2BRkdJRHY/U2oudJSRCq5cUoM5hoSqlKBOLRcwi6eocgo6A8qvC3rbG2rHKdAV0R7BRXyjdNFZtZ+WFqH8gQladOB6CzfjykAmtD0ERLPLRHdBRN1BvJJet2uUEcaCk/KrVZ/z48ZVXWspCyG5Xu6KNgngYq0dsrCebubV3qdOTJe0smbnGms01nns0SkIpo+vIhNZHgGxYZxRTOyKdncA6oSdWq9qfcCKpHjM3EZvMaSqi1UYltqaOrScg0aD31KzQngIX3TwExbtd6XbQxykxgvApk2QVjS8fmdD6AGT7uIQWFhXXzmQd33777VjeUR1Dsw0ulG2yXC6//PIoPaRZ/frrr4+uFRnpntLEp6TBdR46dGiPEAXSV+M2ePDgLqvYJnecq5oHnTQHMqH1AdABE88S0O6sC0j4UXN6kqpOUFDredtMMaw0NcmUKPVWFFh7KgAuNsWlHTVqVOWZxoFSh95PLi3FjK5A7FBrFguWJZvRHMiE1svBekm1Yl2RmKblxeUsZwmVLyAvUteskFSwighS4aggOFf0d7/7XXyt0UDSXNxawpPdAXJW+c/6Y3V2BQbJ6B2VXZVNbisLmzFlkQmtl0PwXKyJNfPII490um9QPRlL67DDDqs8U8T2nSOPPDJutzxTwLZT8agHC6eR7UZl6KFEGOVERHfBjdUStvzyy8ftd6Ug2A2AXJLzJ6vNZc9oHmRC6+WQnZSltFB1CXQWFrnSiL322iv+zYKhakv+hrunFKQMMbM0+k5msKcULhS4yqx2pDi4PWgHS24m8nbNutJVIKupHk8XhrhZI8k2ozHIhNaLoa0pWQsEB7sChKTin0wQiKmJK9keAqjuR9QaJBlgnwMGDOgRd0tcTnbTDM2O1tPVg4SJY2ZtSn6QAurq/FD6ajTOuNvmCGQ0HzKh9WIgH64ma6GrhaXairQXqWEDrph4GkFIahPVkjziaSS3EZrG8Z7IcrISqbwqqegOHDsX0bkhItnZrhIwCaPUDeC4EGVG8yETWi+F+I+2IwtM4L6roMsvwJ00+QXKuVLqqqrdzQTDdO2Xq6uHsdGwTRlWlmJXtcR8Tnxwiy22iFlZmnBdjffZluSEJn5WXk/IJWU0BpnQeik0b2vItli1/nQHXEsZS+SGrFS9EymsBxprCM0Cp1rbaCgh0SfancEmGst1ACirEDNrq32qPSgmNl2KNtodd9yRNc6aGJnQeikM7FCp3904E9eJC6neTHGoTGm9RnVgraQiXg+k0cjCVy4tchXT60yDeBlKPvbYY48YvOc2d6e0xLYcC2tUS1m9YcIZzYFMaL0QrDNZQISiALarQE6yfdwyi19GsTpmVgtKOhKhqeeqR2jcYq/51zG3lxF1PFqpdCSog+sKEJDsLAIydakrmd8EhKrzwnnqmuiuJZzR88iE1gshC8iK4RqqGesuttlmm7hoO9plQI3VWDxxLuUiYkoSFAgRwUoqqFcbNmxYDMgjTLMB1lhjjRjva0tySNZWAF+nQGeBzA455JB4Loiou9aU6yGjKfGSJzf1DmRC64W49dZbY4wJQbBquos0DLej8yv33nvvYquttooiiD632WabRZcVEXGBZV0NFjGghVvM+jOIxXu1Cyls/fDDDytbmwhFquJ5LKzOZiN1NyRXmHXXmQb9WvjFL37ROpXd5PiM3oFMaL0QqvpV0bMaukNoPuuhkNbCNeGpPajh4mayXpR2+JyHoSASBGJy4mAKdpECC1KRrpIJhEnyu54S7AMPPBCD+HfffXflmY6BhXjiiSdGN9M5dLd2TXJEltd5cTWzYGPvQSa0XgbFnWq0SAU1KqbDArF4O1L+Ia6k6FUiQWFtIjTZ0e5ALI/lpp1IvK2jUGdGJpxrKBHQ3ZF69i32phvC9CZ1dh2JK2Y0BzKh9TIY2sGKkXlrVHGnqnek1JFRcDoIvFf8jrSPBnLW4sknn9xla9Hnbrnllrh/VlxHtyPgnyZcIdTuDiaxXxakujzlMN3pKsj4cpAJrZeBogZCEXjvKoFUI42q0wLVlq4XNzLtX7xKnEpvpL+VR3QVzkMvqfhbW0OFy1BXZkAK4tlggw1i/K27lpSuCTMUuK6s1lpxvozmRia0XgSZP5LUtM9kFRuFNLZNHIwLVw/KLlKXQFLnSOob3SmwVawqocA66gjEuHQ0zDbbbNGa0vbVFeWMaqTrQCLJAOaM3odMaL0IBt5acEOGDOlSWUM9SC7YrmzkhAkTKs9OilRrZn6ninnlFYBYfJZ71hWIeSnrMDC4IzVjYnhao/SR9u/fv3juuecaUrnvvFl7WpsQbEbvRCa0XgKEksoSGj067qabborb9ajVm8kyU1/GzfNAJqmUQQYzVeR3FshJj6VSDaUo7UHA3gR3yQjusa6GrnYTlGEkH0tPSUlHx/9lNCcyofUSIDRZQO4myedGxc9AM7p6MbGjq6++uvJsC8SlZP1OOOGEmIlUkqE+a+TIkfF1bUWKbHUPdBbKLZZZZpkOyWw7DkqxMqwykIitEeUU5JFYm+r6xM8yejcyofUSqPtCZko2kiR2o4AoEBoLTUtVGYQR99lnn6hcK6uKSC183QLAYqOP1llCsy1ZUjVtHSmiffHFF+P705CWRijlukkQbBS/MzAl15v1fmRC6yUwmQjhcDsbVa6RkKaP2351ca3iWSPsymoVEgE6BZAbMmI5drb3UswMObM22wvoq72TXeXaGjfXiDkGLD7bVSri/BT7NtLqzfhykAmtF4A1ojQB4VS7hI2ALCG30fZZYwl6IUkUIZG02P2LjDbddNP4N5hrqR+0o2UTyi2QmXIRpRJtQWnIoYceGgnXMJhGlVKwzpCkRIAOhZT0yOjdyITWCyCjKQgudtXdtp5aMD08yWrvvvvurVlDZEL4sVrokfCiZvMECq4ItyOlE+J14mYKgzWTtwWuNSkjx6XpXL9mo0BzzcwCJKm+LqNvIBNaLwACsajVoPVEnEftmTiSfWg0T5aWroBaLU0ITmaSdcX93W677eKjvZYlWUnnIKPYnkoIUpV9lajYddddi9dff73ySvfx4IMPxsb5TTbZJE6Oz+g7yITWCyDDiGy4aj0B3QFKMexDUWkiNHE71lQ1iXJ7lU4kfTM9lNzOtkooxOm8hxIHBdj28NRTT8VEBfkhGmmNAqtQHZ8i4jy1qe8hE1qTQ5Zx6aWXjmRz2223VZ5tLATZWU72QcMs9S9qr6o12UnN2MILL9xKdPvtt18kRBX8taDBWzbTZ5Bke6DSQeSRu3v77bdXnu0+WJRUObia4nIZfQ+Z0Jocsm9afJBao8s1EtKgFITGekn9lDKcmtCrhR+VUNA/SxOfEJo+zFqlFG+88UYkRZaZuFV7U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CONVOCATION EVALUATION
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A l\'attention de part 4   part nom 4

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Vous êtes convoqué pour une évaluation de type : Examen.
L\'epreuve se déroulera du 11/11/2025 12:30 au 11/11/2025 15:00 , à distance sur la plateforme du ELYOS. Vous recevrez le lien ultérieurement.

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Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Cordialement
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Paris , 09/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\n
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', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:15:25] "GET /myclass/api/Send_Evaluation_Convocation_Participant_By_PDF/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/690f3bd5a00c978d63f0330a/690f3bf4995b26cde9611a59,690f3bf4995b26cde9611a5a/66dc4ddf75b3f60c3ea43084 HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:20:18.123871 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:20:18.124870 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:20:18.124870 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:20:18.124870 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:20:18.124870 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:31:30.370419 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:31:30.370419 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:31:30.370419 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:31:30.370419 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:31:30.370419 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:31:55.380013 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:31:55.380013 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:31:55.381013 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:31:55.381013 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:31:55.381013 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\main.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:34:17.549475 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:34:17.549475 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:34:17.550476 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:34:17.550476 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:34:17.550476 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 11:35:27.973801 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:27.980833 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:27.983867 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:27.989835 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:28.002872 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:28.014881 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:35:28.046591 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:28.052591 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:28] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:35:53.456530 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:53.459505 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:35:53.464504 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:53] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:53] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:53] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:35:55.165223 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:35:55] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:36:10.833419 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:36:13.079001 : Publish_Unpublish_Participant_Evaluation_Note Le champ 'tab_participant_note' n'est pas autorisé +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:13] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:36:57.150908 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:36:57.155886 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:36:57.160411 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:36:57.165409 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:36:57.171393 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:36:57.179414 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:36:57.190393 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:36:57.195392 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:36:57] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:37:04.264174 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:37:04.267828 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:37:04.271831 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:37:04] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:37:04] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:37:04] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:37:05.811152 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:37:05] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:37:11.337191 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:37:11.355204 : Publish_Unpublish_Participant_Evaluation_Note -'publish' - Line : 2114 +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:37:11] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:37:49.123239 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:37:49.124240 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:37:49.124240 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:37:49.124240 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:37:49.124240 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 11:37:49.181400 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:37:49] "POST /myclass/api/Update_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:37:49.199384 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:37:49] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:38:46.352494 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:38:47.170298 : Publish_Unpublish_Participant_Evaluation_Note -update only works with $ operators - Line : 2124 +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:38:47] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:41:17.544672 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:41:17.544672 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:41:17.545672 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:41:17.545672 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:41:17.545672 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 11:41:42.333628 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:41:42] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:41:42.402645 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:41:42] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:43:29.416769 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:43:29.421769 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:43:29.423770 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:43:29.430769 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:43:29.435768 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:43:29.440767 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:43:29.448817 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:43:29.458771 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:43:29] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:44:10.700551 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:44:10.704979 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:44:10.710806 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:44:10.715812 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:44:10.740341 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:44:10.743325 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:44:10.751421 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:44:10.760377 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:10] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:44:14.456357 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:44:14.458343 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:44:14.462353 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:14] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:14] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:14] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:44:16.339091 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:16] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:44:24.184641 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:24] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:44:24.298015 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:44:24] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:47:17.790489 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:47:17.790489 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:47:17.791489 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:47:17.791489 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:47:17.791489 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:48:01.949125 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:48:01.949125 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:48:01.949125 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:48:01.949125 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:48:01.949125 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 11:48:02.021837 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:02.023851 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:02.024873 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:02] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:02] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:02] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:04.821401 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:04] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:14.105091 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:14] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:14.217127 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:14] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:17.134616 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:17.137613 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:17.142119 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:17] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:17] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:17] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:19.491003 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:19] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:53.706145 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:53.709144 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:53.713130 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:53.719142 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:53.731127 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:53.738126 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:53.746142 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:53.760142 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:53] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:58.143294 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:58.145292 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:48:58.149293 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:58] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:58] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:58] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:48:59.494122 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:48:59] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:49:21.055314 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:49:21.058318 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:49:21.062317 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:49:21] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:49:21] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:49:21] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:49:27.039536 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:49:27] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:50:33.259488 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:50:33.259488 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:50:33.259488 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:50:33.259488 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:50:33.260489 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 11:50:33.525000 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:33.530002 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:33.534026 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:33] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:33] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:33] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:50:35.018081 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:35] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:50:44.008138 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:44.011140 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:44.016141 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:44.020154 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:44.023155 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:50:44.032141 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:44.037139 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:50:44.052159 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:44] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:50:45.399239 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:45.402237 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:50:45.406236 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:45] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:45] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:45] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:50:46.918073 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:50:46] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:51:18.524993 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:51:18.525992 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:51:18.525992 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:51:18.525992 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:51:18.525992 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 11:51:18.980419 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:18] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:19.079578 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:19] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:42.296209 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:51:42.297210 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:51:42.300202 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:51:42.303206 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:51:42.306755 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:51:42.311765 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:42.332269 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:42.337295 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:42] "POST /myclass/api/Get_List_Evaluation_Planification_No_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:44.087817 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:51:44.089883 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 11:51:44.094901 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:44] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:44] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:44] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:46.701877 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:46] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:55.081055 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:55] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 11:51:55.153582 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 11:51:55] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:54:54.232880 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:54:54.232880 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:54:54.232880 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:54:54.232880 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:54:54.232880 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:55:32.220297 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:55:32.220297 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:55:32.220297 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:55:32.220297 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:55:32.220297 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 11:58:29.398378 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 11:58:29.398378 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 11:58:29.398378 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 11:58:29.398378 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 11:58:29.398378 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:01:00.685249 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:01:00.686234 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:01:00.686234 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:01:00.686234 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:01:00.686234 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:01:27.795542 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:01:27.795542 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:01:27.795542 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:01:27.795542 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:01:27.795542 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:03:10.550659 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:03:10.550659 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:03:10.550659 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:03:10.550659 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:03:10.550659 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:04:57.663791 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:04:57.664797 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:04:57.664797 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:04:57.664797 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:04:57.664797 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:05:23.808105 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:05:23.808105 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:05:23.808105 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:05:23.808615 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:05:23.808615 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:05:46.068534 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:05:46.069534 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:05:46.069534 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:05:46.069534 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:05:46.069534 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\note_evaluation_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:06:51.391416 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:06:51.391416 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:06:51.391416 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:06:51.391416 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:06:51.391416 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:07:07.345470 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:07:07.346471 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:07:07.346471 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:07:07.346471 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:07:07.346471 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 12:07:07.418359 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:07.420347 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:07.421351 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:07.431342 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:07] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:07] "POST /myclass/api/getRecodedParnterImage_from_front/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:07] "POST /myclass/api/Get_List_Theme_Catalog_Pub/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:09.503327 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:09] "POST /myclass/api/Get_Partner_Catalog_Pub_Config/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:12.804019 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:12.808020 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:12.812021 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:12] "POST /myclass/api/Get_Partner_Data_From_Subdomain/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:12] "POST /myclass/api/get_all_class_Given_partner_owner_recid_No_Login/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:15.740927 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:15.752938 : Ajout Token OK, _id = 68f23fd115d6ff1cb9f4ec72 +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:15] "POST /myclass/api/Ent_Student_login/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:16.846523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:16.849522 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:16.852522 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:16.855522 : {'_id': ObjectId('6906220dd3d7adc37cb3fc93'), 'apprenant_id': '66432a8b41efccf7bb038fe4', 'type': 'student', 'email': 'mysy1000formation+02@gmail.com', 'partner_owner_recid': '43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89', 'active': '1', 'adr_city': '', 'adr_country': '', 'adr_street': '', 'civilite': 'neutre', 'code_postal': '', 'creation_by': '65f04934549224c14c3f6039', 'creation_date': '2025-11-01 16:06:53.957236', 'firstconnexion': '0', 'locked': '0', 'mob_phone': '023456789', 'nom': 'ccc', 'notification_send': '0', 'prenom': 'sss', 'pwd': 'Sdj3X7hCbFo', 'lastconnexion': '2025-11-09 12:07:15.752938', 'token': 'CPfyUN9MaoZ61z_nqNtWEAI2RUsQwG1LCw'} +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:16] "POST /myclass/api/get_user_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:16] "POST /myclass/api/Get_List_Ent_Alert_Message/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:16.893172 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:16] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:16] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.003340 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.005343 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.007854 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.008880 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.011865 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.014862 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.017858 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.023877 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.027862 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.031860 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.036872 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.040858 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.042855 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.046859 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.054855 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.056870 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.061858 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.069898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.072885 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.073883 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.081882 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.086477 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.088455 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.092458 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.101475 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.103474 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.107454 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.119485 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.121474 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.128983 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.132990 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.137004 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.148004 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.150013 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.154018 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.164006 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.168993 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:17.172012 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:17.177996 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:17] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:25.803254 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:25.807263 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:25.810249 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:07:25.815255 : {'_id': ObjectId('6906220dd3d7adc37cb3fc93'), 'apprenant_id': '66432a8b41efccf7bb038fe4', 'type': 'student', 'email': 'mysy1000formation+02@gmail.com', 'partner_owner_recid': '43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89', 'active': '1', 'adr_city': '', 'adr_country': '', 'adr_street': '', 'civilite': 'neutre', 'code_postal': '', 'creation_by': '65f04934549224c14c3f6039', 'creation_date': '2025-11-01 16:06:53.957236', 'firstconnexion': '0', 'locked': '0', 'mob_phone': '023456789', 'nom': 'ccc', 'notification_send': '0', 'prenom': 'sss', 'pwd': 'Sdj3X7hCbFo', 'lastconnexion': '2025-11-09 12:07:15.752938', 'token': 'CPfyUN9MaoZ61z_nqNtWEAI2RUsQwG1LCw'} +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:25] "POST /myclass/api/get_user_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:25] "POST /myclass/api/Get_List_Ent_Alert_Message/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:25.846265 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:25] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:25] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:07:30.992989 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:07:31] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\ent_student_common.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:08:26.722471 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:08:26.722471 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:08:26.722471 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:08:26.722471 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:08:26.722471 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\ent_student_common.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 12:08:43.246195 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 12:08:43.246195 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 12:08:43.247195 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 12:08:43.247195 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 12:08:43.247195 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-09 12:08:54.380372 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:08:54] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:08:55.928928 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:08:55] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:09:29.361747 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:09:29.363729 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:09:29.367773 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:09:29] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:09:29] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:09:29] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:09:30.879548 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:09:30] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:07.001676 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:07.003675 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:07.007675 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:07] "POST /myclass/api/Get_Partner_Data_From_Subdomain/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:07] "POST /myclass/api/get_all_class_Given_partner_owner_recid_No_Login/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.310982 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.317992 : Ajout Token OK, _id = 68f23fd115d6ff1cb9f4ec72 +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/Ent_Student_login/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.352530 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.355545 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.358533 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.368529 : {'_id': ObjectId('6906220dd3d7adc37cb3fc93'), 'apprenant_id': '66432a8b41efccf7bb038fe4', 'type': 'student', 'email': 'mysy1000formation+02@gmail.com', 'partner_owner_recid': '43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89', 'active': '1', 'adr_city': '', 'adr_country': '', 'adr_street': '', 'civilite': 'neutre', 'code_postal': '', 'creation_by': '65f04934549224c14c3f6039', 'creation_date': '2025-11-01 16:06:53.957236', 'firstconnexion': '0', 'locked': '0', 'mob_phone': '023456789', 'nom': 'ccc', 'notification_send': '0', 'prenom': 'sss', 'pwd': 'Sdj3X7hCbFo', 'lastconnexion': '2025-11-09 12:10:14.318993', 'token': 'GLD0E4yNiBHmby-nlXB9B3MnaWd84G_Z2A'} +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/get_user_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/Get_List_Ent_Alert_Message/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.393545 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/Get_Ent_Student_List_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.491118 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.494116 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.496118 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.500117 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.505135 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.508119 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.512117 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.517119 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.523119 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.526134 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.532118 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.541146 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.545145 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.549145 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.554721 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.556816 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.561799 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.570799 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.572815 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.575815 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.579798 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.581820 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.592815 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.595798 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.598799 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.602799 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.610798 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.615799 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.616821 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.622819 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.624820 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.628820 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.637871 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.644386 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.645452 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.655548 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.658572 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:14.661548 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:14.664564 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSessionFormation_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/getRecodedClassImage_no_token/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:14] "POST /myclass/api/GetActiveSession_Cities_And_Distance_Formation_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:36.318435 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:36] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:36.421614 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:36] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:46.768114 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:46.771137 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:46] "POST /myclass/api/get_Ent_Student_Given_Class_From_Class_Id/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:46.776112 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:46.780111 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:46.784113 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:46] "POST /myclass/api/Get_Ent_Student_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:46.795139 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:46] "POST /myclass/api/Get_Ent_Student_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:46] "POST /myclass/api/Get_Ent_Student_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:46] "POST /myclass/api/Get_Ent_Student_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:46] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:51.340525 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:51.342526 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:51.347525 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:10:51.353525 : {'_id': ObjectId('6906220dd3d7adc37cb3fc93'), 'apprenant_id': '66432a8b41efccf7bb038fe4', 'type': 'student', 'email': 'mysy1000formation+02@gmail.com', 'partner_owner_recid': '43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89', 'active': '1', 'adr_city': '', 'adr_country': '', 'adr_street': '', 'civilite': 'neutre', 'code_postal': '', 'creation_by': '65f04934549224c14c3f6039', 'creation_date': '2025-11-01 16:06:53.957236', 'firstconnexion': '0', 'locked': '0', 'mob_phone': '023456789', 'nom': 'ccc', 'notification_send': '0', 'prenom': 'sss', 'pwd': 'Sdj3X7hCbFo', 'lastconnexion': '2025-11-09 12:10:14.318993', 'token': 'GLD0E4yNiBHmby-nlXB9B3MnaWd84G_Z2A'} +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:51] "POST /myclass/api/get_user_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:51] "POST /myclass/api/Get_List_Ent_Alert_Message/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:51.407832 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:51] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:51] "POST /myclass/api/Get_Ent_Student_List_Session_Promotion/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:10:55.137033 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:10:55] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:06.087816 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:11:06.091865 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:11:06.092865 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:06] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:06] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:06] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:07.573200 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:07] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:19.393318 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:19] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:19.467864 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:19] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:26.807798 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:26] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:28.280240 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:28] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:37.968665 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:11:37.971620 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 12:11:37.975665 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:37] "POST /myclass/api/Get_Given_Evaluation_Planification/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:37] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:38] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:39.568773 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:39] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:50.351087 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:50] "POST /myclass/api/Publish_Unpublish_Participant_Evaluation_Note/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:50.454606 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:50] "POST /myclass/api/Get_List_Participant_To_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:57.906042 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:57] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 12:11:59.196778 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 12:11:59] "POST /myclass/api/Get_Ent_Student_Participant_Notes/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.156096 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:42.159095 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:42.163097 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:42.167096 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.174096 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.178101 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.184102 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:42.189104 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.197266 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.205273 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.218793 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:42.235784 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:42] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:46.804744 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:46.808731 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:46.813741 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:46.817747 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:46.826321 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:46] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:46] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:46] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:46.834298 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:46.841290 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:46] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:46] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:46] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:51.321589 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:51.322616 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:52] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:07:55.210502 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:07:55.213533 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:55] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:07:56] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:11:15.927089 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:11:15.931090 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:11:15.934088 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:11:15.938090 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:15] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:11:15.946600 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:15] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:11:15.954602 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:15] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:15] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:15] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:11:15.971601 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:15] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:11:15.976600 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:11:15.978600 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:11:15.985600 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:15] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:11:15.996607 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:11:16.001607 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:16] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:16] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:16] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:16] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:11:17] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:17:58.385695 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:17:58.390694 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:17:58.395695 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:17:58.399711 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:17:58.407695 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:17:58.411691 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:17:58.416695 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:17:58.422694 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:17:58.428211 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:17:58.439219 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:17:58.451230 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:17:58.456737 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:58] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:59] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:17:59] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:19:52.143816 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:19:52.147817 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:19:52.153816 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:19:52.158327 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:19:52.167332 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:19:52.169327 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:19:52.181328 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:19:52.186328 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:19:52.192328 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:19:52.205328 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:19:52.218328 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:19:52.226328 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:52] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:19:53] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:07.762201 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:07] "POST /myclass/api/UpdateStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:07.905927 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:07.908474 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:07.912475 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:07] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:07] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:07] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:23.659289 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:23.665288 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:23.669282 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:23.673793 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:23.678325 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:23.691315 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:23.698315 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:23.706312 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:23.713320 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:23.719317 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:23.724315 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:23.728318 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:23] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:24] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:25] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:26.720613 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:26.725614 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:26.728612 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:26.732614 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:26] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:26] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:26.744615 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:26] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:26.751611 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:26] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:26.757615 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:26] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:26] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:26] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:20:28.408428 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:20:28.410407 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:28] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:20:29] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.545172 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.549166 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.552168 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.561687 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.573683 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.625883 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.627883 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.631884 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.638883 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.643887 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.648888 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.653926 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.657951 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.670935 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:24:59.675920 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.678923 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:24:59.682927 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:24:59] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:00] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:00] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:25:03.005620 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:25:03.009618 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:25:03.013591 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:25:03.020604 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:03] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:25:03.024587 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:25:03.029589 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:03] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:03] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:25:03.037587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:03] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:03] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:03] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:03] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:25:06.642568 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:25:06.646553 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:25:07] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:26:25.748331 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:26:25.751333 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:26:25.754338 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:26:25.758335 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:26:25.766341 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:26:25.769368 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:26:25.777897 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:26:25.781898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:26:25.793448 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:26:25.798458 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:26:25.803459 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:26:25.808457 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:25] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:26] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:26:27] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:18.377354 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:18.381356 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:18.386356 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:18.394354 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:18.399354 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:18.408355 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:18.423354 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:18.425378 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:18.434363 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:18.449424 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:18.452422 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:18.459940 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:18] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:20] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:21] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:45.086015 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.091015 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.098017 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.103017 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.112010 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:45.124019 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:45.134017 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.144290 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.148292 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:27:45.168812 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.170809 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:27:45.180853 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:45] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:27:46] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:04.335295 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:04.340712 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:04.345659 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:04.349221 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:04.373169 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:04.382797 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:04.395998 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:04.406584 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:04.423587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:04.430584 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:04.450594 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:04.473648 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:04] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:05] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:06] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:53.507453 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:53.512526 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:53.518852 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:53.523917 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:53.538402 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:53.548064 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:53.561600 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:53.575628 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:53.599645 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:53.606630 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:53.614600 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:53.625704 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:53] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:55] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:57] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:58.083918 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:58.092440 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:58] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:58.102452 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:58.116437 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:58] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:58] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:58.139435 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:28:58.156456 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:58] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:28:58.179067 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:58] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:28:58] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:29:00.151292 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:29:00.159308 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:29:00] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:29:02] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:31:03.557448 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.559451 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.565458 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.569458 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.574459 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:31:03.582978 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.591978 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.595978 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:31:03.613492 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.618491 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:31:03.626491 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:31:03.638490 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:03] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:04] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:31:04] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.206506 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.217513 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:35:53.226502 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:35:53.234505 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.254507 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.274022 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:35:53.280025 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.289035 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.296032 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:35:53.300554 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:35:53.304557 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.310558 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:35:53.314078 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.322078 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.328081 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:35:53.331077 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:35:53.341075 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:53] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:54] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:35:54] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:36:01.970093 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:36:01.974120 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:36:01.977099 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:36:01.982102 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:36:01.985104 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:36:01.991606 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:01] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:01] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:01] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:36:02.001611 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:02] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:02] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:02] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:02] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:36:17.559296 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:36:17.562278 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:18] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:36:27.991140 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:28] "POST /myclass/api/UpdateStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:36:28.134248 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:36:28.147247 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:28] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:36:28.154268 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:28] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:36:28] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:38:14.163509 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:38:14.167516 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:38:14.173515 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:38:14.183540 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:38:14.187540 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:38:14.195539 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:38:14.202540 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:38:14.208541 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:38:14.222543 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:38:14.225546 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:38:14.241057 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:38:14.247060 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:14] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:15] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:38:15] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:40:18.031519 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:40:18.187424 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:40:18] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:40:19.125170 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:40:19.271460 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:40:19] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:40:22] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:40:22] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:22.334965 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:22.337964 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:22.342964 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:22.354967 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:22.356966 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:22.361965 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:22.369966 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:22.380966 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:22.387967 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:22.395967 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:22.401967 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:22.409967 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:22] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:23] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:23] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:28.979978 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:28.982973 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:28.985972 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:28.989974 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:28.993975 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:28] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:28.999974 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:29.003975 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:29] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:29] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:29] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:29] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:29] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:29] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:30.993990 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:30.994988 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:31] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:31] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:51.308019 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:51.313024 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:51.316019 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:51.323569 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:51.328536 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:51.332535 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:51.337536 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:51] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:51] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:51] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:51] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:41:53.207708 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:41:53.210692 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:53] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:41:54] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:00.137979 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:00.141977 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:00.144976 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:00.148975 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:00] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:00] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:00.154976 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:00.158983 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:00] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:00] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:00.166982 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:00] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:00] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:01.954856 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:01.957875 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:01] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:02] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:17.418945 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:17] "POST /myclass/api/UpdateStagiairetoClass/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:17.646542 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:17.650421 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:17.652406 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:17] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:33.181998 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:33] "POST /myclass/api/Get_Personnalisable_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:33.189035 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:33] "POST /myclass/api/Get_List_Partner_Document_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:41.380318 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:41] "POST /myclass/api/Get_List_Partner_Document_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:42:43.441986 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:42:43.447031 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:43] "POST /myclass/api/Get_Given_Partner_Document/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:42:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:43:51.075412 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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SASU JMJ FORMATION
BP 60540 97206 FORT DE FRANCE CEDEX
Email: jmjformation@gmail.com
Tel: 0596 97 58 46
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  Date Facture   09/11/2025 
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Facture n° NEW_Invoice_84 

Destinataire : msys boite


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Client : test01 prenom billardman01@hotmail.com\n  

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Intitulé de la formation : CONDUIRE UN PROJET  

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DésignationQuantitéPrix unitaire HTTotal HT
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CONDUIRE UN PROJET
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15/09/2025 - 17/09/2025
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\n      commmmmmmmmmmmmm - memoooooooo
11500.0 €1500.0 €
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 Totaux
 Total HT1500.0 €
 TaxesPrestations de formation en exonération de TVA, article 261-4-4a du CGI
 Total1500.0 €
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Condition de règlement : 0J  Conditions de paiement : Date Facture 

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Date échéance : 09/11/2025 

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 Code banque
16958
Code guichet
00001
N° de compte
04285131654
Clé RIB
46
Monnaie
EUR
 IBAN
FR76 1695 8000 0104 2851 3165 446
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BIC
QNTOFRP1XXX

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JMJ FORMATION
Siége social : 15 Rue Georges Eucharis, Espace POSEIDON, Dillon Stade, 97200 Fort-de-France
Adresse Postale : BP 60540 97206 FORT DE FRANCE CEDEX
Siret : 799 674 064 00032 - Numéro de déclaration d’activité : 97 97 01982 97 – QUALIOPI : N° RNQ 3318
Tel : 06 96 50 23 33 / 0596 97 58 46/ Mail : jmjformation@gmail.com / Web : www.jmjformation.com  

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\n\n\n\n\n\n\n\n
SASU JMJ FORMATION
BP 60540 97206 FORT DE FRANCE CEDEX
Email: jmjformation@gmail.com
Tel: 0596 97 58 46
\n

\n
\n\n

 

\n\n\n\n\n\n\n\n\n
  Date Facture   09/11/2025 
\n

 

\n\n\n\n\n\n\n\n
\n

Facture n° NEW_Invoice_84 

Destinataire : msys boite


  -

\n
\n

Client : test01 prenom billardman01@hotmail.com\n  

\n

Intitulé de la formation : CONDUIRE UN PROJET  

\n
\n

 

\n

 

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
DésignationQuantitéPrix unitaire HTTotal HT
\n
CONDUIRE UN PROJET
\n
15/09/2025 - 17/09/2025
\n
 
\n      commmmmmmmmmmmmm - memoooooooo
11500.0 €1500.0 €
\n

 

\n

 

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
 Totaux
 Total HT1500.0 €
 TaxesPrestations de formation en exonération de TVA, article 261-4-4a du CGI
 Total1500.0 €
\n

 

\n

Condition de règlement : 0J  Conditions de paiement : Date Facture 

\n

Date échéance : 09/11/2025 

\n

 

\n

 

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
 Code banque
16958
Code guichet
00001
N° de compte
04285131654
Clé RIB
46
Monnaie
EUR
 IBAN
FR76 1695 8000 0104 2851 3165 446
\n

BIC
QNTOFRP1XXX

\n
\n

 

\n

 

\n

JMJ FORMATION
Siége social : 15 Rue Georges Eucharis, Espace POSEIDON, Dillon Stade, 97200 Fort-de-France
Adresse Postale : BP 60540 97206 FORT DE FRANCE CEDEX
Siret : 799 674 064 00032 - Numéro de déclaration d’activité : 97 97 01982 97 – QUALIOPI : N° RNQ 3318
Tel : 06 96 50 23 33 / 0596 97 58 46/ Mail : jmjformation@gmail.com / Web : www.jmjformation.com  

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', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:Col 0 has width 50% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 20% +DEBUG:xhtml2pdf.tables:Col 3 has width 20% +DEBUG:xhtml2pdf.tables:Col 0 has width 50% +DEBUG:xhtml2pdf.tables:Col 1 has width 10% +DEBUG:xhtml2pdf.tables:Col 2 has width 20% +DEBUG:xhtml2pdf.tables:Col 3 has width 20% +DEBUG:xhtml2pdf.tables:Col widths: ['50%', '10%', '20%', '20%'] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None, None, None] +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'PLTE' 41 6 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 59 821 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:43:52] "POST /myclass/api/Invoice_Inscrption_With_Split_Session_By_Inscription_Id/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:43:52.656783 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:43:53] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:45:56.199264 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:45:56.203205 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:45:56] "POST /myclass/api/Get_List_Partner_Invoice_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:45:57] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:45:58.056133 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:45:58.059134 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:45:58] "POST /myclass/api/Get_Given_Partner_Invoice/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:45:58] "POST /myclass/api/Get_Given_Partner_Invoice_Lines/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:46:00.136402 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:46:00] "GET /myclass/api/GerneratePDF_Partner_Invoice/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/69109a97719c7106adb90a99 HTTP/1.1" 200 - +INFO:root:2025-11-09 14:47:34.221876 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:47:34] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:56:24.835854 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:56:24] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/69109a98995b26cde9611abe HTTP/1.1" 200 - +INFO:root:2025-11-09 14:59:22.637736 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:59:22] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:59:22.648738 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:59:22.650739 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:59:22.656738 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 14:59:22.663746 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:59:22] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:59:22] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:59:22] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-09 14:59:22.757504 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 14:59:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:00:32.158717 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:00:32.159716 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:00:32.165717 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:00:32.170716 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:00:32] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:00:32.182780 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:00:32] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:00:32] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:00:32] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:00:32.216457 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:00:32] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:05:51.780266 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:05:51] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/68f15277d980c4ab7268ba8f HTTP/1.1" 200 - +INFO:root:2025-11-09 15:09:23.593134 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:09:23] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/690df2ec995b26cde9611890 HTTP/1.1" 200 - +INFO:root:2025-11-09 15:17:26.088926 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:17:26] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:18:11.691591 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:18:11] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:21:42.372155 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:21:42] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:21:46.386166 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:21:46] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/69109a98995b26cde9611abe HTTP/1.1" 200 - +INFO:root:2025-11-09 15:22:42.777811 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:22:42] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:22:49.333938 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:22:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:22:52.422693 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:22:52] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/69109a98995b26cde9611abe HTTP/1.1" 304 - +INFO:root:2025-11-09 15:22:57.060515 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:22:57] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/68fe06e779119ff4d421aeed HTTP/1.1" 200 - +INFO:root:2025-11-09 15:23:59.553360 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:23:59.565366 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:23:59.570365 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:23:59] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:23:59.586880 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:23:59.601881 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:23:59] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:23:59] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:23:59] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:23:59.899197 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:24:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:24:07.988704 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:24:08] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:27:10.546389 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:10] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:27:15.254898 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:15] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/69109a98995b26cde9611abe HTTP/1.1" 304 - +INFO:root:2025-11-09 15:27:43.239813 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:27:50.700908 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:27:50.709911 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:50] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:27:50.724925 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:27:50.732929 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:27:50.734909 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:50] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:50] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:50] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:27:50.750926 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:27:50] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:28:05.826218 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:28:05] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:28:38.991906 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:28:39] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:29:17.433227 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:29:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:29:33.590850 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:29:33] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/69109a98995b26cde9611abe HTTP/1.1" 304 - +INFO:root:2025-11-09 15:29:54.685756 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:29:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:30:31.390008 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:30:31] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:30:34.734372 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:30:34] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/69109a98995b26cde9611abe HTTP/1.1" 304 - +INFO:root:2025-11-09 15:30:41.278093 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:30:41] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/68fe06e779119ff4d421aeed HTTP/1.1" 304 - +INFO:root:2025-11-09 15:30:45.214518 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:30:45] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/68fb8f5979119ff4d421aea0 HTTP/1.1" 200 - +INFO:root:2025-11-09 15:31:35.838590 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:31:35] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/690df2ec995b26cde9611890 HTTP/1.1" 200 - +INFO:root:2025-11-09 15:32:01.990880 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:32:02] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/68f4d22dd12201e20d8b6dac HTTP/1.1" 200 - +INFO:root:2025-11-09 15:32:29.558465 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:32:29] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:32:33.982793 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:32:34] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/68fe06e779119ff4d421aeec HTTP/1.1" 200 - +INFO:root:2025-11-09 15:33:01.457258 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:33:01] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:33:04.153157 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:33:04] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:33:14.413525 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:33:14] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/xQvCaXv9Jm4CdK7afh52CRBApicf7umogg/68c57c1f1dac169e77e4db7a HTTP/1.1" 200 - +INFO:root:2025-11-09 15:45:54.420260 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:45:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:48:51.270948 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:48:51.276948 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:48:51.281975 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:48:51.287950 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:48:51.299950 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:48:51.304948 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:48:51.322949 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:48:51.339947 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:48:51.353954 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:48:51.355954 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-09 15:48:51.363469 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:48:51.374468 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:51] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:52] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:52] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-09 15:48:56.276568 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [09/Nov/2025 15:48:56] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 15:51:00.676713 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 15:51:00.676713 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 15:51:00.676713 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 15:51:00.676713 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 15:51:00.676713 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-09 15:52:44.662698 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-09 15:52:44.663700 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-09 15:52:44.663700 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-09 15:52:44.663700 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-09 15:52:44.663700 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:35:59.128064 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:35:59.129068 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:35:59.129068 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:35:59.129068 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:35:59.129068 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:36:11.804136 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:36:11.804136 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:36:11.804136 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:36:11.804136 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:36:11.804136 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:36:58.253733 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:36:58.253733 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:36:58.253733 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:36:58.253733 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:36:58.253733 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:49:11.989405 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:49:11.989405 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:49:11.989405 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:49:11.989405 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:49:11.990400 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:49:37.864298 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:49:37.864298 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:49:37.865319 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:49:37.865319 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:49:37.865319 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-10 08:49:38.316923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:38] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:49:44.395982 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:49:44.405924 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:49:44.416486 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:49:44.419482 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:49:44.439479 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:44] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:49:44.485758 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:44] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:44] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:44] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:44] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:49:45.035302 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:49:45.050081 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:45] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:49:45.061199 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:49:45.071605 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:49:45.078658 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:45] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:49:45.090422 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:45] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:45] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:45] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:49:45] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.408788 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:17.413473 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:17.417822 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:17.421931 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.427715 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.433306 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.442217 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:17.448923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.457932 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.462923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.468926 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:17.475946 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:17] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:18] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:19] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:21.965610 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:21.969595 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:21.975869 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:21.979866 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:21.987867 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:21] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:21] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:21.996874 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:21] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:22.007972 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:22] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:22] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:22] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:25.055281 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:25.060213 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:25] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:26] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:46.044072 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:50:46.047089 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:46] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:46] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:51.405213 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  neutre   part 2 part nom 2  

Situé :adresse02    code_postal02   ville02    pays02

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    10/11/2025 10:00  au 10/11/2025 12:30
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Du    12/11/2025 09:00  au 12/11/2025 17:30
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    17/11/2025 09:00  au 17/11/2025 17:30
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Du    20/11/2025 09:00  au 20/11/2025 17:30
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Du    21/11/2025 09:00  au 21/11/2025 17:30
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Au plaisir de vous retrouver prochainement,
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10/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:51] "GET /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_PDF/AetKl4vNLkYTl7xsmMfQtyjcyO_DjfMCzg/68fb8e6a0438bff16569753c/6847efb6adbfa1041e0cf34b/68fb8ede79119ff4d421ae9b HTTP/1.1" 200 - +INFO:root:2025-11-10 08:50:51.913213 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:50:52] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:53:11.497495 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:53:11.500760 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:53:11.504767 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:11] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:53:11.513814 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:53:11.522470 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. 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A l\'attention  neutre   part 2 part nom 2  

Situé :adresse02    code_postal02   ville02    pays02

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    10/11/2025 10:00  au 10/11/2025 12:30
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Du    12/11/2025 09:00  au 12/11/2025 17:30
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    17/11/2025 09:00  au 17/11/2025 17:30
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Du    20/11/2025 09:00  au 20/11/2025 17:30
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Du    21/11/2025 09:00  au 21/11/2025 17:30
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Au plaisir de vous retrouver prochainement,
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10/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:48] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:53:48.783561 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:48] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:53:54.928158 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:53:54.947063 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:54] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:53:54.973343 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-10 08:53:54.999066 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:55] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:55] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:53:55.045456 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:55] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:53:55.049460 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:53:55] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-10 08:54:07.292761 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 08:54:07] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\jury_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:55:29.461563 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:55:29.461563 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:55:29.461563 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:55:29.461563 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:55:29.461563 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:58:27.840941 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:58:27.841936 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:58:27.841936 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:58:27.841936 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:58:27.841936 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 08:59:42.207230 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 08:59:42.207230 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 08:59:42.207230 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 08:59:42.207230 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 08:59:42.207230 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 09:00:09.997033 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 09:00:09.997033 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 09:00:09.997033 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 09:00:09.997033 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 09:00:09.997033 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 09:00:56.058065 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 09:00:56.058065 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 09:00:56.058065 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 09:00:56.058065 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 09:00:56.058065 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 09:01:23.795678 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 09:01:23.795678 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 09:01:23.795678 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 09:01:23.796678 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 09:01:23.796678 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 09:01:40.108773 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 09:01:40.108773 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 09:01:40.108773 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 09:01:40.108773 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 09:01:40.108773 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 09:02:15.993586 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 09:02:15.993586 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 09:02:15.993586 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 09:02:15.993586 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 09:02:15.993586 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 09:02:41.094112 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 09:02:41.094112 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 09:02:41.094112 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 09:02:41.094112 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 09:02:41.094112 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 09:03:12.239489 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 09:03:12.239489 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 09:03:12.240487 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 09:03:12.240487 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 09:03:12.240487 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 15:40:31.360821 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 15:40:31.360821 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 15:40:31.360821 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 15:40:31.361632 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 15:40:31.361632 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 15:40:42.166018 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 15:40:42.167019 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 15:40:42.167019 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 15:40:42.167019 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 15:40:42.167019 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\email_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-10 15:43:06.346386 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-10 15:43:06.347385 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-10 15:43:06.347385 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-10 15:43:06.348430 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-10 15:43:06.348430 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-10 15:43:08.003348 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 15:43:08] "GET /myclass/api/ManualSendInvoiceEmailRIB_CIC_BureauVallee HTTP/1.1" 308 - +INFO:root:2025-11-10 15:43:08.052452 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n\n\n\n\t
\n\t\tMysy Training Logo \n\t
\n\t\n\t\t
\n\t\t\t
\n\t\t\t\t\n\t\t\t\t
\n\t\t\t\t\n\t\t\t\t\tBVD Fr (Bureau Vallée)
\n\t\t\t\t\t25 rue du Gros Caillou
\n\t\t\t\t\t78340 – Les Clayes-sous-Bois- France
\n\n\t\t\t\t
\n\n\n\t\t\t\t\n\n\t\t\t\t\tFacture n° FACT_20251020\n\n\n\t\t\t\t
\n\n\n\n\t\t\t\t\n\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t
Date de facture: 31/10/2025 Date échéance : 15/11/2025
\n\n\t\t\t\t\n\t\t\t\t\tPériode : 01/10/2025 au 31/10/2025 \n\t\t\t\t\n\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t
DescriptionQuantitéPrix unitaire (HT)Montant (HT)
Prestation de service
\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t
23 jours550 € HT12 650 € HT
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n\t\t\t\t\t\t\t\n\n\n\t\t\t\t\t\t\n\n\t\t\t\t\t
Déplacement Bureau - PapetShow -\n\t\t\t\t\t\t\t\t15/10/2025 et 16/10/2025
\n\t\t\t\t\t\t\t\tDeplacement bureau <=> papet show (Aller / retour) : 16,8 km X 2 X 2 jrs = 67,2 Km\n\t\t\t\t\t\t\t\t\t(https://www.impots.gouv.fr/simulateur-bareme-kilometrique) 47 € TTC
 
Déplacement Bureau - Magasin Paris 5 -\n\t\t\t\t\t\t\t\t8/10/2025
\n\t\t\t\t\t\t\t\tDeplacement bureau <=> Magasin Paris 5 (Aller / retour) : 37,6 km X 2 = 75,2 Km\n\t\t\t\t\t\t\t\t\t(https://www.impots.gouv.fr/simulateur-bareme-kilometrique) 52 € TTC
\n\t\t\t\t\n\n\n\t\t\t\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t
    Montant HT: 12 749   €
    TVA : 2 548,8   €
    Montant TTC : 15 298,8  €
\n\n\t\t\t
\n\n\t\t\t\n\t\t\t\tRèglement : Virement bancaire \n\n\n\t\t\t

\n\t\t\t\t> Relevé d\'identité bancaire : MySy Training Technology, 2 place des magnolias, 77680, Roissy en\n\t\t\t\t\tbrie \n\t\t\t

\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\n\n\n\t\t\t\t\n\n\t\t\t
BanqueCode agenceNuméro de compteClé RIB
30087338560002128550340
\n\n\t\t\t

\n\t\t\t\t> Identification internationale\n\t\t\t

\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\n\n\n\n\t\t\t\t\n\n\t\t\t
IBANCode BIC
FR76 3008 7338 5600 0212 8550 340CMCIFRPP
\n\n\t\t\n\n\t\n\n\t
\n\t\n\n\t\tTermes et conditions
\n\n\t\tPas d\'escompte accordé pour paiement anticipé.
\n\t\tEn cas de non-paiement à la date d\'échéance, des pénalités calculées à trois fois le taux d\'intérêt légal\n\t\tseront appliquées.
\n\t\tTout retard de paiement entraînera une indemnité forfaitaire pour frais de recouvrement de 40€.
\n\n\t\n\n\n\t
\n\t\t\n\n\t\t\tMySy Training
\n\n\t\t\tMySy Training Technology (MTT), société par actions simplifiée au capital de 10 000 euros, dont le siège\n\t\t\tsocial est\n\t\t\tsitué 2, place des magnolias, 77680, Roissy en Brie, immatriculée au Registre du Commerce et des\n\t\t\tSociétés sous le numéro 917 500 860 R.C.S. Melun\n\n\t\t\n\t
\n\n\n' + dest = <_io.BufferedRandom name='./Invoices/invoice_FACT_20251020.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject './../img/MYSY-LOGO-BLUE.png', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.files:URLParts: ParseResult(scheme='c', netloc='', path='\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__', params='', query='', fragment=''), 'c' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': 75.0, 'height': None, 'align': None, 'id': None} +DEBUG:xhtml2pdf.files:Unrecognized scheme, assuming local file path +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'tEXt' 41 25 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 6645 +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'tEXt' 41 25 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 6645 +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 15:43:09] "GET /myclass/api/ManualSendInvoiceEmailRIB_CIC_BureauVallee/ HTTP/1.1" 200 - +INFO:root:2025-11-10 15:44:24.840166 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 15:44:24] "GET /myclass/api/ManualSendInvoiceEmailRIB_CIC_BureauVallee HTTP/1.1" 308 - +INFO:root:2025-11-10 15:44:24.846096 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n\n\n\n\t
\n\t\tMysy Training Logo \n\t
\n\t\n\t\t
\n\t\t\t
\n\t\t\t\t\n\t\t\t\t
\n\t\t\t\t\n\t\t\t\t\tBVD Fr (Bureau Vallée)
\n\t\t\t\t\t25 rue du Gros Caillou
\n\t\t\t\t\t78340 – Les Clayes-sous-Bois- France
\n\n\t\t\t\t
\n\n\n\t\t\t\t\n\n\t\t\t\t\tFacture n° FACT_20251020\n\n\n\t\t\t\t
\n\n\n\n\t\t\t\t\n\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t
Date de facture: 31/10/2025 Date échéance : 15/11/2025
\n\n\t\t\t\t\n\t\t\t\t\tPériode : 01/10/2025 au 31/10/2025 \n\t\t\t\t\n\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t
DescriptionQuantitéPrix unitaire (HT)Montant (HT)
Prestation de service
\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t
23 jours550 € HT12 650 € HT
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n\t\t\t\t\t\t\t\n\n\n\t\t\t\t\t\t\n\n\t\t\t\t\t
Déplacement Bureau - PapetShow -\n\t\t\t\t\t\t\t\t15/10/2025 et 16/10/2025
\n\t\t\t\t\t\t\t\tDeplacement bureau <=> papet show (Aller / retour) : 16,8 km X 2 X 2 jrs = 67,2 Km\n\t\t\t\t\t\t\t\t\t(https://www.impots.gouv.fr/simulateur-bareme-kilometrique) 47 € HT
 
Déplacement Bureau - Magasin Paris 5 -\n\t\t\t\t\t\t\t\t8/10/2025
\n\t\t\t\t\t\t\t\tDeplacement bureau <=> Magasin Paris 5 (Aller / retour) : 37,6 km X 2 = 75,2 Km\n\t\t\t\t\t\t\t\t\t(https://www.impots.gouv.fr/simulateur-bareme-kilometrique) 52 € HT
\n\t\t\t\t\n\n\n\t\t\t\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t
    Montant HT: 12 749   €
    TVA : 2 548,8   €
    Montant TTC : 15 298,8  €
\n\n\t\t\t
\n\n\t\t\t\n\t\t\t\tRèglement : Virement bancaire \n\n\n\t\t\t

\n\t\t\t\t> Relevé d\'identité bancaire : MySy Training Technology, 2 place des magnolias, 77680, Roissy en\n\t\t\t\t\tbrie \n\t\t\t

\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\n\n\n\t\t\t\t\n\n\t\t\t
BanqueCode agenceNuméro de compteClé RIB
30087338560002128550340
\n\n\t\t\t

\n\t\t\t\t> Identification internationale\n\t\t\t

\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\n\n\n\n\t\t\t\t\n\n\t\t\t
IBANCode BIC
FR76 3008 7338 5600 0212 8550 340CMCIFRPP
\n\n\t\t\n\n\t\n\n\t
\n\t\n\n\t\tTermes et conditions
\n\n\t\tPas d\'escompte accordé pour paiement anticipé.
\n\t\tEn cas de non-paiement à la date d\'échéance, des pénalités calculées à trois fois le taux d\'intérêt légal\n\t\tseront appliquées.
\n\t\tTout retard de paiement entraînera une indemnité forfaitaire pour frais de recouvrement de 40€.
\n\n\t\n\n\n\t
\n\t\t\n\n\t\t\tMySy Training
\n\n\t\t\tMySy Training Technology (MTT), société par actions simplifiée au capital de 10 000 euros, dont le siège\n\t\t\tsocial est\n\t\t\tsitué 2, place des magnolias, 77680, Roissy en Brie, immatriculée au Registre du Commerce et des\n\t\t\tSociétés sous le numéro 917 500 860 R.C.S. Melun\n\n\t\t\n\t
\n\n\n' + dest = <_io.BufferedRandom name='./Invoices/invoice_FACT_20251020.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject './../img/MYSY-LOGO-BLUE.png', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.files:URLParts: ParseResult(scheme='c', netloc='', path='\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__', params='', query='', fragment=''), 'c' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': 75.0, 'height': None, 'align': None, 'id': None} +DEBUG:xhtml2pdf.files:Unrecognized scheme, assuming local file path +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'tEXt' 41 25 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 6645 +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'tEXt' 41 25 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 6645 +INFO:werkzeug:127.0.0.1 - - [10/Nov/2025 15:44:25] "GET /myclass/api/ManualSendInvoiceEmailRIB_CIC_BureauVallee/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\main.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:36:31.805035 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:36:31.805035 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:36:31.806046 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:36:31.806046 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:36:31.806046 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 09:38:51.980842 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:38:52.796098 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:38:52.799098 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:38:52.804098 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:38:52.808099 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:38:52.817098 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:38:52.851097 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:38:52.855097 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:38:52.857097 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:38:52.865096 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:38:52.874102 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:38:52.884620 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:38:52.893621 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:38:52] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:13.499405 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:13.501405 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:13.503407 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:13.508961 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:13.518975 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:13.524976 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:13.532993 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:13.543975 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:13.548980 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:13.555977 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:13.563992 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:13.568974 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:13] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:14] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:15] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:16.009197 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:16.013706 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:16.017713 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:16.024720 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:16] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:16] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:16.034720 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:16] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:16.042720 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:16] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:16.049718 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:16] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:16] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:16] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:17.873538 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:17.877538 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:19] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:30.471685 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:39:30.475691 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:30] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:30] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:32.489757 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  neutre   part 2 part nom 2  

Situé :adresse02    code_postal02   ville02    pays02

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    10/11/2025 10:00  au 10/11/2025 12:30
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Du    12/11/2025 09:00  au 12/11/2025 17:30
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    17/11/2025 09:00  au 17/11/2025 17:30
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Du    20/11/2025 09:00  au 20/11/2025 17:30
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Du    21/11/2025 09:00  au 21/11/2025 17:30
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Au plaisir de vous retrouver prochainement,
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11/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:root:2025-11-11 09:39:39.969575 : Internal_Usage_Store_User_Downloaded_File Le champ 'tab_related_collection' n'existe pas +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:40] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:39:40.006559 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:39:40] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:40:20.111932 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:40:20.112934 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:40:20.112934 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:40:20.112934 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:40:20.112934 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:41:22.116044 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:41:22.116044 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:41:22.116044 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:41:22.116044 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:41:22.116044 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:44:27.762260 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:44:27.762260 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:44:27.762260 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:44:27.762260 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:44:27.762260 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 09:44:47.867704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:44:47.870701 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:44:47] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:44:47] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:44:50.494231 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  neutre   part 2 part nom 2  

Situé :adresse02    code_postal02   ville02    pays02

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    10/11/2025 10:00  au 10/11/2025 12:30
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Du    12/11/2025 09:00  au 12/11/2025 17:30
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    17/11/2025 09:00  au 17/11/2025 17:30
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Du    20/11/2025 09:00  au 20/11/2025 17:30
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Du    21/11/2025 09:00  au 21/11/2025 17:30
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Au plaisir de vous retrouver prochainement,
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11/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:44:51] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:44:51.531029 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:44:51] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.837525 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.838547 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.842524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.851039 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.858040 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.910039 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.912080 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.914040 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.917038 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.921039 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.929044 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.931071 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.946554 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.951585 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.959624 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:20.963585 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:20.977586 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:20] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:21] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:21] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:21] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:22] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:47:28.965232 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:47:30.333412 : Get_List_object_owner_collection_Stored_Files_With_Filter -list indices must be integers or slices, not str - ERRORRRR AT Line : 1441 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:47:30] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:48:37.120490 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:48:37.121493 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:48:37.121493 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:48:37.121493 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:48:37.121493 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 09:48:42.589642 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:42.593642 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:42.594643 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:42.599644 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:42.600643 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:42.606670 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:42.611682 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:42.615644 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:48:42.625647 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:48:42.640200 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:48:42.650201 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:48:42.659269 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:42] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:43] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:48:48.070433 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:48:49.938848 : Get_List_object_owner_collection_Stored_Files_With_Filter -list indices must be integers or slices, not str - ERRORRRR AT Line : 1413 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:48:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:49:13.129511 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:49:13.129511 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:49:13.130528 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:49:13.130528 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:49:13.130528 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 09:49:18.220204 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.223204 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.226731 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.231714 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.237810 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.239835 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.246809 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:49:18.254852 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:49:18.269830 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:49:18.282832 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.293830 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:49:18.302831 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:18] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:19] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:49:22.249357 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:49:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:52:49.777777 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:52:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:53:07.407572 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:53:07.409575 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:53:07.413575 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:53:07.417577 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:53:07.419576 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:53:07.429091 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:53:07.426091 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:53:07.438147 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:53:07.445095 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:53:07.455158 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:53:07.469374 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:53:07.474419 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:07] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:08] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:08] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:53:14.628805 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:53:14] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:55:55.588573 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:55:55.589580 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:55:55.589580 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:55:55.589580 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:55:55.589580 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:56:58.708332 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:56:58.708332 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:56:58.708332 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:56:58.708332 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:56:58.708332 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:57:59.508536 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:57:59.508536 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:57:59.508536 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:57:59.509550 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:57:59.509550 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 09:58:01.218621 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:58:01.222184 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:58:01] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:58:01] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:58:03.940575 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  neutre   part 12 part nom 12  

Situé :adresse12    code_postal12   ville12    pays12

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    10/11/2025 10:00  au 10/11/2025 12:30
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Du    12/11/2025 09:00  au 12/11/2025 17:30
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    13/11/2025 09:30  au 13/11/2025 13:00
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Du    17/11/2025 09:00  au 17/11/2025 17:30
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Du    20/11/2025 09:00  au 20/11/2025 17:30
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Du    21/11/2025 09:00  au 21/11/2025 17:30
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Au plaisir de vous retrouver prochainement,
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11/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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ttx9kB7oARSbstqdiAxrubiiy9e/KDUZTFixIji29/+dvF6jWLljM4hE1onoKCVxNCJxx0/ScGtVqTRhx4WJbhrtTvVgtalVGw6paH3lNS1R+pDbRaYa6Atar11BsdrVA+6GlZefoXYa/vUkxNllZoVujSOOuqoSGijKnLkCfvvv3/xjW98o/jZz35WeSajq8iE1glQztASpSUnyXHDo4+0NKuvudrqHRq/pnKdvlnS2Z/SoCqywrLLxof/byboAhi+8y7FSccfP4lkUzX+/Nlncc6Bxv33ewER6AoZOHBgJLSzzjorxtMSDjnkkGLqqacuXnrppcozGV1FJrROwI/wwAMOiD2KZH0S6OnrdTz7jDMrzyCND4rbbh1fXHnFFcWEUrsQa+7kE0+KzeD6ObUBUYRQXElqm+UxYcKEaKkYywavvfpaVKEw0ehnP5u83Qe4alq27r7rruLKK6+IY/fKI/lYO3fdcUdU2zBoheDhisstH+cI/Ptf/4ok+2awQB3Hddde26qDRrXX5+iJaWn6vBLI9pnXX3stNpub5JRalCxcLUvXh214kBdK8J4bwvtJCHEra8G1oCHHGk4QZ9IOZrbCtddc0+pmagV7/rnnw3WqT3zNAq1uCyywQIyVvVU1ZpDLOVP4PRhhmNE9ZELrJMhVa9bWGI5E9COS8SHmaCHDhMcmFCuvsGK02jSLU+7Yfdfhxd8DqVGw1VitWdpnNGOLBZ195lnxOWqxpLtJ5OhL/P7ll0cXTEO756nIvvTi5HdylhapH83xmsM1zO8xfLeosKFUgGoF9RCvLbvU0vF9SE2sSo/jyuH//T14rbWKmaabPpDHNTHrRh7J+bJK7Z/8ESAXTeaOy3EfHlxuIM7ovc7N5whTgvM2Wcp7nf+Siy0eruXEsXkJelldky2GbR7/1iR/4nHHRRWT+eeeJ/6b9uXYqH78pIaqbbPBTYp1Nm+4XtV9uiNHjoz1aO/X6E3N6BwyoXUSMlXkghDCRx/9KloLCGvYJptG6wSBbLDeesWcs85W3HLTzTGmRjfMTMlLLrooih8efcSRUWLHSLaHHngwWj2nnXpqVKhYZsBSxeWXXlY8+cQTMWhPOYJkkB87i4c8D6KqbmwXj2PB0QD7RSC3zYcNi+oYXGMqE/6f/I/Xvnf++ZHwBq64UiC0X8XPIhuqGCP23CsORmFZcYmJNl595VXxbyoXSIXFSdEDuTjHX/z8F9FaYgUOXGnluO1HH300Cj9yIQ0Kds2WW3qZcE4vxqG/yJCqSXUxKcttgfnmLYZuOCT+fd+99xazzjhTsd7gwcXLwYrUkG8bdOLWXXudYsnFF49Tqpod48ePj4Q2dOjQyjMTscsuu0QLrZY6cEbnkAmtCzjogAMjsXDfLr/ssijYaI4lICFWkAWZ1CQeDKSFLJIg4p2BMPxtelLCmFNOjduhFptgAPJss8wcR+VxXU864cRIcIazfPy7SWcZiN3df//9USNss0CurBykSSljv2ABcJMfCK8Dkl1p+RWiy8lC+02F0Ej4fPJxy/g5U6XE2FhaZKyd57CNN4lDfa8O7ue++4yIIo+sQgSJqFmsW262eSTPDdZdP36GC/lEsE642OsE6+/SSy6J7rp9seCq41801hZaYP5i441aFr5hKa71NcFiLEN8jTqu7SDxZsfYsWMjoW233XaTxM+cx3rhhjVPsFw7Ip2e0TYyoXUBjz3ySCQfAobbbr11scA887beXZ995tlIOttvs21rgsBAXuSy1x57xL9pdtUjNPGohNPHnBbft8aqqxXbbb1NJLYdtt0uZlSrM4AmMbGmNg9kRrrH+332xhtuiJLZYnzPlSaVs6S4a4nQjNwzET3Fo8waRXJcym222iqO5nNOtvtksLB+99vfxalMhq0gK8fGajLUZN999okWmOf3G7lvMT6QqmMjUrl9OH7bMh+UG55mmiZUExphyLlmm32ycXrNRmi+D+RdD2PGjGlNCJQhPjhkyJBi5kDauUm9+8iE1gVE2erVVy/ISLNgtttmm1byQhaIAhmkhXZqsLpi0qDyYzb6zQLfdaed49/A5URorJ8EwXiksMduu7daeyynJGedoIREHE98Kk2Gop5L0lrMj7ouCw3pgcQB62iV6HJOJLTVVlk1LMoWQrPQuHTzB7KWDACEJYngWIzYA0Tef/El4nVARmkmp1kFpsdTsaW/xj3lOqf6sj9/9ue4gFl1ZVQTmilS3PX9R+0X9+/x29/+NsbWmoHQJHuQFCvrimBFp++pGgcFSxOhfa+UTAJS6msEK3f2cMPraMlPRn1kQusiTCufdqqpopw2kcQyDAMWR+LSDdlg/Sgtve5a68T4Fbzx+hvRimP9iLdZ5CZMfecb34huWoKMKAlw2zI6b9gmm0Rp68sumfgeQD5mTxrB53XurvosJDr+1ltjhnDxhReJpGLwC3dTgmDpJftHUpFZXbRfvxjjKlsZ3FXzNpWqbDJ0aIxjsUgJK7KyNlx//bg9x7fNVlvGshZxQc+T3W6xQveMi9z18rfkA8VbNXBp/mkZYm5zhvchU3B86wXicgMwf9TjhOOOj27boGC5LjT//F9q7Omiiy6KROUx11xz1SXX4cOHF1/72tci6ZXBsps/nMOywb034T2je8iE1kWYiH5+RZG1LF0NAvasK3LXpjeR3U5kBqySG66/PtZQkdqmIvvC8y8UZ5955iTlCkAvi5Ui/mbOAGL4wdsTq8wTLPwTjjsuFv4iWMkGUt1KOeCxRx6N+9p3xIjinrvvjllKcTlkIzD//UCkV1919STJBqQx4dHHomu56847R3IyYZ5Vctkll4Rj2jUeE+vSXACquo7VOZtZYEpV6k/0GdanbdiWbZbnjCY434suuCAmGxIkRJS62JfPG1IDYpimv9cadTcloG5szjnnjGQ2SyBc/54SrPFqqxNYaF//+tdjtrMMvx2Etnqw+DO6j0xoPQg/7OpsZBksq1o//lrw3ra2BQjI++qhM/srI51H9WfrHZPn6x1H+kw5MN4ReH+tY/iywJo69NBDi//3//5fzFzec889MQ4mY1kNx67W7H/+538mIzRZ6GmDS7399tu3WUjcFbC2kT2r0X6Ui6RuhGa5jo1GJrSMjC6A5bnEEktE5YzzzjsvFiCTBRo0aNBkxITEEZai2meeeabybAtYeSw7WdBGgdV9d7DC991332LuueeOGVT6a/avuNexsCRZvm0lMnojMqFlZHQB48aNi0SEKCSCAFEgEEmLauy3337RQqNUW8aNN94YXdHLSrHTtvDQQw9FN7WeheV1+3JsCy20ULHFFlvE1qrRo0cXu+++e7QivcaylIi49dZbY6KlryATWkZGJyGjvddee0Vi2GyzzWJgH8HUIzQu5xFHHBHfX22hHX/88cV0003XocZ0rVEsQJahAu9qIEey3gsuuGBxzTXXxOlf1VC6s+WWW8Z9Oh4Ep+Wtr+ArQ2iamX//ySfdmp79ox/+KGYNywN2O4zwo/bDTo8vCwYC6zH99UeTKn04Jouy3rGl41bWIZifejctRNckyeFwoW4bH7b/655TEknHUu9YexpctSShzfqBRGjUZ6trBEEMjXta3YDOLURAHalBe+KJJ+I2ZpxxxtiJUcbDDz9crLXWWsWGG25YPPvss5Vna0O3hffZlsc+++xT85h7I/o0ofnB+6IVoypRUD2v+t0C7Apk7VStK3jtLE4/bWwsVzCIV8X9LjvtVFxy0cU177SdgXPkggj4thfotfxV3pv2/nBwTcrgdiiHUM+meb0M2USlGIp+773nnmK2784clUXUnN1w3fWxpGLsaS3XxKR0RcTV228U1LRtPmyzYovw2HTjjWOhrwzolCzdYGVpVeJCnnNOS4cIcOtkO2uR+WGHHRbdvHIDuljXkksuGcmuPSCh1VZbLRIQIj399NMrr7QQLJFIMt5+7x0Bq0yZiW0Z0tJXauD6NKFdeP75sfZqrtnniEWYKtPXWn2N4uILL6q8o3M48/RxsfhVmUJnMXznXeNntSXtstPOxYDwQ1Y0O3znnTskOVQPWq2WX3qZ4sD992+X0EC5hJalatICbVczTDNtsdfuu1eeaanId8yzByK/9+67I3kedsihsbQCkJzzGFO5JvuOGBkJrtb2G4ErLteXOmPsA9XTukb413VdbZWBxU+mUIEtEkME//3f/92atXTtDz744OhyKmGphsSBz2hPS2AVDRgwoDjppJMqz9QG8uFmUrq1DY9jj20RCXBDu/fee6PVZh+dwc0331x85zvfids74YQTOvT7aXb0WUKz0FWvq54nfZO+LI3gZfPa+8456+xibFiQquqrK70fDz/YscEiI5Nz7NFHRwtt7JgxlVeL2BhtqrjnNFLXm5q+x/Dd40J/qjKujFQQi1FRapJe1sytgZ0ckXqvcixG07v6sdODJcRStHg1fas9m37qqaPVd/+998Vzk7nSbqUX1Pu1WlH6AL2eswYL66EHJ7egxFwU+660wgpx2/Dee+/FImAFuwp9dSUgq6Qscs1VV8em+tMq10StmwJawekE21Wf5lhYbu2Vn7SFq664MvaKnlGxUNSt6UCYcbrpiksuvjiGFB4O56a42f7uDt8pUlYHR/HDsafv343E8Tz22GPx/5U32MYpJ54Yrfh6GUBzAZCAYL4hJwk77rhjzCLWKr84++yz42fuumuiwgi3sV+/fm12OigPETdLRJYepLwdn/Nl5Rm4Uq9Uph6ECyQNbE9crS+gzxKaRm4tM/oY6y0g0jwayRdbaKFi6f4DotyPglDkAdddc01c4Bb0CssuV/RfbPFIQInQnnvu2agiQS6HxTXXHHMUxx97XM07XSI0Wl+AKFZcfvm4PcW0T4fntQnZH7d47mBVbrDuulFayF34iMNGx+PTAYAIL734kkBg9xaLLbxwlONxjI5FfI9G2BKLLBq3M2DJJSLBkNz54ovPo8tZj9Asjs2DW2x7yBn0hSIsVhm89eZb4Zr1i/2dzhPx1iK05HIiVm1gi4TPkAyy7TPHjYuvVcP2tGElMq2FRGga5sGi3mmHHeJ3rVD48ccmxK4I595/8Zbvy3eCjEkzcZfTudFz87pC4FdffiV+x66j72Hw2mvXdMO45mJlSEA5RDn2tffee8fMYtK+KyNZaLfffnvlmZa4V//wffqO60HMTVwuEVlyOREneSnJBoQn2N8VCyupgLAs3+kFqiXtoc8SmubnmYNrckZwE2vBj8iit9ieDz8GdUSar7lPN914Y6yetygQhsWpiVoMzOviYbDJRkMjmamm1wmwblgE5HVqVfLrx0RoiPbmm24KbueOYVszxnYmlhi5n9lnniU2ctt3tLymmSYsxmMLEj8Dllgy9o7qq/zNr38TBSQlOqh8fHf66Yvttt66ePH5F6KlQRvt0YcfidvVZsUdcx7iTDoN6hEaiOul/QKCd84C0oB8+803f7FVRQ+uHqEhMpbKWmsMig3sSJZuGUtvkWCV1FrE4nP03tYZtGZdsUOEZn/Dd9k1Xqtjjz6qmHuO2SN5IXPXhbyR75NopTYvRCoJQkZp5hlnKA4LriGwdLmrdwQL9sxxZ0QrTwzwD7//fbC8351M2ihhq0DmSIC2WYqBummaraniv1bnwh133BE/k9xC7xeM10HQFi699NL4OQ8WoX3PEW6c3F3kuUK4iYnP1TvW9uA34pgRZXUGtjeizxIaGecW16Q2oZHSsXD3DAs2QTvSjNNOF9UsLA7upR7GhPPPPS8ubtvUIM66o8d1wvHHx15M/YnkdR4sxUkSEJqFznrwWHrAgKi+odnbnRG56lPkQgEl2/kCOZLj+ehXHxVbb75F3DdCOOuMM1sXEjdquuByWogp6/dxWMxcPFYUzTNWR7/5F4gDbo8cPbpNQnvzjTejBUjT//XXXg+EsHyxViCYdFwIbaGwra2Di9IWoSEVmVBWJYvn5ODGnXLiSXF7ekw1r1djmy22LGYJBON7ExOsBYQm6cBKdM2QFXf7kUownIXHeqP+QWSTxbvQAgtGtw7JacJfdeVVohXuBoUIJTeQKVUPN6idg+tIj64WEJFuAATD1StbcRtttFFsNK/l+pmM7jPHHHNM5ZkiuntiV21BfC0RmrkDJ4breOSRR7bGvlhn5ba6rmDnnXeO23rggQcqz/Re9FlC0z9JedWP/U9/nDwlTaMMoY0IbkICqZ2ZgrWjaZpgoYW6RXBTEhBJIjQ/ZISmcVt/pB5DUjkeb4dFX41koZHS1l8pfpFcYSqtSyy6aJwzkNQqIqEF94ySB1fQMBMa+sjBMe4ZtgeIGaEhksBoLVXpwdKcMyxO1thdd95RDB3SIsbIxWqP0GCbQFZij9RmHbPsZ0JnCE0pB0JbKrhVnneN9t93VHHAqP2Kn747ucqsZIv3k2MSm6sFhDbLjDPFa+G6vfPjd1pDBNzPLTYdFrch3nlnsIo01FMMSVnQg/Y/oFgwkJYe3KUCIR16UIu15magnEVzPbcYEdYavsICVvKAADSUp+8L1g/fn0yk76saLFyfkTgArUg+X61eCynG57uk4rFpIN5dd901fv6SSy6Jvz1kuEq4uZVnW3QW6QZ4dLhWtn11Sbqqt6LPEpp6K9LVCMg0ppdeeDEG0h8JrtAbb7wRhQUXCIt2zWBuc3+4R2Ip3i9wy0Xx+vLhRydlLjhL8tnr44LLiYxIViM0ahZgJJzt1vpBpxharYZsP+D1w8JjSaUgs6A3wj0p3JHFbd6vzBIQg2OhDFxppThzQJDb+5SBWGyykJIhLBHWigVD4QJJdJTQiDCKLYnXsVhS3A86SmgC3q4ZeR8k/Ga45vC3QD6uUSLzMsSeSBvRmytXr1vYyMr3EF1sMbTgLlaD2gcy42ZyG1nZNNgWDC5ymkPA8nJ9VgnWmxtSivX5DUgI2RfLeZqppoqkVw3freJVBLBouAmJzYFz5f4puK11bo7dIJRhw4bFvyUilg/WarV1Ja6mNi2NtNMnqk3pwgsvjGUfKXiv9er99xsj2W0KVSLL3o4+S2hA/sZdmEWDLFhBFpusJpw1blwxb1gA3MYVllsuvkbRATFYrEcdcUSU2Vk8fA6B9F9siWKGqQPJnHBi/LxYm8Xhjr9quFsikR223bZmPGOn7XeIckMsl1oQYxFbsshWWWnFSFrcvl9++Mu4UO0fgVqgSiiOOerI+DmLltvl2EkMiaMZvoJkxAfFo7hm4nPabmQ5p/n2t4OrOrlbnCBhgcimm/o7xbprrT1J1o7lSt4HubtGAvG2l2YHSMLIuiZ1XHJIrD3nxV32fXhPrUxgLXifwDh3Tu3XOuusU3zra1+PmeBqIMT11103hgqQ6DprrhVvauruqKOA70YNm9gZiaMUwLe9/oF8HSPrbNmlBkQpo2o4np3CzQMB6N3kxoLtiGkho1pAloL7Jqa7bty8ZK0lKPcQVyMzxKJDdiuF712h7PXXXx/3SZkj7bNRcCzc2epi3d6IPk1oYMGTfD76yCMjQUnnlxUHHnrggeLYY44pjgiWiwLSdMcFP0Iu4ujDDouTkLiBSLL8Q1d+wYo6PLyHq6rMw3ar8dwzz0bN/+q2mDJefvGl4pSwsLhTF4c7stgZWCykd0YHF/LoI4+KRJoWIogfOT9lCuJnrI3Tx44tjj7qqJiweO7ZZ4rxt9wag9VKRCQl0rZrgRXix+19r7w8ae8hF0sZCEuHy2LWgPela6IMxnkmEUrvMUNAnNE1OuWkk+ICTe5OW2AtcanEpSxmD8FrNW/lQb1lvBOs8NPGnBpczmPCMT4ZLWKuZPl7PSZcFwmAcWMnFqe+EazX9D1K+ogl1gLLMcWcEFqKLSIZMTV9lLW+f/tfKtxgEBKXUdlFuTgWXHPEMn24AZuf4H3fDTcmNyLXwTBipN5eJ0Bn4Hw2DzdACYdarVK9DX2e0DJ6JxAeC2XjjTeOE5Fk8rQbLRcs6a7on3EDufYkwk22Yg13tUxhhx12iITG4ko3KC4lIqrntrHsEAfFC1YY8itnet081w3Wpe2Krflb4Ss31j64oMjc5xqZjXRdJBrEz2qFSnobMqFlNC0ODO6x9iJV8SrsVcuLKdUreG0LssISLLKaEiQXBQu4K2B9OS7EoxYsdQUgR5X8bQXWkbLPKfdQf8a1T2BxLh6OzeusN7Afz7Gi1LtdcMEFxXXXXddhd72jELftyjVtRmRCy2hKUI7gfqm7Qhq3BTfXYi+3DnUGLB6zHYQPlLp0B6cF116AXlIgWVl33nlntCAF++shFdd6kOQuw6yB9BpSRFqSD8o2kgvLmuKGNxKSDY6lrVBIb0ImtIymA2tF8Fz1uhYqrqISBQHyerGzKYk0wWmGGWZoPZ4rr7wyWmhlq6saYl/UaX12/1KdHfc6WX3qy9SscbdtXyV/T8GxmzilqV12vC+gVxKau5dslfqj6ocMZRnubuRsBPxTjEBRp6D7ezVqgHoC+juVUEhGSO9XB8QdswLbX4S7vXPoCHyG1ZG25ZpYBJQevqjcxZ2795RLIMrwuuC9EoD2gvT/CPtTha9jotpKsB3STIan/CXsrz189umn8b21YmG+VzEd8aKUBZTxQwTVWUFwPSUmJCuqz+E/8bh+H/flOrSHzz79rOW4KkXL1eC2KjlJfZmykYL3wB1sa0gKqIVDUqw7emUJEjzI2jY1q/tujzrqqFjiUU5mNBo33HBD3Kfe1L6CXklo2oL0La65+hqx586EIANvtc3svuuulXe14MLvXRBLBR4ouRlqsRTd3nHbxL66ngKi0bWgFKClRmr5SWZvalMauuGGsZjTQylBvSr1BPV0yiZSg7b4zRabbR4/r4zkqCOPjMT4+Refx7ow6h7lUhKEJPsr46iOTnFxrdqpBIvUlKe555gzll+Y/K7mDpCIYTFKX5SaDF5r7djmVA9333lXHJ9njJ7SiptuuLHySkvGjYv1ja9/PT58n5r5JQYE4KutH9X9A8N77Ne2ZKLL8N0rxfD62oPWLJ55un4wXX+nbTku5Tfq6xJcm4svuii2n3ld3y53mDWlrhEMEBbAr76hlqEmkEosEilbXsg2ZXIV5iJnbiCrrdEuZoJ9LLbYYrGNqiwk0NvRKwnt5PCjJxuj7kp9mYWs7cjfqtETWAA6BqoJwoJXh2SCeU/Dj1V1vMr37513XhzAq68SoYBU+SEHHVzcctNNxbHhrmzBkMZhedQCK1MRrXo0Vt3nYbFtV+kMOPOMM2K9mx5WjfeggV0NGhWJBIXF/cJ1U0+mfk0haT0rDiFrI3KNFbPusuNOsbDVtCVQCKsIV0eF81N0SystVbuXIRMoKK/Ql6qIurqFF1gwNryD2ripvv3tmAhQCa8vdkD//nGyksxg+ZogdfNAjQrUo+lGIXPp3ECczLXcbJNNohqK5ng9rX/4/eRWIcJeasn+cZ7qJRdeVKy28iqxX1UhMjz80MPxHDcZunEkyTlmnS32UiKgq666Kr5H98Cq4TdY7zqCmwrtMedXJhFEJx5nexrfxdpkM9PErEYDSbIov/Wtb8VOhBSj6wvo1TE0agOan1lg1GTLcFe97977Yk0XAnM3T1+cmi0V/x0htFdfeTXWVdUjmAR1TPoVq3/QLJiy9aOo00J7tmIteC25SgKzrBJ9is6tFhTmKppFHsAaYvkRsfRDFX+RxdOnCCrzNx06NJJk2uYPAomOGjGiGHvqmNgvitCMoKsFtXcsHJ0BwF1HkPZn27TT/K3mC8ztVNiqHq8aaWjw9wLBgJuNvs4LK8N31193veJrwdWUBZQIoKLxnammirGpai1+zeQKpkkkgRo8f6cOAiMCKWs89mhLkH7HQPS+89TzWcaFYXE7rjQIetzYsfFvXQmgQR/xp66CocE65jYiIEF1GUKERE67LXAfZWrVfJWLWIUi1JfZHrJToCsp0hY5dgdq52RSdS4k0YG+gl5PaNxO7TWpEjzBlHAL252bNYNELr+0ZRBFRwnNHXVQsDbKFk890N1yl6+V/v5dICrKDwpQWRVbBvetXBgrLvPKKy8XZ59xZnAZ54/HV8/VINCo8p5yBeg/1RCf1DFYbSxA5532wTUtt10lYvc3y6stQtMJgKCOqzRVc29db430iFFNl46EdDwtah7fbb3WZSAG+3uw0gTNrUMUhxx4ULQE5w9EZlGnWq69grXt702Cy1kNljgyTMSp2FcLmOvDKnZcWrdSD+exRx0dJ8mLnVaDy+2mQMASbg5kwiLbf9SoSCprB8vfNU9SQYeFm+R/VwhNszlrlPtp6HBb+OEPfxhjaD53ZkX+CLTaIRfPe5D1TtezJ3BxsNbth35bR6S/0w3ZemMBs2jFalNjfnvx1ymJPkloRBcpWmh9kb15JVgZJoP7mxtqcXaE0Cx8VeNUIF6riDCW8Z/wn1Yg3QJIQ+zFEFxEIXieYIjv/IFcuWqIJok8JliE+kZnDFYBWWkEVwviMyaVrx3I5I+VgLouiOnCYkq9lGJn3DrSR3/6Y0vjNLfTAtWjWYbm6/YIjcVDASPF60gZaQ9afeCqxUsvvhTdNFYlIoWzzzwrEtqF57dYXQmuJetUS1UiVsSGSDT0s8BYZ1xOC9/NRIznf4Jrd3CVxA63e4fttovXKwlN2iZC23/ffeMNxPlT20hlFUkpJVldZWyz5VYxxvn4hMfj36SP3AxH7LV3/I05X6GNlCw45+yz43EhBS1ZDz74YAzqJ3e3Ht56661WlYwDwneeQD3Dc1xrfZupj7Mn4BjVwBmSUhabrAXnLkwgacCi8zlFzrOF35Jj5WIjX3HE9jyYKYU+SWisFgvFoiNDY8EKZrOOkJ0WpY66nG2BFbXzjjtFy0zA2I9+uaWXiWKRt958S+VdLfEebqsYF2sRqVm0CbFd6KabY1sT62rjIRtNouKQ4HwHrb56se1WW7VaggQYWWiJ0Fgn5H8QTcqYandiYTjvMjpCaGJGCCoRmju6vlJJmDdeez0u9oErTSQ07/P+6sZud3FuqmuUCE0gXqKBJcRd427NFMiTa6aui6z01wPJiZGVgRxNX+cWJkITJ6U6cmAgCkQuDiZxlAhN/24k2op7W4aYpOuTCE3Dv+uy38iRMWsrXovwEqFpWSoT2rXXXhuPleVDv+z555+vaWFfHr4r7Us+p1RCVlrLlMlRMpopY9pTYEkmOaI03KUWkJPeYhbczME69/62Hm48ZhqUOx++LPRJQuPaITQW2fHHHBvdDYtZDIcaakcttPZgkYp7Cd6StVl+mRY5GHMa//Ln2oJ7p5x0chRklBmsBdI9Fl6t2IYFJfGx9RZbtGbTxAann3qa2KcKXELkPXSDIfFv0AdogSaV14SOEBpXjlt4eEWx9u0334qBf1YNt0N8jpLvjyrXn7XFRX3ogclnChx68MExHndX5bojPcmZcYEgiAyKl80XiIWFqk1omkBQ3P1ajfQHHXBgtMjS7ALqwjMFq+P0MS1KKGSANOWnhMPBgehc1/vuaVGrLYObzILV7wpXBgL1+0i9ngbEuE7KQ0CWXBbWYpa1TOobYn/+RW612qoSmSBucTQqxeJnMrgmr/ck/FZZfiwr06GQT9lVTP9/U1g7FENSjFDygzKvJAXilc3Vw5qsPO/x4DKrHaS592WiTxIaxViLWuzDD8tXpQ4sZRZTDE2Gzt2eW6WCXGN3NcTOWHlpbFs93HP3XcWywTqrjqEpyxDIZy1RmmWlCFaL0wDrSeCdFBDzfvWBA4t5gtVSq4A0LtRg+rOKUlO04+JiyuApa0DaXFuB7QTlKWJorMQyOkJoZIuiUkY4rth+c/750TIShIcjRx8Rg/FaicRUWEWs1VqV55rqvZcYpePfftttoxLGcccdF12xdcJCQ3DbbrNNtGT6LbBAvEmkWE0ZZjz4DvfdZ0Qk+h222zbGSZM776ZlX+efd15UK+EWU/z9qNKqVIY6Re8VS3NcBB7LiQ7bck1ZeYjAtr4b9p0Ws3o0bVAyscogZA+rG8hZnVtvvXV8r8wiUmOlSQBQuu1psBjXXnvtWCunZKTct+k1cTFlIsjYOSErQpasTjdoay2B9+B8JC5YekpYfEbtoHOqpzY8JdCrCc2PL6b+w4IToC6Dbr3FKnZFNsj/c+ngsPAlTP3tqQKh3R1/oFL6U4cFVJ2Z++tf/hrcwxWKb4cvrL3eP6KN3LNyRhPosokbKddYOPzoSf+oS0uFnldfeVU8NvVgguIsS1I89ZICxx9zXFxs5fmOyIVVZD+xvCC4QeUYHit1vrnmbtUkS6CCgRS4b21l1Iyos13uon+5xKmkgOuMYFlx3LIF5p2vuPbqiUWjZShMlQWddabvBisvHOusswXraHRx6KGHxmA5a5O7znphrbHmWEu14PqxElldvv+5wnGxnJKl4UbGVUSYjpvIowRHLVigJNvTcfmM40okzzJL5+gai69tWLHK0kOLlkWPoFhq1STseJEJC8e1o4XmcxQ4zBkoW0s9AXE67qN+0nI4w34lMwYPHtxKSuJ7XE5ICaR6EJOmdEtFxOd9d7aVBv9MafRqQrMIxR0MiKiusPeaEgOunXQ8GaDk43MLLeZPPv4kEscd4Qfl9XLxacKERx+NmTGB5q7AtKX7wkI99+yz40PcqLwfx8ByOTu4g0oxxJdYa/WAlJDTAftNbJ1xrlwvweprg+vFGk1w3BbjFsOGTVb0+cc//ilaaZRf21pQimhNUpI5vj5sv/payMixZFmH5jO0tQh++5vfFjdef33clmJn1hOJHHd6NwOzLalW7BSsJN9fPWIHBCleSknYxKty5hje++l7McbouGyrreMSy/I9OC7fUfW18tsRy5NU8B2xXFItGgUNPaaORzO5AtvqCn+Bc9aPLgjHecstt8ShKsikpxvDNbRzGal5vF8RhXStERvrENGxHLn9yLX6OnYEkg1KUlwP7qeuDpbdlEavJrSvKk46/oRo1cletgckN0dwN5PgYjMBiWoBYtGI3XB7NHhb6M0Ox2vxeiTNMgtYPdm5NeKjEgmIL2nxKVNBsD0t2SMWK8bHgpKsAIQlfpesMu7+2LFju51djcmniqUmG0pQYEojE1ovhLu/MoRrr7q6+FeVi1uGH66snoB5W5bOlwlTwzWhy6yJ8Sh/EKvraResu2CRJUJbc801I0EhBLG05K4lODfS2Yilp6r/a0E4YM8994zkwiIEvwmdCMsss0w89oUXXjgW+VZblF0Bq5ayrrIO23ajmpIT7SETWsaXBmULYkksMg/V9kQNkUOzg0XGNbZwZQ1BUF1tVjUZc0W5m+11EjQSrEUTpbiSSRnXdXUDkZnlFmqzarR6iZuRoS6ui+SIUEKKF08JZELL+NIg9iYZ4CH2JBhdzqY1M7hXSQpIQkCMjRVmpkC1G6nzAVlz86aE5SlQrx4OoZApEmNFqmrdlGNwkVlpyf1tNLTfpQJicbVafb09hUxoGV8KLGyxJlk1i4xlU6t2q1nBQnPsFq0yDJal/2elQZm41HVpSq+VdGo07ENgH2kpE1ErSADB/E7Hx72XoKhVuN0oSLAgd98rd7faBe9JZELr4+B6dNXkl22lXdYRq8J77EdWt6NgPVhkiKGrSrRfFpBEqtlShyXg7/+5cqrm77vvvujOSXooZdDE3tOQLaWYK44nrucYXdeBAwfGY3PTaLSLWQ9uVvbpMW5c7WHfPYE+S2gffPCLWAahH0/B5A3XXT9ZYPy1cJclq6PHrhralQwU1gSteNPQ2t4Gpr72r+qWp47GqC677LLYatVWGUkCy0DRr2HBHcGbb75Z9OvXL/7glQ7oGrg8uElkidT8/exnE7XP1BsqvTBcWdkE9ylBkJs0k+Jg9XvicmUoc1E0PWKffVoKqdtJjljwBivbl33WK2EwqCQpZKRHUtLw/wpTUzmE9+n37EmkEiZDZByHQD+3099cY8mBVLIxJTBhwoSYsVbaooF/Srja0CcJTUP6umuvHfsm/Zj323dUMTL8oMndJFjU22+zTfGdb32r2HHb7SrPtkCRrILdVVdeJbYUmSM5+tCW1p/ehM//+c8oJpmmaztnEkf12q6qoVVK0Sq12vbAOiPceMRhh1eeqQ81ULJh3BGxlpNPPikWBtO0Mz1eh0fSsPOdGQA9MGzbsSu83WfPvYp//buFmLS16ZRA2muusUax8ZAhrUq4b7/1drHsgKVi5b95pAp/6c7VwzPPPB23v9kmm8baxX1HjqyrasxtS+1BHuJTfndqImVrk6qGh6nnPQnlH7KJ6sxkGPWWarNCbFxP8wo6oqrRSIiFyqA6f9p2PV1rl9AnCU1FuIWopSjBHax8l9BYrRF8k6FD47/lWZt+zMQCSWInWIT17jKsk5dferl45qmnJxkC60tkTaSCTp+32KqLNstADBqun3v2uUkKWOmDKegUjC5/XiO2/ficCe7Oo1xAysJIVobz0VjO6vzzZ5+1djW0HP9Lkx2/GrbFFlmk7o/x88+/iNfRZ7U6qcw/UoV9ZbvOlxiAyetiOQmuQSobECzXoaED4a1AQMCSTteaesm8c84VC3ZBCYpeUh0YrGhtVoqiQZM/ocs7KvVPWta0U7letklfbYN116t5Pq7RBuutV2y52eatrzuGet85YUdBd+fAAipbYM71oIMOil0AylDcUNoq6u0OHJ+uhG233Ta2i1HrkFxBZixEQpKJ4KckeAfG8bk+1HinVOa6TxKaim9yPONLihfVoB9G7VTHwJKLLlaMCT+EBJ0B7ub1ppyXoa4IKZLRXnuNQcHFW63Vurjt1lvDglozkEQLMalH2mjDDeq24JCI3iDcZVX2rxlcPVYljA/bMUV9ow2HRKUOFougrh/zDttuH6yPgwJJ7RU1yohdanVKmbZ9gst9zNFHR8LjlmkDog6yyUZDY5aLO+f/0/GvEY4/9UO2RWhI8KAD9o8WENlwZEHlY7NgqZwTXDV3aD2yrK71Bw+OPbcEN0GMiSvGwjGFnCuItBCj7ZZJhEw4ee1kXUscaCPTIXDn7XfEljE9sKBbhGyQodHAyj42nHsCYUnXp7o2yndI1n2eOecIVvu2sVuA+KSe4HrQwmSxejgX7T9lIEj7EcPsycXsBjRq1Kh4HLsHT4I1aKAMQhND+7LqD/1m0kBmZS1TKtPZJwkNcey4/fbhBzpXbISu7vNEBiutsELrD596xeqrDIwDNeDXv/4oLnCkpvm6rfS2xujbb7s9Lrhf/eqXMWZFMQPooOn7Sw3R9msB6jOthrv6issuF6WsHa8ygEQs3JjXXn0t3uXvuvPO2MBNBQNWX3W1KIukXeejj34diVmTNqKGoYEEd9t1eLSaPKc3dYdwN9cKhADcvTWvx+MPi0+TO3kiaIvQLrvkknh9rrv2umidmWae1GWpM1CBXaTfQsUjwUJgHY8aMTLq+h8dCEaJRpKcViN1+/jxsfMBkVNIMW4OAYNYljkF6RjowNGdcw21ktH3TxOLEIc+1t122TWqqujhRU4J1DRY4yy5MpAC8UnflanqPiMWWP27SfA9yhpqME+KEwaOTGk4DrVt9s8KMnuBFLg6sCkZL6uHpPMmGVGOe/Yk+mxSwJ3+/HPPiaqlLIdEAHDrLbfEYSLcGTAAQwzngQcmZtpMMTK7gDTOMv0HBGttcknpBNYIkcdbb745WljkrkFjtf2kRnHuIWUQfZvV0INpQb1Zo/0EkZn4/dgjjxYXfO/8qN2VpKfXCIS274gR8f/BPpDmGRXS3HTjTWIMEBA9cjikSjCxfPzrDw7HH6xDqEdorD9ijUmW290XUaWAuMfAQE5ianpFCUGedMKJxcwzzRS1s5CBhAPZHPVQXCaiio899mhsMNcEfkFFIBI5lQnN9yo2yvrzYHGlGwbi5DLuMXy32M+K0MrX2oAWv4WkoZZgsbmGZhiwCAlhUul4553aVe7cfllNyYx1gnXqfNWfJVd7SgDhnx8sTvsWi3STEMejXJJ6lr9MsLKvCJ6IpIDvPFtoDcKHH3wYXTeL3F0LOVCXmHv22aMVZlFKIFBt2Gv3yWVcBIW33nKrYtWwQMsKFgm0uijIGsZh2Mn6gdC4izAZoYUvlUVRi9BYBAOCpVWO24FFcuzRx0TiIkRIKcRgkURoLMKyW8VKWSa4gawcqCY0FhAXNUFTd8vxb9py/NzDcLeHeoTGsnOOe4cF7YdL+cOCSmTmsXBwC5HHtlttHVUxVllp5RigZplxxfQVKnFQM1WG89106MbRjQdJHTeIFDdEVJIA1197bXzYRxKXdJy+S5+REGHJlWWUJEiWW2rpyeZPsI4PPfiQqO4hgcDKJRlUrU6SIF7GOlOOcNppp8XznZJxItfCMGLHkK63WJ16r3Ks8suGUIA4nlhattAaCMFyMjliW6RgxJHIxSgBOOP0M+KDAmuMr/xo8ruymZ5kcapluFkEKX6UYhVcF5pmIFZmX+mO6V8uT9kNSqDvNe+cc4ZjndQdejpYOCYQja/04slW2WbZQhuxd0usDbhJ8841d+t4uEkI7dNPo9uXLDTHjwAs4hSI33348Bj3gjYttOAaI3FIMRwxsVSbNcsss0QLzXuRljgKUUDV8kAvzPs0eZfhOCiDbLfNNvHvq6+8slgwXHvuMLBSF1to4eKF556PSRLxtBTrdPNaMFyr64MbDIjRTSBh9GGHx/NP7mwZFtySiy4etfLaA7kjpRiC/WJnMrVqv6ZElwPSpObLtU9ZVseiCb1eicmXBao22sNkfdtKhDUSfZLQKNFSpHgw/NjuufvuOAHJ3dqPlmIsscNXX550ipCxaiSc1a4R/DvtlFOLh8Od2P8L7K8XLBdxmTJYEzGYHiwcZEcWh5sjFgQWr7s+RVSketD+B0QF1mrlWBDHYW0hVlJATz35RFyYMoT95l8gBq2Vkxx2yKFR4/+8c1pKLyxQQX66aq+++kosRVlx+eVb67E22mDDqL8GfvCOd/11BgdCeC5aO8ocZAId/w2BVJcIBJYImWQ4/a9aP0a1YoQouWjkciysb37jG9Ei4/ZwNWafZdZYrU66RqW8vr5E/ApPZQnFnq74/hVRspzb61qRR0ozU52H2CIrW6ZTAsOMUAvb+Wy80Uax/u2F55+LiRHXXkYYyJoj/2uDNeN7XHyRReMMhnpgmSFPSaE3Xn8jJh4E9ashqcHa9J3ZF0IXN+xpCW03B/VlLFtupvgdMiVlxPpuNrBkHatZoylJ1dPok4Sm5IE09LLBvfDYOVhQLwbLh0Wi+PK4Y46NsZgyxKgU0HIHSe1sMHjdmMGjmMrCqed+KDngprFGjguuH3WLo45ouctze5SA2MagYEmx2OiYIdlaeCdYh9xhLqM4EWFFpHnm6eOKFcKiHrL+hpG4uIySACB7KHAuBuRzCKo8hGVMIGbCkylzKPOqvs6De6vvDlnH4w9ultjVURUhTMc5auTkvYnA7TzpxBOjm5xiZ6sFy84kJxaZUoZvBStCBnC68P9LBNdQoiBBRbtFKYbm+Fwjx29otEJZ31WCZIb6NLFMbm6Swga1ZkIC6seED5RzJCC9c4IVLputXMV36zupB6RgNsNK4f1uIqsGYuc2lUsuZESVY2jtSRYR0vO+nrSQXA/FvIhUwapjIBg5cuTIKLvUjOAW+10YsFJt5fcU+qzL6cf858/+HB9pcVjUCKJeTdC///XvqFLqfb6A+PngnrSX+mbBpPf57L++mPh+f5svkH7sXqu3f3Cs9uszqard++M2/vq3lu1X9vPF519Eq44Sr78dQ/UPx3udV4L3ISPb8/9Q7/j/8+9Jz6UajktcUhaL+6Ncw3Mp86alSXsTt4z6b9ofsLwQmnot+3U8zruea5K+j1pS4QjXa7WI1z7dvJxzef/1gPB0KyxcKQpVClH+HKuMiyeDV0ZHtt1V+E3Q6teH6TE03KzFzBTSNnPL2BnBwncNiT1OKXwlYmh9FX7oKy63QkwUfJnQ2uKHS95ZZiu5oO7Q6txqQfDa4uSSNhNcU7plLCF6XixMiq8JtwYL19wABas9SWIJbsDasbjsjkeje3Ljy7M9mxFJRujYyszYKYFMaL0YLJsTgjV0843123l6GhY1IUFFlBZ6ynbSOWsr4ybju35wI2U9mykzd3dws1XcU1tNA3lZkQlnnXVWDHRPiWNGZtxJWUJkhhhIlC+44ILF8OHDK+9qTvCQJIJY6eKlUwqZ0Ho5EMqUsBTagyJPmUtN0EhgyJCJY/TqwVQhiQHxp2bBBRdcEGvMlKIgNedCVpqLzHU1h1PcqqdjQm5WyIzOv1gZd978AZYZC5gL3cxgVcp4UyJ5qjKHdUqg4YQmhuLOIv6SIPj8s/d6RkyuDPv2Q6iHeFx1Fn9bsbVq2Ee9/aTzr4e2jqEa9lHvmNo6Btvv6H7ae29H9lNGipsoOnWXTmj9XVT241+uqloqrqnXOnr9ewqOQUsTC42Cbuo3ZZGJYSE05RlJATahre+p1jUqo9Zn/U38kutLXZYE0b333tvafF4eUt2soKbiZmVWZ61McU+hYYTmjqHafbddd41V5CP33qe1pmuXnXaOjb+16n86Cq05bf0wHn/88WL3sO9tttqquOrKKyd5r/oghavqmw4+8ICY0UzwI1WysdXmmxf7BOtCVXs9+PHdefvtxU7bb1/sGH74Ks/LP0ZlGnvutlvMtml7+vzziUFqLUYG6m652WbFAfuNiiUY9SCOowhUC5Ks5+MTJvaU2t+9wS3aZccdY4nG7eNvm4RwFJnKVjrXo0Yf0abKgmyhIlT1ZLK/5bIU1++G668vttt667ivRx5+qPJKC1gPBgf77JhTTo4tSaA5Gglw1xKUhIwKVo1zV/uXMswynTKkawQrxGtUNDT5NwLq1JxT6qst46477ihOOfHEqN7hO1EmIymhY2GvioWpzisJOHqwkChYILlUFoKwTYLym/O7f/qpidllIEt1wH77xe/izDPGTfL7l/zQkaBNzm8mNd9LHgkjLL7YYpFYzS41WZ4MEGuHkGS9xEkzQaxR6Y44Wr0bYk+gYYR26sknRxUECgd0pPyAU2uR3rknH3+irhXQHpQo+OLrjZLzY1D/dciBB8bjUEuUGsARgLILaXs/IK092pOSAoH364VUn7TT9jvE0oByWUAZ2qcWXrBfceLxJ8R6Kft55KGH42sUTLVJ+fEpt4j1TIEoE/Qyaiynv6Y2bPBaa8WMWS0obzD1W7/i3nvsWSy1xBKx3QaMxNMjqXtA36GCX/MsQdmB6zR4zbXjuSrNQEi13CMuoqJgE8Zl9ZZfepmowpEI2lg63RVmfioJ6R8WmFo6+Ph3H8dOgS3DTcD5LL1k/7hwLXDTtVldV4abCui0WDXcpXfeYafivHPPLRZfeJFINIAULVo9oIjFTUKpTHf7EB2HXt5pw3aVe7hBlKG5X5uZazM0uMaUWZZbdtmoPJsITNbWsaW/FYfusMMOUW471XwpySFs4F+EtuyAAa2qLQZM+74VXfttOe9jw/eVoPdVx4O14ne3wjLLRvUQlo1WIWS65qBB0TiYZ6654zGsv+56rX2rzQ5dC1z16qb9nkZDCM3ioHKgdaYW3JlMJbdY/LjcCd2lX3/t9UkULfwYNCqXBRdZfpQxyPkgrmQJlIGwDL+1faTJUltv7XWilfH8s4HsAjncXwlMWpQG9SJJjeUqzYkLws/DQkKMimqroVzA4mBFxL/DtrU57bDNtvHv/UbuG+vRUumAQtA1V1s9Li61UX74qVj09UBOhuzqKa0GkkO+RAbBMapJQ16gSHjXYPFy6Z2rQtMtw48eHn7oodiYnmqxiFIqLH28Rh8qK9Yk8aQ8QZbHkGN/W7C6BfRVwqd/+lPUI0stU5dcdHG8CbxfadpPjepiYXobZQjTdlnGfht6Y4FumXYlRb1cp28Ht+R/wp1cnIUIQCTRMS1T2buKtwMp+L3oBnH+5bo8QD6uY7J0hoe/EYjAu2NHyINWHxQ7ARBzGobiPTwB0D+qvm3smDHxbzdbnSZ6VkHLFZUQc0jT336Hvl+zSL3GWgVdEAjvsEMPja6uGB69NccnpmffEi6KrHsLuJnOod5Nu6fQEEL7ayAnxZmq0H1Z1VAZT/VBpb7gquZn7h03dIdwV4azzzwr3sk3D+b5SsG8/l5FhFAhqR+KH6aF7o5WBsJgXZx8UssPCZJMjFYjLoEG9VQ5n9QaWGYTHn0s9kWmdiM/oM3DD52ZX42fvPuTaD1YzAnHBaJVEPrpp3+K1tDRpTvw5cHldAcWC9E6hdDeq1h+CH7FcI6svGq88cbrxdyzzxHdoATWhuuiB1HRZ1oI4E5PE4yrMubkU8JCWSa6T8DSQdAXXTC5/PO+wWLcMBB0coMMijXZnQDi++//LB4DWZ8ELVG+L3VaCnlV56faOha4nlWtUlRoBbG5ur4bfZwkeRKQruZzpPvow4/EoluuCX0x27Nd59sdnBhuBr4Xx+VmUN2Mj9DKx79LcOsdg4Z02Vmu3V677xlfA2KUSEU9lZs3vPjiC7FT4vHHJ94sttpii2i1FsV/YjcD6yxZh488/HAkWS6wm6r2tOeeeza+BizeRQOZq6xHBMAlR67c8rPDte1tmJKuZkLDXM5Hwo+TkoQ7j17Fcne9uxYyUpPkLuwOrSKcXhOSc9dbcrFFozQOXHLhRdENYMmZF3jUkUfGz1gAv/5o0nS5mJH+yLIKqzYad3qxG8S1QiCP1GfHMqQtdtABBxTXXn1N/Gy5C8DCVW1fHad4/rnnozV3U0kmRlcA4qTesHRVI7T4mrsusqQK4fU0k5ELGGV9dplcyZQlSewwxVTg8EMOjS1OTwS3nVV11RUt7hwgbMflRiJuSe016frr3bSgxYrKYG2K81l8yaLkZqvUV7VPWgjplONPlGHpi/3m17+JpM89THFK8UDXAaGLPQmss5aJSFargbjW2sEs8KuuuKKYZeaZI1mQvfHd7BbcwU2GDu2QSm4tCCW4uaTaPC67G1pqYAcWvJYpclHv/+z9YsYZZiimn266aDGq8eJuLtV/QLjhjA6/kwNjLJG1JjGQQESybA3DAaP2i83/n3z8STE4uKis9BRmERv0Gxa28ODyJnki4YQBwW1HXMpGgDv+3ZlmiseydUXOKaN9NIzQgDrpiL32iq6L5uVUq3PySScXqw0cGIPO3BQkIhCfQC1iycUWL6656prinrvvCQRwZvHd8CNL7T1665YKP8rf1hjSmgitbLlx7VhHb7z+enEKQgsuTwp4Sy5stMEGMaDNzdLoXCY0rTU0tVgXZbirLhrey9pK4GpZyH7UFo14UwIVC8fw8osvtRBaeJ2bBbYtmJ6axstIhKavMYEMuBvAU088GS29FB8EfYoIzbW2gNZaY1Cr5eFcnXtS3khIhOY7+mflPH/+/s9je5XWJ61GCC1pqgFXUZ8kFwqhsawToVl8VCx2CJYVckp1W6r3KWWM3Gciof0okAZCE2qgNMtVnX666WPjupuOAPmmG2882fXnBrMAXYsjDjuseL50fcq44/bbozWffjvIiDSU5v+EfcJvlP4aq2jJ8B2xgjYP1wKScGO/YLmzFFldWrGqkQhN7DSBJehmyb2uJrTXX30t/Fb6F3fdcWcroQmxIErdFLom3HhdUzf5FSvFySzejI6joYQGzEwLj7V29BEt7SGnnHTKJIQWLZ0bW9QgALmwyOhYkfBxV/V48YUW3aoLKi5kLfkeixZZCConcPdYJsgOGS671FKt5MriWyVYi+PGnl48eP8DgQwXKl6pNBVzDwSKuQrVsBC5qlde8f3KM0WMn3AdWUICwGVLSE+j/SpXoRiB3JKVIC5IrpqSbDVeeemlSGhlMkF8MmksWgR18YUTeyKJHLo2LC0uMEs41SixZn0Pho9UY6+wTZZQsuZ++IMfFIuGG8PmwWrjajoG7mGCJA+r5p//989i1512igs9kQ7xSb2aG4YbhUV4TyVJwRLdfNNhxfBddo5/w7NPPxO3bTFTsO23wPzRRWWdaFTnopYVMhK4xhddcEFx4gknFMcfd1xw+SbVNAO/PdaX7YsBugmsFqy1OWaZJYp4BnaJ70tJIplkirniZqmxnOKrc1g3EBMgmJQoKePZp5+OhEZ8M4FqyXbBvdZqJtnC2k9uF2sXeT77zLMxpodQxeeUtwwIvyt9ozLaPAPH5Bg0npctwIz20RBCcxeq/tItliQBQ864LUI7c9wZ0VWVGaoFChgWbbJwqiEovkNp0AmVWvEex/XQA0hr4dbAsIU09xxzxsUqxiZLeHPlWH71y1/FbNMZgeyqYUGxNg4/tGVYih8qC0dJA0gOEBdMP2AuDxWOf4UF8cSECdES5DIDS3becIdmTVRD7EnD9zlntcRM/vrXv0QtNkkCBLLuOuvETGqC+NS2gQTglptvjgtFtgycI7f3qRqlC2cHK1hMMEkbORZul4X02KOPxWzv2Epwnvu3VnBl07lTpUCsSViRysgCwSrSXygG9HpJpJJkD/WOZDWyVt0YBIvFFFlo3E37PTRcMzeis8LvoStwXckHIZKbb7o5qpWY9kXrTYwPmSq5KCcFVN5r9k6lGOJkjkUpSVtwo2Itu2GCm5okATEAGH3oYfG8UxILGYt1SvK8+867wUKbp1g2nCslCu1imut5JkpDENn/BquRSGd1hjajbTSE0ARKWVRiZ2JMLC7qn5dfell83WJkwcQYmh/xPPNM4gIk64c09KMPP1zcW3E7U3r8umuvjW6KxVAtnwx333V3dDOoKbRIP/eLnwEN3ciVmylG58ctRsZSA/EdstQUIrgIKyyzXGsCoRq2vVBwRS4L58U6W2TBhYrHJ7RYUoL4jmFccDuVTCDtKy5vseZYKuJVyiRkHlk3Ske4FrXAcmN1kq9xLZdbeqnirTffjK8pp7A4L7rwong9HMNDD7RYUqSwuVGsOfuhdbbT9jvWbNoWn1w23ERYanfcfkeM8ZlURMdMtpLMEquSiCKpcseT3Kv3fvpe0T9YfqPCtSPL47vdI2yHnA1SKxdSmhNgO4cHN5H7Z+GOOaUlMwhGDCJDJDIbFYngln3wQdcmFLGQSUO9VLHsE2STbX/11VaPQoxuCkPC78HNY+lwDbYPrmW6EZ0QLEDvnX3W2aL7yxrdf99RNW+2spLLBSv85ptuimUrSD7VF775Rkum1U3Azdv1S+Uq6hWRqISIwcSugfik6UwLhd+NBMXMwWrcbuttosUprkgxxvedCa5tNITQLBjaWRuut34csuHuZyGkhSSeJGAu6CtOooaqPJEJpKS3D1YWORzkgzxSjMZC3T9YXSRuLr34kvhcGd4nHsPFUFph3+kHCu6IMnOUKQ4I1o3yjAQk627KNWHyc5/qgYXEchKg51I4r/9ULFP7Yw201LmtN1lxLxIQu3EMZIrKxb3VkFChfzYoLED6YoQME/ygueCCz0pV7g4kXbaO6XjtvP0O0eWSRW2rbon7w8UTuN82WNPKEnasWJxuJkjNMXDXyCSVoa6QRer104LFdmNYtOq2KEFU47577i02Ccfqup1/7nkxTJDAUttlx52KbwSXUyN4OT7YGYgLSmiwav5SydwmcKfXCtcLUXlsv9328ffl2iBwOm0JqdNh3cGDY0zM+DtlQ8mCK8MNSTmNa+BmXE7kAD2+YRtvEuOa55x5VgwFEGLUlM8qHRbWiWuPrPx+FaFKAiwZbhZqAt3M0kN9p3rB8m8qY3I0NIaWXM8UCO0s2vt8rVhGGT5X77Np2/XQ3rbLaOsYu3MM1WhrP+0dQ0f3471uPHovLeQTg5VT3m5Hz5Wr5PMsnPLNJKH83mqwYFlOPi9+lDoJGgWab2nknEdS+LglWG5qzB4OXgE4PplMWmfKWDqKjlwjN0PijKxYccrUsO2zLFqk6thWDJaaco2MrqHhSYGM3of3g8WqpUczMdnkzgIhkbWxIPUcdhasjjQhSIC8kVLWLM1BgwbFbXPl/CuTCYpWxavUCiYgmHqSR10Fi1uihAWLzFJxLriZmHDuuLj83//+xKRTRueRCS0jWg7cPQHqrrTWIA0yQKrZy10enQFXTKZTCUVZf6w7YCmywhC18getS4gjTTLn9hnQm4qLewLIUfZWWQYyq5bp1iGBVB0XPbmM7iETWkYcVGJBGf7RFbBwTPehXNtVKLhWi+Y4jMRrBLh5SIxlxMUzOg9pUrFA3BICspw9BbFfViC3VnysWs5bUoIckHMmS5SSYBldRya0jDhT0qKiKNEVSAj4vDhQqk3rChTk2o5G8JSF7g6UQ9ieuBS3Gqn5m4S2obymi9cK9jcCyExcEZkhK5nzcmxRgkCszvEgck3pZbLL6BoyoWW0Vsdzz7qCNPCWtE13QBeN6yuW9M4771Se7TyIC4pL0RJzXKkPkgKE7XtO2QT12Z5wN2U/kTOrlYIHt7NMVmKGyM55Og43hFQMndE9ZEL7ikPsKqlJkEymlX/XXXe1qaNWBouMtaPavrvKpILn3ED9oOJ6XcElJKLWXz+ej4cuBNOSgIS158SzjKJLYgGNBII0WAWZIrNyT3OC60vfzHlyeXuLJFBvQCa0ryhUycu2DRw4MKpLWOhzzjlnlNDxt8B5uUC2HmTpZBEF3btrZSjXSNYiC6azYCGussoqccSbAlXbocefilFJ86jz4uolfblGIsXsJEfE6WqVn+h7Vcjr2BBvueE9o/vIhPYVhHjNqaeeGgPk3CKLiyXDYmEZjRgxIj5HIrs9cO+QYFLL6C4IAjouswnaQ7n2yzkhCgTGXeVOOof99tsvunhiaIQTWUYTqoqEGwHEjiiRmTmUtcgd4Y0ZMyYel2uWel4zGodMaF8xUHfgbqnJ4mLSxzeDEiEl90jjNyvHNPD2Fr8CVFZPR8ivI7A97pr9a8+CaqKUrURejl3dm0LUww8/PJY/kH4GcTPEofIfEK8KfYNGGg3kNWzYsNh1oGi3XkLDDE1k7bh6o75Zb0AmtK8QkIVK/KjIGtxE2lv6cLma3LEy0gi3cePGVZ6pDYoRCO3ckh5ddyATiKwE7xGAzKsuhtTwTlMulTp4OBdWpmPgJqdM4oUXXhjLNdJxOT+j9hoJgX43ASUZMqduFLKbtaC0JY34875a3RQZ3UcmtK8IuFwHHHBADESzfmQUQUbO39UuHovG/EcDbpOlVAtHHXVUjLl1plWoPahDs/CnnXba+C+yMFIOlFmQqGZdpoHGHo6hTKqKc5Gd83SOCO3Oqr7X7sB2BPMVy7IMZTXrlYAQnUxxMy1eFE7qtUpldA+Z0L4CYIWdd955sUyANTZ27NhWC0E2E2lx2aohwM1SSlnCaohNaWZHOI2crclylIlMREWeO0EngmC6f5WLpISGc0tzDEAJCvcOiXM7xc8alU1ERlrEdBmwAo8//vi6pC9u5tpzR43AY3V2p1Yvo21kQuvjQDqas2UhLX4B/6RNBvomkQFLqwyLlpwNsqARVsuiECtChjKlaYpWI0CmiCVp3wbtlmNoLEEZRPtW34WovM+8ynIfqlmW3FCxQv9yQRsFGVJkpuH9zDPPrEtmrLjnn38+Zl5ZcRIxjbxOGZMjE1ofhxiPSUwWvbhZdeM3ElDcWavdiMa+hShGVAtcLAkFA3AbCRlLVp9jduxlOH61W2JVWoUMsvU+7md5DoQp7pQtvCbhUd1D2VVIkshmujko3m3L6kO6w4cPj8fgM11p/M/oHDKh9XEcccQRcUEhiFo1Ty+99FKMVaXgf9kSE+sRR+Mq1apJU0jLuuPWNTLILYvJlXPcu+yyyyQumuMrF6smyWzCkuX4mGOXLWXhNUrBQpmFNia6cddee21dgc4ErqZjY8USdczoeWRC68MQBJ+vogaLJGqRjkJPbpmJ59VAJKwbcbRahagWqW030p1jZWmSt10Phbbc5npgrXkfty6NmAPnKq6nTKURULSrx1RcTjN/2W2vBR0YLF+JiTR0OaPnkQmtj4JFtc8++8TFLnBfr82He4ewCDPWgliRbdRqa2pUD2cZ3DTxPJOQzCeQzewIoYnj9VQ/pHgcvTjWqHOtFU8sg2vJknNczqO992c0DpnQ+iiosApaKyZtS19MwoAVoe6sFmjeW5j6D6vBkmKxNLonEoFx58Tn9EO2ZQ0lpRCKGo0qySiDu6rAmNudSkfaAndY8J/LLP5HFikT2pRDJrQ+CA3SFriFLgbVFsTQZAHpdtVCqrgnUlgG8hDwFqeyaBsNrid9tTXXXHOSmFk1koUmOVB2ObsLLqtGd+Uj4nPc9/aAiPXHpunxVDS0RGVMOWRC62NANEoJWAjzzz9/65i6ehAbY8nViqHBaaedVtNCI7stsyjo3lOlCLKrLKN6rURQ1lBri/g6A/sTF0T0+jKT/n97YFUmpQ/dALlEY8ojE1ofg4HKFiFXELG11zCuaFbWrp7LmZqpq8seWFA6DBBaWzGu7kCpA7ezXjaRFaXDwfGx5pBsd6EURceBbdp2Z7KTyVp0zN3Rc8voOjKh9TGoqreoqLGmOZptQRbQ+8vV+JDiPiw0Ra5pMlICN1MGVX9kT7hVJH8QMyuwrfIIxb+ytILw3U0K6LfURSFJctxxx8UMcEfBvTS7gFXXkVhbRs8gE1ofguA8iwlBsc46AqQne0dupxaSBVQdQ5PJa8tVbQSQJWunLZdTJT4S6Yp+Whl6VwlAigmy0MpFuu2B9ZqKl1lpPTl0JaNtZELrI2BRkdJRHY/U2oudJSRCq5cUoM5hoSqlKBOLRcwi6eocgo6A8qvC3rbG2rHKdAV0R7BRXyjdNFZtZ+WFqH8gQladOB6CzfjykAmtD0ERLPLRHdBRN1BvJJet2uUEcaCk/KrVZ/z48ZVXWspCyG5Xu6KNgngYq0dsrCebubV3qdOTJe0smbnGms01nns0SkIpo+vIhNZHgGxYZxRTOyKdncA6oSdWq9qfcCKpHjM3EZvMaSqi1UYltqaOrScg0aD31KzQngIX3TwExbtd6XbQxykxgvApk2QVjS8fmdD6AGT7uIQWFhXXzmQd33777VjeUR1Dsw0ulG2yXC6//PIoPaRZ/frrr4+uFRnpntLEp6TBdR46dGiPEAXSV+M2ePDgLqvYJnecq5oHnTQHMqH1AdABE88S0O6sC0j4UXN6kqpOUFDredtMMaw0NcmUKPVWFFh7KgAuNsWlHTVqVOWZxoFSh95PLi3FjK5A7FBrFguWJZvRHMiE1svBekm1Yl2RmKblxeUsZwmVLyAvUteskFSwighS4aggOFf0d7/7XXyt0UDSXNxawpPdAXJW+c/6Y3V2BQbJ6B2VXZVNbisLmzFlkQmtl0PwXKyJNfPII490um9QPRlL67DDDqs8U8T2nSOPPDJutzxTwLZT8agHC6eR7UZl6KFEGOVERHfBjdUStvzyy8ftd6Ug2A2AXJLzJ6vNZc9oHmRC6+WQnZSltFB1CXQWFrnSiL322iv+zYKhakv+hrunFKQMMbM0+k5msKcULhS4yqx2pDi4PWgHS24m8nbNutJVIKupHk8XhrhZI8k2ozHIhNaLoa0pWQsEB7sChKTin0wQiKmJK9keAqjuR9QaJBlgnwMGDOgRd0tcTnbTDM2O1tPVg4SJY2ZtSn6QAurq/FD6ajTOuNvmCGQ0HzKh9WIgH64ma6GrhaXairQXqWEDrph4GkFIahPVkjziaSS3EZrG8Z7IcrISqbwqqegOHDsX0bkhItnZrhIwCaPUDeC4EGVG8yETWi+F+I+2IwtM4L6roMsvwJ00+QXKuVLqqqrdzQTDdO2Xq6uHsdGwTRlWlmJXtcR8Tnxwiy22iFlZmnBdjffZluSEJn5WXk/IJWU0BpnQeik0b2vItli1/nQHXEsZS+SGrFS9EymsBxprCM0Cp1rbaCgh0SfancEmGst1ACirEDNrq32qPSgmNl2KNtodd9yRNc6aGJnQeikM7FCp3904E9eJC6neTHGoTGm9RnVgraQiXg+k0cjCVy4tchXT60yDeBlKPvbYY48YvOc2d6e0xLYcC2tUS1m9YcIZzYFMaL0QrDNZQISiALarQE6yfdwyi19GsTpmVgtKOhKhqeeqR2jcYq/51zG3lxF1PFqpdCSog+sKEJDsLAIydakrmd8EhKrzwnnqmuiuJZzR88iE1gshC8iK4RqqGesuttlmm7hoO9plQI3VWDxxLuUiYkoSFAgRwUoqqFcbNmxYDMgjTLMB1lhjjRjva0tySNZWAF+nQGeBzA455JB4Loiou9aU6yGjKfGSJzf1DmRC64W49dZbY4wJQbBquos0DLej8yv33nvvYquttooiiD632WabRZcVEXGBZV0NFjGghVvM+jOIxXu1Cyls/fDDDytbmwhFquJ5LKzOZiN1NyRXmHXXmQb9WvjFL37ROpXd5PiM3oFMaL0QqvpV0bMaukNoPuuhkNbCNeGpPajh4mayXpR2+JyHoSASBGJy4mAKdpECC1KRrpIJhEnyu54S7AMPPBCD+HfffXflmY6BhXjiiSdGN9M5dLd2TXJEltd5cTWzYGPvQSa0XgbFnWq0SAU1KqbDArF4O1L+Ia6k6FUiQWFtIjTZ0e5ALI/lpp1IvK2jUGdGJpxrKBHQ3ZF69i32phvC9CZ1dh2JK2Y0BzKh9TIY2sGKkXlrVHGnqnek1JFRcDoIvFf8jrSPBnLW4sknn9xla9Hnbrnllrh/VlxHtyPgnyZcIdTuDiaxXxakujzlMN3pKsj4cpAJrZeBogZCEXjvKoFUI42q0wLVlq4XNzLtX7xKnEpvpL+VR3QVzkMvqfhbW0OFy1BXZkAK4tlggw1i/K27lpSuCTMUuK6s1lpxvozmRia0XgSZP5LUtM9kFRuFNLZNHIwLVw/KLlKXQFLnSOob3SmwVawqocA66gjEuHQ0zDbbbNGa0vbVFeWMaqTrQCLJAOaM3odMaL0IBt5acEOGDOlSWUM9SC7YrmzkhAkTKs9OilRrZn6ninnlFYBYfJZ71hWIeSnrMDC4IzVjYnhao/SR9u/fv3juuecaUrnvvFl7WpsQbEbvRCa0XgKEksoSGj067qabborb9ajVm8kyU1/GzfNAJqmUQQYzVeR3FshJj6VSDaUo7UHA3gR3yQjusa6GrnYTlGEkH0tPSUlHx/9lNCcyofUSIDRZQO4myedGxc9AM7p6MbGjq6++uvJsC8SlZP1OOOGEmIlUkqE+a+TIkfF1bUWKbHUPdBbKLZZZZpkOyWw7DkqxMqwykIitEeUU5JFYm+r6xM8yejcyofUSqPtCZko2kiR2o4AoEBoLTUtVGYQR99lnn6hcK6uKSC183QLAYqOP1llCsy1ZUjVtHSmiffHFF+P705CWRijlukkQbBS/MzAl15v1fmRC6yUwmQjhcDsbVa6RkKaP2351ca3iWSPsymoVEgE6BZAbMmI5drb3UswMObM22wvoq72TXeXaGjfXiDkGLD7bVSri/BT7NtLqzfhykAmtF4A1ojQB4VS7hI2ALCG30fZZYwl6IUkUIZG02P2LjDbddNP4N5hrqR+0o2UTyi2QmXIRpRJtQWnIoYceGgnXMJhGlVKwzpCkRIAOhZT0yOjdyITWCyCjKQgudtXdtp5aMD08yWrvvvvurVlDZEL4sVrokfCiZvMECq4ItyOlE+J14mYKgzWTtwWuNSkjx6XpXL9mo0BzzcwCJKm+LqNvIBNaLwACsajVoPVEnEftmTiSfWg0T5aWroBaLU0ITmaSdcX93W677eKjvZYlWUnnIKPYnkoIUpV9lajYddddi9dff73ySvfx4IMPxsb5TTbZJE6Oz+g7yITWCyDDiGy4aj0B3QFKMexDUWkiNHE71lQ1iXJ7lU4kfTM9lNzOtkooxOm8hxIHBdj28NRTT8VEBfkhGmmNAqtQHZ8i4jy1qe8hE1qTQ5Zx6aWXjmRz2223VZ5tLATZWU72QcMs9S9qr6o12UnN2MILL9xKdPvtt18kRBX8taDBWzbTZ5Bke6DSQeSRu3v77bdXnu0+WJRUObia4nIZfQ+Z0Jocsm9afJBao8s1EtKgFITGekn9lDKcmtCrhR+VUNA/SxOfEJo+zFqlFG+88UYkRZaZuFV7U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Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:58:04] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:58:04.954321 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:58:05] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 09:59:40.796815 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 09:59:40.796815 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 09:59:40.796815 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 09:59:40.796815 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 09:59:40.796815 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 09:59:40.856117 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:59:40.858117 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:59:40.859626 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:59:40.860647 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:59:40.863649 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:59:40.866209 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:59:40.869208 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:59:40.872209 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:59:40.877195 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:59:40.881710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:59:40.881710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 09:59:40.882710 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:40] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:41] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:41] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 09:59:46.348656 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 09:59:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:00:26.056116 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:00:26.056116 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:00:26.056116 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:00:26.056116 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:00:26.056116 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:00:40.159260 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:00:40.159260 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:00:40.159260 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:00:40.159260 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:00:40.159260 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 10:00:43.953465 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:00:43.956466 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:00:43.960467 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:00:43.963468 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:00:43.966474 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:00:43.971474 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:00:43.978475 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:43] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:00:43.982985 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:00:43.986987 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:43] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:43] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:00:44.008987 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:00:44.029503 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:00:44.032504 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:44] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:00:45] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:01:10.518609 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:01:10] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:05:19.744427 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:05:19.744427 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:05:19.744427 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:05:19.744427 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:05:19.744427 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:06:04.253573 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:06:04.253573 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:06:04.254573 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:06:04.254573 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:06:04.254573 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:06:23.734681 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:06:23.734681 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:06:23.734681 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:06:23.735681 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:06:23.735681 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:06:54.351575 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:06:54.352893 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:06:54.352893 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:06:54.352893 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:06:54.352893 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:07:10.641593 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:07:10.641593 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:07:10.641593 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:07:10.641593 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:07:10.641593 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:07:24.597334 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:07:24.597334 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:07:24.597334 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:07:24.597334 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:07:24.597334 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:07:50.717262 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:07:50.717262 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:07:50.717262 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:07:50.717262 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:07:50.717262 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:08:09.234291 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:08:09.235291 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:08:09.235291 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:08:09.235291 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:08:09.235291 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 10:09:16.024888 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:16] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:09:36.164183 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:09:36.167210 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:09:36.169184 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:09:36.172183 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:09:36.175190 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:09:36.183190 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:09:36.187190 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:09:36.194730 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:09:36.201254 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:09:36.208769 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:09:36.219281 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:09:36.224286 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:36] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:09:38.643109 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:09:38] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:10:43.198123 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:10:43.199122 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:10:43.202123 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:10:43.206123 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:10:43.211124 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:10:43.218130 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:10:43.236642 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:10:43.230641 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:10:43.244642 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:10:43.252761 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:10:43.264647 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:10:43.272647 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:43] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:44] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:10:51.004067 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:10:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:12:10.685151 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:12:10] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:12:57.593336 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:12:57.597343 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:12:57.600336 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:12:57.605334 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:12:57.611372 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:12:57] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - 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Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:12:59] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:13:00] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:13:14.682277 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:13:14.690277 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:13:14] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:13:14] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:13:22.604841 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  neutre   part 3 part nom 3  

Situé :adresse03    code_postal03   ville03    pays03

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    03/12/2025 10:00  au 03/12/2025 12:30
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Du    05/12/2025 09:00  au 05/12/2025 17:30
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Du    10/12/2025 09:00  au 10/12/2025 17:30
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Du    15/12/2025 09:00  au 15/12/2025 17:30
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Du    16/12/2025 09:00  au 16/12/2025 17:30
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Au plaisir de vous retrouver prochainement,
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11/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:13:23] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:13:23.486505 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:13:23] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:13:55.990154 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:13:55.990154 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:13:55.990154 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:13:55.990154 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:13:55.990154 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 10:16:24.893050 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:24.898015 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:24.903014 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:24] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:24.912014 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:24] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:24] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:24.933014 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:24] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:24.950528 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:25] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:25.320791 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:25] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:25.660454 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:25] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:30.963863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:30.967373 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:30.971394 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:30.975373 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:30] "POST /myclass/api/Get_Competence_Domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:30] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:30.984374 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:30.996405 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:30] "POST /myclass/api/Get_List_Partner_Basic_Setup/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:30.992374 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:31.005376 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:31.009375 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:16:31.014375 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:31.017376 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_Competence_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_List_Partner_Basic_Setup/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_CRM_List_Opportunite_Etape/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_List_base_document_automatic_setup/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:31] "POST /myclass/api/Get_List_Partner_Basic_Setup/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:16:32.825622 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:16:32] "POST /myclass/api/Get_List_Message_To_Mail_Queue/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:22:35.418529 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:22:35.418529 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:22:35.418529 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:22:35.418529 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:22:35.418529 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:22:48.707335 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:22:48.707335 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:22:48.708334 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:22:48.708334 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:22:48.708334 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 10:22:48.895212 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.900358 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.905362 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.910363 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:48.918378 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.922902 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.935303 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.941298 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:48.952886 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.956903 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:48.971160 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:48.980150 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.982147 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.984161 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:48.995150 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:48] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:49] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:49] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:49.008167 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:49.009167 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:49] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:49] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:49] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:49] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:50] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:57.546514 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:57.551523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:57.554523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:57.560525 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:22:57.563525 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:57] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:57.571524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:57] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:22:57.580524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:57] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:57] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:57] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:57] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:22:57] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:00.039543 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:23:00.043574 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:00] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:00] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:05.594422 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:23:05.597327 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:05] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:05] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:09.360426 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  neutre   part 3 part nom 3  

Situé :adresse03    code_postal03   ville03    pays03

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    03/12/2025 10:00  au 03/12/2025 12:30
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Du    05/12/2025 09:00  au 05/12/2025 17:30
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Du    10/12/2025 09:00  au 10/12/2025 17:30
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Du    15/12/2025 09:00  au 15/12/2025 17:30
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Du    16/12/2025 09:00  au 16/12/2025 17:30
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Au plaisir de vous retrouver prochainement,
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11/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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' + dest = <_io.BufferedRandom name='./temp_direct/Convocation_43598_37732.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject 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0RhuKMU/Zqs5woAbCtKhprveBAHIQQQGjEdhNo44S15MLyMfCwfVuRhT0EydN0YcEVHPLYVJKLESJ5v9wzEYLueXZKvhVCEXveRMAeA/Px8bN68qU1BVgDgt99O4bffTjcKI9we9Ho9fvzxx1Z5tIvFYjz99LN47733MHLkyGaF+Z1apkwmw7Jly7Fly1b07t2n4TeJxAzLlz+NTz/9PwwdOqxTNd/W1gnRvR3ISSAQYOLESQgPH2ky7ZUrl3DixIk29aOioiJ8++23JpdGxGIxFi5cBDc39/taPjGB3laTBsehl42hx7yCCIVqZbufq+J12F6cgoomBu/nrJ0RZPNfr1pbkRmed/ZtZFrhAeytK8dNRXmXdpRJPTzxumsgHJvMxOtBWFt0E6cr8rrNSe5mXSUO1hSj6RRmtJkVJrn4QMgO2+g0wbNnzx5kZma0fXIoFGLjxg0oLi7uUBkKCgpw8OCPrcrv6aefxcqVK9u8vUwkEmHkyJF4//0P4OPjCx8fH3z++edYvXp1qxy/7mfs7e2xbNkyk+vDHCfA9u2RyM3NbXXf++mnn5CUlGgy7ahRYzB27Nj7vi2YQG8HjhJzND2NRglCja793q+xNSU4r6oxuD7LxbeRQxcHYJyzF3ybrJcrQDhQnNqlWrKQ4/CYey8ssHOHWWMFHtm8DmtzopFW1/UBOAjAn5X5KDTyrk+5+MNFYsE6aSeRkpKCPXu+b7emePNmEg4fPtyhEKDR0dFITU0xmW7WrNl49tlnTWrlzQscDqGhofjiiw2IjPwOERFTWhURjQEMGTIU06fPMNlPUlKSceTIEeh0OpPPzMrKwu7du0xq9NbWNli0aCHs7Ozu+3ZgAr0daHjeqJBpr26qIx67i1INDkSZa2GHUCOmY0exBZ519DTIf0d1IdK7OHqZrVCM1Z4DMNnC1qDzXNCq8K+s6yju4m10PBHO1hSj6fTJSyjBKAcpBGDaeWeg1WoRGbkNJSUd07A3bfoKOTk57fs2dDqcP3/epLm7Rw8nLF68uMN7jzmOQ79+/eDl5cWOVG0DVlZWmDdvvkmnL4FAgG3bvjVp8eF5Hvv27WuVZSgiIgJDhgxljcAEevuo1KjQ1JvVHByshe3bKpGsqMBxheG+2kecvI2e7iXkODzo4gP7JuvZubweJ0symvFT7zxczSzxludABIvMDETnobpybM6L7ZT1/ObIV9chpd7wCMiJFrZwkJizDtpJXL58Gfv37+vwc8rLy7B3795WaWVNKSsra5Uz3oIFCxEQEMga7S4SHByMJ56Yb1KjLikpxt69P7QYEjYxMQH79v1gMs8ePZywcOGidltlWp7cARUV5Q2n8rX3Lz8/v83+J+2Febm3VTsnHtdrDDUWO04At3Zs3eJB+LEkDalNBOAEiSVG9fBo9j5vSzu8aNsTa+/w8tYD2FKehWluAW0Kj9vmjg4g1NYZa2XBWJ59HcX035VzFYDPy7PhZW6LJ9x6dcladrlGiXwjE4Yhtq7d7mnf9rr7e2h9tbW1iIzc1qqDSYjIpDa7Y8d2TJ48GSEhIW0uhylzOxFhxIgRXb7Hl9EyYrEYjzzyCH7++RiysjJbtILs3r0LERERGDBggMHvarUae/bsQVFRocl+9cQTT6BPnz5d861yAqxY8Qr0el2HnuPr64fffjvTJZOObhPoZdp6FKg7LwCDABxczCzuujk1X1WLPYoSg+v9Le1bfVb2nWQpa7C/qgAcGpvspzvIWlwLFnMCTHf1x9rqgkbRJG7yOpwty8Z8Wd8uNu1wmOTkhdWqGrxSnNKo9BVE+KgwCd4Wdhjp0PlepyX1ChQZrJ8T3Mys7+0Rjwjf5NyAo7DzYuALOQGe9Q2DuJPPqb969QqOHv3J4Azxpnh5eWPgwIE4cGAfWtqDXVtbi507d6J3795tOme8oCAfdXUKWFg0P1kOCuqNgIAAJlHvAXx9fTFv3jy8++6/W0ynUNRix47vEBQUBAuLxuNcVFQUDh48aFKYe3v7YPbsR7t0371QKOzwRFEg6L6JZhcJdA4v5dyAGdd5Fd1LZIadfSbAWnj3NLA6vQ4bc2OR3WTGZgbgIXt3CNvxvqfLshHbZLvbEJEEU1x8TdeJTQ88Y9UDXynKGq5pAewsy0SEqx96iLt2RigRCLBQGoQMVQ2+qCls9FuiXot3c6KwwcwS/padG0zB6Bo9ocsOPelEiY73aks69Ym9OQGepsGdOxkvK8WGDRtMCnOe57F8+XIMGzYcly5dQn5+y+cPHD16BFOnTsXo0aNbXZbS0lKIRC1/84GBgd2i/TBaI7wEeOihh/Dzzz8jKup6i2mPHTuGGTNmYNSo//aHuro67N69GzU11Sb3tS9duhRyuZxVeiNFq4vI0muRrFN32l+9TtPla8MtoeJ12J2fgA3VBYZailCM0T082mw7KFTXYUd5lsF9D9r2hIeRuO1NsRCIMMvFz3CSoFHiXHlOt9SLg8gMKzxDEWFuWN5f1XX4JCcaFdrOjX1dayTMKzgOTmLmkdxReJ7HkSNHceWK6UAeffr0xcSJk+Dj49OqEKB1dQps2vQVampa77hZV6cEZ2Ki7OHh2Satn9G1uLm5Y9GiRRCLW7ZE1dersG3bNigU/z2O+dKlizh27IjJvhQWNgSTJ0d0W1S8+16g/69AADJU1ViXcRUri5JhTDStdPGDczuOiv29PBfntapG05QAgRCzXP1bPTkYaN8Ts80ar5frAPxYkoG6Dq79tBZPCxu86dEffY2Ent1eU4xv8+I71UnO+EE4BP09HoTj70BOTg42bfrKpJlQr9fjqaeegouLMziOw4wZM+DhYTqi1p9/XsCxY8da//21ok27y+GI0XrGjh2HkSNNB5v5/fffce7cWQBAVdWtMwBMOU9yHLB8+VPsKNv7UaDzAIo0KmTXK1r9l1VfizhFOc5X5OHTzGuYm3QGaytyUGvEQjDD3AaP9AyAoI3OX1VaNXaUZRg0xmRrZwRZt/54RjuRGR4zYp7fVV+Nq910aAsHYJi9G/4h7Qf3JtqUGsDHZRk4UprZaSfS2TSz7FKkVbEvugPodDrs378fhYUFJtOOGzce48aNx+11czc3NyxfvtykZkVE+Pbbb02a529jbW1lMkpYfn4etFota8B7CDs7Oyxa9KTJbYQajRqRkZEoLS3F6dOncfbsGZP9Z8qUhzBixAhWyUbosgXpXgIRLDrRw9lGKGqXh3AdgBezrqKtxth6AHVEBpHbGmnHIjO84z0Yju1Yu71YVYCjTbZeuXIcHnX1b7Nn+IgeHphQlIyTTQTajyXpGNFDDjHX9fM2DsBUFx8kq6rwUWkmFHfUWwnxeCcvDr4Wtgi1delwXs05lZVq6u/tr43jsKdnENwknXeQjYDjIOoks2NycjK2bv26VWkXL17SaM8xx3GYPDkC33+/2+TRqTdvJuHAgR/xwgsvmJwAODk5Q6fTtWi+TU6+CY1Gw9bR7zHCw8MxderD2Lv3+xbTXblyGXv2fI9ffvnFZH+QSCRYsmQpbGxsWAV3hUAnMrayTXjPMxQDjIRIbb8pgYNlO7wFedw66rOzCROZ4VOvQejbjndU6nU4VGoYMGGUhR0G2bm2+XkuEgtMdZDiZElaYy29rhxP1pQitB3PbA8WAiGelwcjW1WL7YpS3Kkzxes1eCv7Or70D4dnB7fUuZlbw47jUN1I4+eQV19zj39uHAY7yuBzDx65Wl9fj61bv4ZSaXpnyvTpMzB0qGEgjx49euDZZ5/Ds88+Y2Jew+Hbb7di8uTJ8Pf3bzGtVCqFlZUVeL75iXViYgJSUlIwaNAgNqLfS8JFJMKCBQtw8uSvqKgob1GGfPLJxyaXV4h4LFiwEH379u22dxCLxR32cpdIJN0WpKjDAp3jjOvNPcUW8DL/35xFPW5hj1Weoehv69KuTXQxNSXYcodneoNA5ATYXZDUrmdW67V/6cl3bh/j8WNJGvrZukDUTR3KXmSGVV4DkJb6B8422bb4s6oGn+VE49++Q2HdgaNebSSWcOMEqCZ9IwvB77UlWKjXwkbIHKTayqVLl3DkyE8m092KCDbPYKvR7bFg7NhxGDduPE6f/q3F55SXl+O777bj7bf/0eLZ1dbW1vD19W9xLzrHCXDu3DmEhoayvej3GL1798YTTzyBL75Yb1IxNIVM5oE5c+Z0WzheIsLbb/8Dw4cP75gyKhB2m9MmCyzTBgaIzPCUkzcecQtAD3H74oVriceh0nSjv0XWVSCyrqJTy7y9uhCLlFXw7UatMNDSHv/2GIDF6ReR2sQj/bOqAnjlJ+IZWT9I2mkqlptbw0tsgZtqxR02IeB4fS1K1UrYWLKYzm1BoVDgq6++bDFy153aef/+oS0K/KVLl+G33061qJVwHIcdO77DlClTjWr7t3F2dkb//v1NBpfZtWsnHnroIbYf/R5DKBRi9uxHceTIT8jKyurQs5544gn4+3df+xIRpFLZ3yoCIfNybyUPmtvgcNB4LPUIbrcwB26Fed1eXdRt5c7l9ThSkt5pDmmtZZi9G95072PUj2JdSSpOdWBbnaVQhCFGHAdreT1Ol2d3+7v+3fn1119x5cplk+lcXFzxxBPzWtSoAWDgwIGYOXOWyefxPI9vv/3G4AzyRhqHSISRI0eZPNylrKwU33yzFXV1HQ9mFR8fh+zsbNYxOgkPDw8sWbKsQ7sR+vULxrRp05kF5n7X0C0BvO3iB3+L1mlt5eo6PFV00+B6oroOefW1kFm0fxlBT4QjJekope7dZrOlIhdz3YPQ08yq2/IUchxmu/ohS1WNf5VnGUwy3smNgZu5Nbza4SDGAZjg6IGvKnJQcofw5gB8VZqBSc7eXRr69n+JwsJCbN68uRWnoXGYO/cxBAUFmXymhYUF5s+fj6NHfzLpfX78+M945JFZmDRpUosTBF9fvxbDiQLA3r170LNnTzz33PMmJx3NER0djVdfXQWxWIznn38BEydONBnYhmFCaxQIEBERgUOHDuL69WttF1KiW2edy2QyVpn3u4YuBjDWQYZHXP1a9bdI3g9rHQ1jqOcQj49ybqCyA0FS8uoV2FmVj+7eNZuk1+BUaVarwvLwnRi+x1IownMewVhiZahNX9fV44PsKOS3MzxwiK0zhjbZf08AonRqHCpOY3vSW8mBAweQlJTQKi1rzpw5rdaQgoODMW/eApNroxzHYePGDSgvb95pSiaT4eGHp5l0LOJ5Hhs3bsTGjRtRU9M2B0mdToerV6/i7bffQnLyTcTHx2HlyhVYv/5zlJSUsI7SQZydnbFs2fJ23Tt06FBMmDCBnX7HNPS2I+EEWCbrhzO1pTjTZBvYr2oFduTH4wWvgW12XCMQfi5JQ3qTMK/2nADP2Uth2UkhbXkiHKkpwhVt4y1cm8rSMa2nH2xELTuUEBE685w0J7EFVnsNRGrKeZy/o0x6AD8qKyHKiQLa4QZoLRTjmZ6BOJd1DdVNpiAflaShv7UTwnvIOz3yv5Z4XKjIx0A7V9iIJH/rvp6eno6dO78zbRHhOCxevKRNGpJEIsHjjz+OI0d+QllZaYtpY2KicfToUcyfP99o5C+O4/DYY3Px88/HkJaW2uKzNBo11q//DElJiVi+/CmEhIS06JDE8zyqqqqwb98+fPnlRlRW/teHpa5OgfXrP8fVq1fx+utr0K9fPxaZrAOEh4cjImJqqyLB/dfaY4nFixfDwcGBVSAT6O2jp7k1Vkv74M+sa40iwykBbCjLxHB7KQbZ92zTM0s19dhZnm0QaW6JjQve9A2DWScF8CcCfPMTsbAgvtG2sQsaFc6X52KKq1+L9ws5rtM7hb+VA972CMXTmVeRfoeTnB7AHmVVu587zFGGCSVp2K+sbHQ9n3isybmBrebWCLRy6DShXqfXYnNuHD4uTcc8O3e87TMYtn9Toa7T6bBz5w7k5+ebHFz9/PwxderUNmtIgYGBWLhwIT755OMW7yUibNr0FcaNG9dsbG53dymWLFmKN99cY3ItVq/X45dfjuPcuXOYOHEiJk16EL17B8HVtScEAgGICDU1NcjNzcWff17A/v37kZubY/S5PM/jwoU/MG/eE1iz5g1Mnz4dlpaWbJBsB7a2tliwYAHOnTuLujpFq+6ZNGkShg+/O0FkOI5DcXERQsOCJAAAIABJREFU0tPTO+2Zjo6OXTo5YQK9GcY4eeHVqkK8W9U42loqr8enuTHYaOUAhzbEDj9dloUYXVMvYg6PuPrDojOP/OSAsc5e8ClORnITa8Dm4hSMdfKEZYvburrGrDXaUYZVymq8XpSEmjtiF3TEMG4rkuBptyCcybiIiibxEC5qVXg+9QI+8QlDSDu3F95JmUaFT7Ki8FFVPgDCF1V50GcQ3vEJ+1tq6lFRUdi1a6dJIc1xHJ555lk4O7cvpsTMmY/g4MGDyMhoeVDMz8/DgQP78eKLLxoNO8txHKZMmYITJ34xGU3sNiqVEocPH8JPPx2GSCSCubk5HB0doVSqUF1dDb1e1wrfgVtUV1dhzZrVuHEjCq+/vgY9evRgg2Q7GDhwIB599FF8++03Jvuera0dnnxy8V2bQHEch7fffqvTrDJEwLp1n2LGjBldVmZmP2oGM4EQS2T9MExkZiAMvldVYV9BEvhWiqNqnQbfl2agrkn6+Zb27QpMYwpniSWecjDUdH6vr8W1qqK7Up9iToD57kF42l6KztqRyQEY7SjFuy4BBi3BA/hNU4elaX/idFk26tsZS17D3zKxP3vzLD6qymuYgqgBbKjKx/sZV6DQ/73CjtbV1WH79kjU15uOrDd06HA88MAD7V6/lMvlmD9/fqvu3759O5KSkpr93d7eHmvWvIGgoN5tHEgJWq0WtbW1yM7ORmlpCTQadauF+Z3PsbOzYxHpOjKumplhzpy5kEpNL988/vjj6Nev310tr16vh1ar7aQ/TZeXlwn0FvCytMNb0r6wbCLSOQCfl6Yjprp1zjIXK/NxSmPo/DXXxQ82os4POCDkOEzr6Q+XJjPLKgB7SlKh4fV3pT6thCI85xGCKZ14nKqIE2CerA9W2bkZ/f26To0HMi7jzZQ/EFdT2upDYlS8HimKCnyYcRnh6Rew30gUOi2AWr0WujbsWrgX3HouXryIQ4cOtkKA8XjmmWcahXhtDw899DD69DEd3au8vAzffvst1OrmHU979eqFd95ZC0fH7tWQiQhTpz6E55573mR8ckbLBAYG4rHHHmsxjUwmw5w5c9gOg7aOh6wKWma8szeWV+bh/2qK//txA0jkdfg8NxbrrUa3uI5ap9dhb3EalE22V0VIrDDEwb3Lyi23sMXTtm5Y22TJ4KiiDE8ryhHcCTHV21UuM2v8y3MgclP/wDVd5xyrai0UY4XXQBSmXsCuJuvpt1vs05oi7FKUYpalA8LtpRhg6wJzkQSWQjEshUKoeR4qvQ4KrQpRNaU4W5mHSGUl1H8Ja2O2mNfspVjjPRj2RhwNtc0I+cNlWXCuLu6SunU2s8TEHh4tpqmsrMTWrVtb5a0+bdoMDBkypMPlcnFxwZIlS7Fq1QqTWvGxY0cxffqMZk/q4jgOYWFh+PjjT/DWW2+26iCZjsLzPGbOfARvv/02c87qDIVDKMSMGTNx/PhxJCYmGKlvPZYsWQovL29WWUygd7KJSCDEsx79cT7pDK7rG5tMtisrMKrwJhbK+jV7oEpibSl+UFU1ES/AbCdv9BB3nelOzAkw1cXXQKDnEuHHolT064R15fbS16YH3pKH4Jns6yjsJGuBm5kV1vmHQ559Ax9WGT/Jq5jXY6OiDBsVZbAVCOEjEMFdIIQ9J0Qd8SgjPa7rNKhvhcb9vpMPnvfo36yFxeiBOMTjleKULqvX52x7tijQeZ7H8ePH8ccf502uCwoEHBYsWGg0xGt7mDRpEvbsGYzLl1s+Z12pVCIychsGDBjQrCYsEAgwfvx4ODk54R//eBsxMdFd9x2JxViwYCFeeOFFODo6sgGxsyb2cjkWLVqEN95YY3BcamjoQEyd+hALItMOmMm9Ffha2uNVtyDYGjG9v1ucglSF8T20WuKxvzgNyiYCYoTIDOOcPLq83H1snLHU0nAQ+qGmECmKirvY6ThEOHniTRd/dKa7i6uZJV73GYwNroFw4wQtTlhqeD2idWr8rFFit7oWhzV1uKCtNynMewnF2O8xAC97hnbJcklHMDVBKygowMaNG0wKcyLC44/PR0hISKeVzdraGs8993yrYlqfOnUSp06dNDHhEKB///744osvMGPGzC4xzbq5ueOTTz7FqlWvMmHe2X2V4zBx4iQMHhxm0PeWLVsGV1dXVklMoHfdQPlwTz8ssnGBsImmncnr8Un2Daj0OoP7UhQV2FFraF59xEHeLZHMLIUizHU1PM0qidfjRFnmXa1TMSfAPPcgLLbr3GUHO5EET3uEYL/fCCy0doJrJwWjkHECvGjnhoO9xmBmT39YCP9exi29Xo+DB39Ebq7pkLv29g54/PHHOv0QjGHDhv11hjpMTii2bt2K4uJik0LBy8sb7733PjZt2oIRI8I75RAMe3sHLFiwELt27cb06dPZmnkX4ejoiMWLl9zhZEiYNOlBjB49hlUOE+jNDA6d9BwLgQjPe4Sgt5EtX7uUFThUlNIoxhoPwvHSTAOTcm+BCBEu3bc2NNDBDbPMbQ2u76/IRV694q62jZ1IglWe/THF3KZT20zIcRju4I5NvcZgl/cQPGZhD6927vPvLRDhFTs3HPAPx8cB4ehl5Qjub9jX09LSsGXLllvHHbfwx/N6LFiwsM2e5K3BzMwMy5cvh0QiMVmOqKhrOHLkp1adwmVtbY0JEyZg06bN+Oyz9Rg9egxsbe1aHTuciCAUChEY2AvPP/8Cdu/ejbff/gf8/Py6NDrZrfrmm/2jLoh2SIQW8+xIvPX2EB4ejgkTJt5SQCytsGDBQtjZdd/hSqbqorP/upoOqxm2IjMscZA3GkwIBEdx92/tcBSbY4W91EgZO2efsK+VPd6Th+BsVaHBbzGqakzUqhvWxau1GlQQb1AeuZk1/Cy7z7HGXmSGBa4BkFcXNhJEBCBNWQWZuXXjwVEkwQJHeaMDTngQLLtor7WnuQ0+8h6CvnesLXMAHDqh/5gJhBjv5IlwRxmSFRW4VF2IazUlSNHUIUWvRSHPAw2BeDmAE6CPQIheQglk5jYYZ++OXjbO8LO0g6CNA7uVxByrHeXoTr92XwvbZgVHcXExli9/yrTlRCzCjBkzu2z9sn//UHzwwUcoKjK9fVIgEKKurg7W1tamrWgcBzs7Ozz00EOYOHEi0tLSEBcXhytXrqCgIB95eXmoqalGfX09hEIhrKys4eTkDC8vT3h7e2PkyFHw8/ODs7Nzt4QYFYlEeOONNw3Wjxu/vwBOTk6dluft6H3Tpk1r2Rolk3VbRDwrKyssXrwEp0//hhkzZiIsLKzbvpeIiAgMGzasW2VUr169uvT5HBELes24f9AToUSrQq1WDZ1OC9xeM+cE4AQCmIskcJJYsDPV/4dQKBSorKyERqOBXq8Hx3EQiUSwtLSEk5MTc766y+h0Oqxfvx4TJ05A3779WIUwgc5gMBiMvyu1tbWwsrJisfKZQGcwGAwGg8GmQwwGg8FgMIHOYDAYDAaDCXQGg8FgMBhMoDMYDAaDwWACncFgMBgMJtAZDAaDwWAwgc5gMBgMBoMJdAaDwWAwGEygMxgMBoPBBDqDwWAwGAwm0BkMBoPBYDCBzmAwGAwGwxARqwLG/QARQaVSged5mJmZQSxmx6MyGIz2odfrUV9fDwAwNze/Z47gZRo6475AoVDgrbfewpNPLsKNGzdYhTAYjHbB8zyOH/8ZTz/9FNat+6RBsDOBzmB0EzU1Nfj552O4cSMK7u5urELu0DTy8/PATlFmMFpHQkIC/vnPf0Kr1WHRoidhZWXFBDqD0Z2kp6ehvLwUwcEhsLOzZxUCIDn5Jj788ANs3rwZPM+zCmEwTFBYWIj3338PcrkcH3zwATw8PO6p8jGBzrgvyM7OgZmZOQYOHAQLCwtWIQAOHTqEr776EsHBwRAI2FDAYLREfX09Nm3ahIqKCnz00Ufw9va+58rInOIY//Oo1WrEx8eBiODv7w+RqPXdnogamaNNCb4707dXSLYlzzvTcRzX6F6O48BxnNH0CoUCN2/ehFgshlQqa/Tb7XuM/Z+IjD73Tg3f2O/tLa+xe1tTnq56bnO09f1bWz9tKWNb3rm179KZfa8tfd1UPbVU562pY2PlNHWfXq/HrFmzsHjxYsjl8ja9W3dNmJlAZ9wHAr0eUVFRUKvr4ePj0+pBLTs7G9euXcOVK5dRUVEBBwdHjB49GsOGDYOTk5NB+sTEBJw+fQapqSkQiyUYP34cRo8eA2tr61blqdfrkZ6ejtjY2L/yrISjowPGjBmLsLAwgzwBYNu2bSgpKcaMGTNRX3/rPePj4/6yRgzE2LFj4ejo2JD+woULOH/+HOrqlLh27Rp4nsePPx7AmTOnAQDTpk1Dnz59UVZWhm+//QZCoRDLly9HYmISzpw5jczMTDz77HMICQkBEaGkpARxcXE4f/48iouLYW5uhpCQEISHj4S/v7/B4BgVdR3nzp3HgAGh8PHxxcmTJxEdHQ2VSgl/f3+MHj0GgwcPNvAa1ul02LRpE+rqFJg9+1FoNBqcPXsGsbGxePDBB/Hww9MAAEqlEjdu3MCFCxeQnp4OgYBD7959MGrUKPTp08dgMpebm4vvvtsOHx9fPPDAA7h27RpiYmKQn58HPz8/hIeHIySkv9FJIM/zKCwsxLVr1xAVdR25ubmwsrLGyJEjER4eDjc3t0bvX1paiu+++w48r8eyZcthb2+49BMfH4ejR4/C3d0dCxYsBMdxqK6uxtdfbwERYdmyZUhPT8eZM2eQlpaGxYsXY/DgMOTkZOP48V8QHx8HgEN4eDjGjx8PZ2fnVk8i8/Pzcf36NVy9eg1FRUWwtrbCyJGjEBYWBplMZjDBOH78Z0RHR2PKlCmwsbHFpUuXEB8fB41Gg5CQ/hgzZozBfXdOsuPi4nD16lUkJyejqqoK7u5ueOCBCRg8eDB++ukwSkpKMXXqVPj7+zfKNy8vr6GcxcVFsLa2xogR4Rg9ejREIhG+++47mJubY8GCBbC0tGy4T6FQIDo6GteuXUVmZiYUCgV8fHwxadIk9OnTG9u2RYKIx9y5jzX61nQ6HZKTkxEVFYUbN26gsrIC7u5SjB49GuHh4Q153Eaj0SAq6jr++OMPJCenQCp1x/jxD2DYsGFtUibaqw0wGP/TpKSkkFTqRoMHD6KSkhKT6Wtra2nz5s00YEAoeXjIKCDAn0JDQ8jDQ0YeHjKaNGkixcREN6TneZ6OHz9OgYEB5OPjTWFhgykgwI+8vDzotddeo6qqKpN5VldX0+bNm6hfv74kk7lTYGAAhYQEk6ennDw95TR16lSKj49vdE9lZSVNnTqFAgL86MknF1FAgD/5+nqTn58vSaVu5OEho2nTHqasrKyGe/bu3Uu+vt7k5eVJcrmUPD3l5OfnQ35+PhQWNohSUlKIiOj69etkZ2dBU6dG0CuvvEy+vt7k5uZKvXsHUWpqCmm1Wjp16hRNmjSRPDxk5O3tSaGh/cnHx5tkMnfq3TuIjhz5ifR6fUPeOp2O1q1bRzKZO82YMZ3CwgaRXC6lwMAAksulJJO5k5+fL3300UekUCgavWtWVhYNHTqEQkP707/+9U8KCupF7u6u5OhoS6dOnSSe5ykhIYFmz55F3t5e5OXlQSEhwdSrVwDJZO4UEOBPn376KdXX1zd67qFDh8jV1Ynmzp1LU6ZEkIeHjAID/cnDQ0YymTv5+/vS5s2bSaPRNLpPpVLRd99tp8GDB5JcLiUfHy8KDu5L3t636nX06FF06dIl4nm+4Z7Y2Fjy9/elmTNnGDzvNl999SXJZO60cePGhnsTExPJxkZCEydOoFWrVpKfnw+5ublSYKA/xcXF0qVLl2jQoIHk6Smn/v1DqG/fPuThIaO5c+dQbm6uyb6nUqlo//79NHJkOMnlUvL19aaQkGDy8vIguVxKI0YMp7Nnz9Adr0I8z9Py5cvI01NOS5YspuDgfuTl5UEBAX4kk7mTXC6l4cOH0dWrVxvlxfM8ZWdn0TPPPEN+fj4klbqRp6ec/P1v9VkvLw+aO3cOjRgxnAIDAyg7O7tROX/4YS+Fh48guVxKHh5SCgrqRV5eHiSTudPYsWNo7dq15OrqTMuXL6O6ujoiItLr9XT9+jWaNu1h8vLyJKnUjXx8vBry9/f3pWXLlpK3txfNmDGdysvLG/IsLS2ld9/9N/Xu3euv79KfgoP7NXw7Tz75ZKPvS6vV0ubNm8nPz4f8/f0oLGwweXl5kI+PF61bt460Wm2XjnVMoDP+5zlx4gS5u/ekpUuXGAiKptTV1dHatWtJLpdSRMRk+u677yguLo6Sk5PpwoULtHz5cpJK3WjatGlUXV1NREQVFRU0YEAo9evXh44fP07p6el05cqVv4TWYDp79qxJYf7GG2+QTOZO06Y9TPv376f4+Hi6efMm/f777zR//nySy6U0f/78hjyJiJKSkqhv3z4kl0tp/PhxFBkZSbGxMRQbG0s//LCXhg8fTnK5lNaseZ10Oh0RERUUFFBcXBz961//JKnUjd566y2Kjo6m2NhYSkhIaBB427dHkru7K8lk7jRp0gT6+ustdOnSJfr999+pqqqKDh48SAEB/jRo0EBat24d3bgRRSkpKXTjxg368MMPycvLgwIDAygmJqahvBqNhubMeZTkcin5+/vRq6+uovPnz1N8fBxFRUXRhx9+QIGBAeTu3pP27t3bqI4uX75M3t5eJJdLaejQIfTRRx/RH3/8QefPn6eysjKKioqioUOHkJ+fD61cuZIuXvyTbt68SfHx8bR161YaNGggeXl50KFDBxsJ2c8//4xkMnfy8JDRiy++QOfOnaP4+Di6evUqrVmzhmQyd/L0lNOVK5cb7qmvr6fPP/+M5HIpjRo1krZs2ULR0dGUlJRE165doxUrVpCnpwc98MD4RgJ1z5495O7ek955551GE507hd0rr7xM3t6edP78uYbr+/fvJze3W20xbtxY+vLLL+nixYv0+++/U35+Ps2dO4fkcint2rWTkpOTKTExkZYvX0aBgf4UGRnZYt+rr6+nDRs2kIeHjEaODKetW7dSTEw03bx5k6KiomjNmtcb8s3JyWm4r6qqiiZOnEByuZQGDhxAX3zxBV2/fp3i4uLoxIkTNHPmDJLLpTRz5kyqrKxsuC8jI4MiIiaTVOpGDz44iXbu3EFXr16luLhYOnfuHL344ovk4SEjuVxKY8eOaeiPKpWKPv10HXl4yCgoKJA++OB9unTpEiUkJFBUVBT93/99SgMG9G+YGH711ZcN7Xzp0kUKDu5HMpk7zZ8/nw4ePEg3btyg2NhYOnr0KD3++OMkl0tJLpfS6tWvNdxXUlJCS5YsJrlcSnPmPEpHjhyhuLg4unnzJp09e5Zmz55FMpk7rVy5oqGcSUlJJJO508SJE+j8+XOUnp5OJ0/+SoMHD6LRo0dRXFwcE+gMRnvR6/W0adMmkkrd6LPPPjOZft++fSSVutHcuXMazbxvU15eTk888QTJ5TLat+8H4nmeoqOjycNDRkuWLG40YUhMTKSUlBSjg/edg/jWrV+TXC6lBQsWNNJI7tQSpk6dQq6uznT48OGG67/+emuiMnPmDKMDxZEjP5G/vy8NGjSQioqK7tCUtfTPf/6DpFI3OnbsmMF9Op2O1q5dSzKZOz399NONBvJbmmYM9enTm8LCBtOZM6cbCcjbgvv9998jqdSNVq9e3TDYFRcXN2iQBw4cIJVKZZDv999/Tx4eMho/fhwVFBQ0/BYZuY1kMnd68MFJFB0d3ahOi4qKaPr0aeTj4027d+8itVpt8E6HDx8iLy8PmjDhgQaLiUKhoMWLnyR3d1fauHGjwWSvtraWli9fRjKZO23Zspl4niee5+nEiRPk4+NNERGTKS4u1iAvhUJBS5cuJXf3nrR58+aG6++88w7J5VI6evSo0b5QUlJCERGTqU+foAZLiV6vp//7v09JJnOnJUsWU0ZGRqP6rq6uosBAf+rXr2+jNs7JyaHo6OhmLQG3+95vv51qsDrduHHD6Lu89tqrJJW60fr16xuux8fHU9++fWjo0CF04cIFgz4QFxdHAwcOoMBAf4qKiiIiIqVSSS+//BLJZO60evVrlJeXZ5CfWq2mf/97LUmlbvTmm2+QVqslnufp119/JblcSmFhg+nkyZMGbazX6+nChQvUr18fcnbuQadOnSIiosLCwgYr0rp164xayyoqKmju3Lnk7t6Tdu3a1fC8zz//jKRSN3r55ZeorKzM4L60tDQaM2Y0+fh40aVLF4mI6JdffiGp1I0++OD9RmmjoqIoOzu7xbGgM2CurYz/aTQaDa5duwatVgMfn5a9UsvLyxEZuQ1isRivvLICnp6eBmkcHR0xZsxo6PU6XL58BTzPw83NDebm5rh+/ToSExMbnHWCgoLg7+/fokNMSUkJvvnmGzg5OWPVqlVGt8E4OTnh0UfnQCKRICYmuuF6TEwMBAIBHn/8CfTt29fgvgEDBkIu94BSqURZWWnD9ZqaWsTExAAgo/nV1NTg2rWr4Hkezz//fCMHII1Gg71796KiohzPP/88xowZa7BGKhaLMXPmI6isLMTJkyegVqsBAJmZGaipqUZYWBgiIiJgbm7e6D6hUIjJkyfDy8sbMTE3EBsb2/BbQkICRCIRXnzxJYSEhDSq099+O4XLly/h0UcfxSOPzIJEIjF4p2HDhsPfPxD5+fnIyclpWG+/dOkSevRwwpw5cwz2E1tbW2P06NHgeR75+QXQ6XRQq9XYuvVrCAQCrFy5En379jPIy8rKCrNnz4JIJEJ8fDx0Oh1qamqQnJwMsVjSbByEysoKZGVlQSaTQyaTNZTx4sWL0Om0ePHFl+Dt7d2ovgUCIfz8/FFSUoQLFy5Ar9cDAORyOUJCQlqMiKjRaPDNN9+A4zi88sor6N+/v9F3mThx4l/r+/FQKusAAEVFRaiursIDD9xaG27aB273faVS2RB4JS4uDt9/vwseHp545plnIZVKDfKTSCSwt3cAAISGhkIkEkGpVGLjxg3geR4vvPAixo0bZ9DGAoEAffv2hYODI4RCAXr16gUA+OOP35GUlIixY8dh2bJlsLOzM8jT1tYWYrHoL3+L3gCArKwsREZGwsnJGa+88gp69OhhcJ+vry9GjBgBrVaLxMREEBEcHBzA8zx+//13pKenN6QNDQ2Fh4dHlzvHMac4xv809fX1iI6+AUtLKwQG9moxbVpaGi5e/AO2tvbYt28fjh49YiQVh5SUZAgEAiQl3RLePXr0wBtvvIk1a1bj2WefwcqVKxERMQW2trYmy5eSkoKiokJYWVljx47vDITcbW4PDpWVldDptOB5QlpaOiQSCWQyqdF7BAIOAoEAYrEYFhaWjQR2XFwsvL19jXrr1tTUIDY2Br169WoQLLdRKGpx7NgxCAQCnDt3HqmpaQAMg9IoFHXo0UOK/Pw8qFQq2NraIj+/ABqNBoGBgc2+p6WlJYYPH4HU1BQUFRUBAKqqqpCamgorKyuDSZZWq8Xly5chEomQkZGJd9/9d7NOjqWlJairq0NtbS0AIDs7G0VFBZg5cxYsLMybqUMhAIKdnR2EQiGSk5ORmJgIgHDo0CGcPXvW6H35+fkgArKzs1BdXYW6OiVSUpLh4OBgdKJ4u40rK8sxZcqUBoGlUCgQExONwMAgowLQysoKzz33PJYvX4o1a15HYWEh5syZY9SBsinZ2dmIiooCxwlw7NjPuHDhgtF0hYVF4DgOCQnxqKtTwtLSCteuXf1r0jjAqNPb7X4nkUgaHMESExMgEokxe/ajzXqJ19fXIzk5GRzHoWdPt7/uS0RsbCyGDBmKyZMnNysUq6urkZSUgCFDhjU4qp05cwYcx2HWrNmwsbExel9tbS3S0tIgk3k0OCpevXoVhYX5cHR0wqZNmyESCY2OBdeuXWuYrBARgoODsXjxEkRGbsOzzz6Dl156GePHj4eZmRnzcmcwOkpWVhZKSorRu3cfODg4tJg2MzMTZmYW4HkeBw7sazGtWCyBg4MjOI6DUCjEo4/OgUgkxtq1/8Krr67CyZMn8eqrryEwMLDFrTfZ2dl/aXDV2L+/5TxFIjGEQhE4ToCysmKkpqbA2toGMpnxwbGmphbFxUVwcXGFi4tLo0lETU01pk59yOhAk5KSAqWyDqGhAwwEb1lZOYqKCiAWS3D69KlWlFcIiUQCnudx+fIl8DyPgQMHmahbMQBqGETLysqQnZ0NV9eeBoKgqqqqYbJz5colXL16uYUnc5BIxBAIuIb2Njc3R0hI/0YTnjs9qktKigFwkEqlEAgEqK6uhkJRC57nm5nw3fn+IlhaWkIkEiMvLxd5eTl48MEIWFsbFyxJSTchFIowaNDgBqGVnp6G6upqTJr0oIE3NXBri9WECROwefPXWLv2Hbz//rs4ffo3vPzyywgPH9li3ysqKkJ9veqOdyET/d0BQqEQGo0GyckpsLCwaHZyUlFRgaKiYtjZ2cPBwQFarRZZWdkg4iGTyZoVyrW1tUhMTICFhQV8fX0bnqXTaREQEGBUU75NamoKRCIxBg0aBFtbW9TV1aGwsBDm5uaQSt2bvS8nJwdVVZUYNGgw3NxuTSIKCvIhEolRV6fAnj27Tfbz2+UyNzfHypWrYG/vgA0b1uOpp5ZizpzHsGLFSri7uzOBzmB0hIKCAhAR+vbta3SbUFNtj+M4PPLIbKxevdqo6bbpYHp7e5WFhQUee+wx9O/fH5s3b8Lhw4eRkZGBr7/+Gn5+/kbvJyKo1bfMkXPnPo7XX3/d5PsIhUIIhUKUl5cjIyMdAwcOanZrUmZmJioqyjF27LhGwXSysrIgFkswYMAAo5pydnY2RCIxgoODDQS+Wq0Gx3Hw8/PH119/DUfHHibLbGdnB51Oh5iYGNjbO7Q4sOl0OkRH34BOp4OX160lkry8PJSWFhvdIqTT6aBQKCASibB79x7RMj2ZAAAgAElEQVQEBgaaLI+lpeVfZtIE6PV6eHp6GhV8t7bARUOjUTcsTRAReJ7HkCFD8dVXm0weysFxHGxsbJCamgqOEyAkpL/Re9RqNdLT0yEUiuDhIW8oT25uLgQCAYKCgpoNiCQSiTB58mQEBwdj584d+Prrr/HKK69g/fr1GD58RLNl43k9iAijRo3BJ5980qr+bmNjg8LCQqSnp8HOzh5ubsbbsqSkBEVFhfD29oZUKgXHcTAzk0AgEECpVDabR0VFBWJibmDSpMkN5vHb6VuqayJCTk4OOI6DTCaDUCiEWCyGWCyGVquFRqNp9t68vDzU1dXB09Ozob/rdDoAwGuvrcbcuY+Z3FMvFAobJikODg54+eWXMXJkOD799FP88MNeZGVlYdOmza2ynDCBzmAYQa/XIyYmBjyvh6+vr8kT1pycekCn0+LmzSRYWlo2a6IzZs4VCAQQCATo06cPPvjgQ7i5uePLLzdg586d+Mc//mlUI+E4Dl5et9ZECwryYWVlZXJQvU1iYiLU6noMGDCw2YEuMTEBHCdopPHV19cjISEBOp3WqHalUqkQExMNrVYDDw/D393d3WFuboEbN66CCCatHv8dNHNRUlICb29v9OzZs9lB+fz584iLi8WQIcMQEBAAAEhIiAeARu9x52TB398fmZkZqKysbHV5FAoFrl+/DqFQ2OwkQKVSITo6Cu7u0ob4BRYWFjA3t0BVVRV0Ol2rB+jy8goIhUK4uroaba+KinLEx8fBwsK8YQKo0Whw48attvD29mm2790OjiKTyfDqq6/By8sbb7zxOj7//HMMHhzWbL93dHSERCJBamoKVCoVXF1dW/ku5cjPz0NY2JBmJ5O3td6goAiYmZlBIBDAyckZt5asUqBWq41ah65fvw6JRIJRo0Y1TDatrKz++kYKoFQqjVoqNBoNrl+/jvp6JYKCggDcWo93de0JrVaLmJhYhIUNMRDMer0eFy/+CZ7nERIS0nDd1tYORDxSU9NgZWXVapO5Xq+HUCiESCRCWNgQfPnlV1izZg1OnDiOkyd/xWOPPd6lYx5zimP8Twv0qKjr0Ot5BAX1Npk+NHQA/P0DER8fh2PHjkGr1RrVAhQKRcP/4+Li8OWXG1FSUtKQzsrKChERERCLxUhISGjx4JOAgAC4urri/PlzOHHiF4OY6jzPIyMjw+BEp4yMW9pcSEiIUQGh0WiQnp4OkUgEX1+fhoFMrVYjLS0VSmV1wxplU00xKioKjo494OfnZ/C7lZUVpk+fCWtrO2zfHom6ujqjA35hYWET824xqqqqoFarUVtba1AnPM8jOTkZ//nPR9Dr9Zg79zE4OztDp9MhLS0NIpEYvr6+BgOypaUlBg0aDL1ej02bvmpYd2/6Tv/f3nlHx1Vdi/u700fSqGtmNCpWteUqG4MLmGLAlICBAAmmOLz3CxB4TkKABMgjgVASQhJqEpKQAAYC5NEMxhhsggFj44JxxUWWbFnF6l1TNeX8/pA8nhmNpJFkmZLzrWXW4mpuOefuu/c5++y9T2VlZdg929ra+OKLnUyePDWs8E4ohw5VcvhwLdOnzwgakaKiIoqKiigr28fy5cuDM7lIV3ZbW1vYseTkZAIBP9u3b+83W/T5fGzYsJEDB8qZPHlKsBCR1+tl69bPSU5OCSuuckT2amtrWbp0aVjwlVqtZt68U8jMtNHQ0NjvOUIpLh7PxImTqK2t4a233ooq7w0NDTQ3N/cbKLpcLkpLpw/oOj8S0Dhz5szgOzvttNNIT8/gueeeZfny5djtdrxeL16vF7vdzooVK3j00UdQFBVW69GiPIWFhZhMibz//mo2bdrYT3b8fj979uzhk08+ITc3n3Hj8oJ/u+SSSzAa43j66adZu3Ytbrc7OGNvbW3l6aef5rXXXiM+PoHi4vHB8+bOnYtWq2P58rf4/PPPo8prZWVl8LvsHRhs4E9/+mPQo6AoCmlpaVxxxRUEAoHgOvtYov7Vr371K6n6Jd9EmpubeeKJxxGi16DX19ezf//+fv8qKyuxWq2kpKRgMBh4//3VrF+/Ho1Gg9VqRQhBe3s7q1at4qc/vZWGhkbmzJmDoij85S9/6fuIXZSUlKAoCnZ7NytXvsvatR9z8cWXMG/evAFddiaTCY1Gy4cfrmHdunXExcWTkpIMKLS2trJixdvcdtutOBxOZs6ciUajoauri6VLn6WmppobbrghqmFubm7iqaeewu128z//syTovuzp6WHZsmW0tbWTk5NLTk4OXq8XlUqFRqOhoqKcJ554jFmzZnP55d/p55LXaDRkZGTw7rsr2bRpIx0dHVgsFnQ6HXa7nc8++4z777+fd99dybx584JejhUr3mbt2o9pbW1h48aNpKSkBF3xTU1NrFy5kjvu+BlVVYdYtOhKrr/+BvR6PS0tLfzjH3/H4XCyZMmSqFHKNpuNLVs+Z/v2bZSVlWGxWDGZTLjdbsrLy/nLX/7Cvffew+zZs4Pu/m3btvHqq69y1llnc/7534pawWvDho2sXr2KSy+9jNNOO63PbawnNTWFlStXsnHjRnw+LxaLBZVKRUdHO2vXfsIdd9zOvn1lzJ07Nziz8/v9vPnmm+zZs4eMjAxsNhter5eamhpeeulFHnjgPoQQLFp0FXPnzkWlUlFVVcUTTzzOpEmTueKKRf1mpsuXL+fuu39BRUUFU6dORa/X43K5WLNmDStXvsO0adP47nevGNCDo9FoSE1NY+XKd9i0aSM+n5+0tDQ0Gg12u51169bxs5/9lN27dzN79uzg/V9//XV27tzBdddd32+gcUTGXnzxn9TUVHPdddcHg/nS0tKIi4sLDl7Xrv2YgwcrWbv2Yx555BGeeeYfOBwOfD4fixcvJi8vL+iFAVi/fh2bNm0mOTmF1NRU/H4/9fX1LFu2jDvvvJ329nZmzpzJpZdeGpTbnJwcGhsbWL/+E95+ezmbN29m7959rF69igcffJAVK5bj9XpJTk7myiuvDK6FJycn43K52bRpAx999BFJSckkJycjhKClpYVXX32FW265GZMpkcmTJ+P1evnFL+7iX/96ORi8KYSgra2NpUuXsm/fXhYvXhw1K+KYIjOVJd9UNm3aKAoK8oPFJrKyMqP+u+qqq4I5yE6nUzzyyCMiJydLZGVlivT0ZFFcXCiyszOFzWYRJSXjxQMP3C+6u7uEEEJUVlaKSy65WNhsVlFQkCcWLrxQzJx5gsjMtIhFi64Iy6UeCLvdLv7whz8IiyVdZGVlitTURDF58kRhs1mEzWYVEyaMF48++kiwqExNTY2YMWO6OPHEE8KKdoSye/dukZeXKy66aGFYdbSenh7xxz8+IdLTk0VWVqZITo4XBQV5Yt++vUIIIVasWCFsNqt44IEHgsVoouWpr169Wpx44kyRlZUpzOY0UVRUIAoK8kRmpllYrRliyZIl4sCBA8F85yVL/kfk548T119/XV+VN6swm9PE1KmTRVaWta+dxeKhh34rWluP5vyWlZWJoqKCfu2I5LPPPhPnnLNA2GxWYbWaxbhxOWLSpBJhtWYIq9UsLrpoodi8eXMwl3zp0qV9eeJ/jXo9r9crHnjgfmGxZIg33ni939+WLl0qiot7q6KlpSWFvC+LyMnJErfffrtoa2sLy69+8MEHgzKXmWkREydOEOnpyeKUU04Wp512qsjOtonly5cHz1mz5oN+hYEi86d/8IMbhMWSIQoLC8S5554jzj77LJGdnSlOO+3UqHnl/d+lVzz//POipGSCyM7OFBkZKaKwME+MG5ctMjMtIjc3W/zv//5cNDU1BgvKLFq0SBQW5ocVDQrl8OHDYv78M8QJJ8zoJ/9ut1u8/PLL4sILLxAmk0YkJRlFamqiuOCCb4lnnnlaXHHFFcJqNQfzyENrMdx0043CbE4TWVmZwmrNEMXFhcJqzRCFhfli/vwzRHa2Tdx33339nqe9vV089tijYs6cWcJgQCQm6oXVmiEWL75GPPvss2L27FmitHSq2Lt3T7/z7rrrLmGzWfp0QUrfPc3CZrOKqVOniL///amgXO7atUvMn3+GsNksYtq0KeLiiy8SU6dOFhZLurj55h+HFYUaKxQh5EbIkm8m69Z9wqpVq4b8XXHxeL73ve+FzTB27drJO++sZNeuXTgcdtLTM5gxYwbz589n0qRJYWvdjY0NLFv2Jp99tpnGxkZyc3OZOnUql112GWZzbOuSHo+HTZs28emn69m5cyddXV1YLFamTJnCggULKCkpCc4i9+3bxz//+QJms5kbb7wp6rr7+vXreffdlRQXF3PNNYvDZmkOh4M1a9awd+9euru7MRj0/PSnP0Or1bJixdts3ryZ008/gwULFgwaN1BeXs4HH3zA1q2fU1dXh8lkYtKkyZx88snMnTs36Dru6OjgyisX0djYwEsv/Qu3283q1b3uU4/Hg9lsYcqUyZx++hmUlpaGzZY3b97E8uXLo7Yjmqv7/fffZ8uWLRw4UIFOp6O4uJhZs2Zz6qmnBiP9fT4fzz23lMrKSi666GJmzZrV71put5snn/wzbW1t/Nd//Xe/5Qe/38+uXbv6atFvo7m5GYvFQmlpKXPnnsyMGTP6zagdDgerV6/mo48+orx8P3l5+UyZMpkFC85h3brevOVrr72W4uLxCCFYvXoVn3yyjtmzZ7Nw4cKobW5vb+f999/nk0/WUlVVRWpqKtOnT2fhwoUUFhbFHAPS25bVbNu2nfb2NjIyzEyePIl5805lxowZwYC8xsZGnnqqd7vdW265NWpqZnV1Nf/4x99JTEziJz/5SVTvR0tLC21tbXR0dJCcnExqagpqtYZFi65g69YtvPvuKk488aSwczo7O1mz5gM+/PDDvowUPVOmTOGcc86ltbWVjz/+iPPOO5+zzz47anzGkaUQt9tNUlISGRkZNDc3s2jRFWg0Gv71r38FAzFD4yjWrl3L2rUfU1ZWht3eTVFRMVOmTOWMM86gqKgo2D4hBFVVVbz99tts3LiBjo4OiouL++rqnx1zfMdokAZd8o0lEPATCAwt3qHR6pFrmw6Hg0AggEajISEhYdAdnBwOB16vF71ej8FgGFERiUAggN1ux+/3o9VqgwFBkb85Egw1kIGL5TdH2njE/XrEUAkhgkF+seBwOOjp6UGtVhEXF99Pge/evZvvfvc75Obm8vrrbxAXF4cQgq6uLgKBwIDtHE47Io2xy+VCURTi4uKiDniOtFOtVg/4To/0zWC/EULQ3d2Nz+dDq9UOKiNHn8+Fy+VGr9cHjX60ew3nXbhcLjweDxqNmvj4hBHttBYICOz2bvx+PxqNhvj4+H73FUIEi9cMtNGIEAH8/gCKAmp17HHXW7du5bLLvk1qahrvvbdqwIC73ra6URQV8fG98ubz+YLPHaucALz11pvcfPOPOfHEk3jhhX8OmEng9XpxOp34/X6MRuOgWzAfkYkjvx2o5sJYIKPcJd9YVCo1oynMpNFooq7ZDjQoiHVXtcGfWTVkQZpYFHysBjlSKQ9HGR4hPj6+X5W1UOrr6+ns7OCEEy4JKkJFUWLq2+EMLI5gMBiGVKKxtDOWnbEURYmpgFD48/VGyg91r+G8i6GMTGyyN3RbFEUZsl8URYVGo+o3OFqx4m3Gjx9PScnEsHcaCATYt28fDz30W7xeL1deedWgs9lobdVoNP2ey+Vy8corr7BgwYJ+O9/19PTw2Wef8cgjvUF4V1yxaND+02q1w9IFw5UJadAlEsnXgq1bt6JSqZg9e86I9+iWfL3ZsuUz7rjjdpKTU5gzZw4nnTSLrKwsmpub2bZtG//+9/s0NjYwf/6ZLF68+JhsM/r228u59957eOGF55k9ezYzZ55IcnIyhw/XsmPHDt577z26u7u48sqruPDCC78R/Sxd7hKJZMzw+bzcdNNNfPTRh7z44stR16sl33x6C6v8lQ8++DdNTY1h6VuKopCRYWbhwoX84Ac3DlinYLhs376dJ598kg0bPqWzs6Of98NqzeTaa6/l6quvibnmhDToEonkPxaPx8POnTvx+31MnDgpZrel5JtHbx2HKqqqqqioqKCrq4vExCRycnIoLCxg3Li8ES35DIbf72ffvn3U1dVRWXkQp9NJamoa+fn55OfnYbNljfmGKdKgSyQSiUQiGRayUpxEIpFIJNKgSyQSiUQikQZdIpFIJBKJNOgSiUQikUikQZdIJBKJRBp0iUQikUgk0qBLJBKJRCKRBl0ikUgkEok06BKJRCKRSIMukUgkEolEGnSJRCKRSCTSoEskEolEIpEGXSKRSCQSadAlEolEIpFIgy6RSCQSiUQadIlEIpFIJNKgSyQSiUQiDbpEIpFIJBJp0CUSiUQikUiDLpFIJBKJRBp0iUQikUikQZdIJBKJRCINukQikUgkEmnQJRKJRCKRxILmy7hpm9dNvdtOmauT9h4XakVFgkZHviGBHEMiaTojakUZ8PweEeCgowN/wD/iZzCqteTHJxN6l2aPk6YeB4ijxyxGE+laQ/j9AwEqHO0IEeg9oECy1kiWIWHI+3oCfiocbWH3MGn15BgTw57FKwIcOAZtLIhPHvX7qnJ2Yvf1jPh8tUpFQVwKOpUKd8BPpaOdgBCjeyhFwWYwkaLVD/vUCkc7Hr8v7FiKzogthvd39N204w8Ewo5nGk2kRsjKUKzvqKelxxX8/3i1ltNSbOhU6pivYfd7aXLbEQzepwoKBkWFolKhV2tJ0RpQhrh2t6+HGlcX4sj7UsCsTyBDZxzyubp8PdQ4O8OOZejjMevjwo45/F6qnJ1H7zECUnVGMmN8f6G0e93UubpHJYpDvfcuXw/17m72Ojtp97oAhQSNFqsujmJjEsk6I4ZhvO8j19vlaKfb50EA8Wod4/Tx5Mclkaw1oB/G9SJlu9njpMzRTr3XSXePGxAYNXqy9fFMjE8lZRjPKxAccHbi8XmDxwxqDflxyagUZcjzy+xt+EJ0oFalpiA+BU3IuQI45OzEGaKjdGoNBXHJg9qRI5Q72ukJ0Qeh+ir0HrWubrq87pHPnhWF/PiUYb3rr7RB7/B5WNVUydKWA7zncfR1kxLSZTBZY+DyhHS+lVFAaaI5qmB2+Xq48cCnfOxxjPhZfmay8OuS09AqR1/axvZaLqreFva75fmzWJiRH6HkPEwuXwshAnS2IZG/j59HnsE05GBmyr4PIUR5/S51HLcWzg4TPoffy7UHN7DZbR9xG28zZfCHiWeO+r39q3YXd3YcHvH5J+niWDHpbMw6Iy1eN1eXf8K2UQwQjhj0jwtP5rTU7GGf+vChLfzV0RZ27Lvxqfx5/Kn9Bm/R+LjtMN+u3IQ9bLAlWJ0/hwUZeTE/R1OPizsqN7PeF6IkFBV7dWdSYkqLfcDl7uaEPR/QIwIx9Bug0rBAa+A0YwoXmAuZZEof0AAccnUxrewjCGnrdYkWfls4l7QhBlPVjnamln0Y8o3DmznTuThzQvjv3HbO2v8xDRGDrOHwkqWEK8eVDvu8HV3NzD+wPuwZh4fg3wUnc1Z6br+/OAM+3m06yKvNlfyfuzOqvrOptVwel8q5abmckpJNkkY34J2cAR//bj7ES80H+D9X5PV6rzlOrePbcSlclJ7HzGQbiYNcL3KStLOriTcaK1juaGG3zxOlTwRZah2XGlO41FzASck24tWDmxCfENxTtZWXupuDx2xqLf8qmMO8FNugvS6E4NaDG1npPjrgutSYxNMTzyQ5pF1+EeCx2p080VEXPJaoUvNG/mzOTMsZ/B4I7jy0hTdC9EGovgp9ltcayri1+cCIZXSqWsuKKeeSq48fMxt73FzujR4nP9u/nkWHd7IqaIiVCE2jsNvn4d6Ow8yuWMed+9dx0NkRdd6hQQFl5P9USnRdp4743UDCkBnxu7Webh6v3o7d7x2yLywRz64MMIrUjbaNI1ZS/ftlNM+hVY5tu1AUElFG3DpVlPu/4mxnWWMF/iFmiY09Lp6s34NdBPpdQxnmA33aVstWX09Q9kEBIXi7qYIAYlhvyBpr36FAwM/7Hge/7KjlhPK1/PrAJtoGmXlYIq7xj+5mXqzfizeWAUSkrEd5a4oCCaOUCWWEwqAoo5fFaPe2+708cnALl9fs4BV354D6rs7v44nuJi44tIUb9q5hU3tdVO9Vt9/LHyo/5+KabX3GnCgGV6HK7+Wx7ibOrNzMkn0fsamjnqHe0mG3nfvKNzCvfB0PdtaxOyiT/d/lYb+XP9qbmH9wE7eWfcyhCA9MVA9dxLutC/h4oGYH1e7uGM4N1z3qAZ4sUm93iQC/qt1BubNj2PfQKmOjB3WKMuZ29rgYdJffxy8PbuQfjpaQselQA1/BY92NPFi1FV8gwFedHuC5rgaer9+Hb7TuZMmXwh+bKyhztA8623i1YT/LXJ2j/yYCPl5pOYgrytfwUlcDDW7H8Wm0ENzfUcsvDmykO4bBaK9iEzzUfIBVLdXDHHj8Z+AXgmdqdvHL9uq+OWBsvOLu4mfVW2mJGFx5RYB/1OzinrYqlGHoln+6OvhV9TZaQ5Z0Itlnb+XG/Z/w687DeMRw9KzgKUcr3y/7mE/b64bdR6s93fyhajudo/XUDcK6Hie/q9pGm9fzHyN7x8XlvqWznlfsrWHHUlCYqDMyXp+ARwSodHdT5e+hPkRg81QafpQ9Fa1q6HGHCchV1DHP2kJd7ceKdiF4vLGciXEpzB+BK7j/JxNOPJD3JbcRwACMU1RoY3ySBEUdZg40itLr4Yg0mEBzhMJKRCFeiT7qP9bj3V2+Hv5yeDe/LZob1ZW4x97Kn1oOHpN77ehsYrW7K+rftvs8rG2rYZFt4oivn4FCiqKEyVAAcCFoFYJIFfdidxPnNFVySeb4mOSyLuDn14d3UhSXREl8yjGXsQwULMOQX/UxnP3kKwrxMc51vIh+krjP2c4TrZURcgwTtQZKDIkIBBVuOzU+D/UiwJGFhnhF4ee2yf3iE6qdXfym9SBKiE6IB6ZqjRTpE9ApCgc8Diq9LupFAG/Qi6hiibVkwHiHSlcXPzqwkX/3OPrNRFMVhSxFTZrWQADo9Lmp8vtpj9BKa3xueg59xpOaU5hqSh9WP7/Q3cDEhjJuzJoS03r6SPg/ewsT6vbwk9zSMdGH4xVVr8cxBhIVFWM9Rx9zg+4XgnfbaukKEwSF32dO5LuZEzD2rd35RIBd3a280VjOsq4GykSAe6wTmJyQHlWh+CIE6xR9PC9MPCvmDtMoqjF5wfsDPu6v2UGWIYHxcaMISBP92zhdH8/rJfPRxPjcY2XQC1VqXi6Zj00XF5sbSFFIUveueaVp9fyx6JSobsVDjjYur90e5lT7QUo2V5iLovq/hopXGAl/627grNZqLjbnhynqbr+XPx/eTVmMs9ihvom3WippHWS29XxLJReYCzHFuAYayZJEK/89bkaYBPlEgE6fh71dTfypqYKNvqNmvQt4sbmC8y2FMQdUbfS6ub9qK48Wn4xZaxy5qAuIDP1cnJTJXfknxTy/PZaBRo/ZpnLKMGIh4tXaMN30RWcjNRHBrHek5bEkd3pwoOgXgjJnOx+2VLO0rYrtfi+3JGczPy23nw7b2FFHS4iX0gjck57PDTmlwesFhKDc2cGqlkO83FbNLr+X7yfbOHeAdjj8Xu6t3MxHEcY8BYXz4pK5MXMi0xIzetsmeoN5N3fW81JjBW84Wgj1Y63zebiv8jP+OnE+acMICu0Ugocb91NkTGbBEGvdI8WO4I/NByiJS+bCjLwRTwNEn4cu8ujL409jnDExRs+WMmiMxNfCoAsEO93dYZ9lqdbAxZZCTCEfgkZRcVKShZmJZq60t7C6tZpLLcVRR94KfWvoocYLhTSNfsD16OPJhz0OnqjezgNFc0nW6Ed2EYV+M2ANKlI1hpg8FmOJGkjR6If18QaVkUrNjAFG8vFRXH65ujhmJmYct7Z5heCR+j2ckGgmty9qOoDgvZZDPNXdeEzucdDZwf91Hb2WHphvMPFeyJriux4727qaRhT0B5Cq1gafP5ITTBlMNZm5qvwTdgeOBqJt97qpdHUNa8b9qqOVaYf38JPc6SOOrFaUvnXMCDlJ1eq/FPlOVGtGJNtHNN4OVydhjmRFxTXWCWHKXKPAtIR0piakc7G5kFcaK7g6c0LUgUlnRPBvhqJwiWV8uHFQYHJCGpMS0rjUXMRz9Xu5LnvKgIP6T9pqecfZHvQOKIAJhfstxfx31hTiQj1UCmhVKs5My2VOso0ZNTu5r/kATSFa/TVPN5c1Vw7bq1QZ8PNg7Q4KjYkUxiWNyfusFQF+fXgXecZEpiakjVQdh0XWHyFZoxuFrBx7jotlcIvw0epOfw9Ob8+As7lppgx+mjcz5gjNryJ/7m5mad1eer4G6/+SCGXX4+Sl+n3Bd1fl6ubh+n3HaIALq1qrqAwxpFPVWn6bdxKlEYO/V5sq6BlF2uJgTEvM4Fvx4cqtQvhxD3O90Qv8vqWSt5sr5Xp63/v1RL4zEaC5xzmgociLS+L2/JlR014DCJyB8Oh/p4A6j33Q691TOIcsffQBnSvg5+mGMlpCZpwCuCU1h+9nTw035hHEqTVcl1vKjSlZ/b1KzQdpHWZalwA+6nHy2+qtwz53OPfY5HXzUPU2mgaJJ/gmMOYGXUEhN8IdJwJ+flm5mY3th49ZwEIwAvFLwhYxslYQPNRUwcdtNcdUzX0FHBDfAK0bPsgap6goVevCPoY/tVWxpasBrwjwUv0+NnnDFcG5UZSlLoYljpYeF8vba8N8L+clWpmSkMb1qeGpTy/am6mIIUp3pMRFzixE8D/hRiXC1Rgp660iwG/qvuCL7tYIY8SIs8G+XDFXRnGmQl7EUpQK+MWhLaxoPECjx8lwhvgqFBIjBnotCH5VtZW3Gito8jiHzMyIZL+9jU0hAwIFOFGj579sk2JautCr1NyUU8psdfiE690ee7++FXMAABcqSURBVL+6A9HIUFSoI9aTX+hu4YX6fUNmTgQzVIbAgEJ8xPf4oqONpw5/gfsYDpIVvloKecxd7ipF4VyThRe7m8LcUM8723m+Yh3n6U3Mj09joimdUlMGmYaEIdd+BaLf+nKd38urDeUxGbx5yZlk6hOOaTtPiUtmoi6Bh9qq8PSpxSYR4N6a7RTEJVE4zPV0IXrdv6E0+3t4rbEipgCgk5OsZI3BGjP0rn2903KI1Bg8KHnGJE5KNH8F51FHmajRc7V1Aotrd6CI3lXbwwE/T9TuYrHXw8NtVWG/X2IyMy/RwqrDu8KOxxKuuK6tlvdDZms2ReHijALUisK56XkkNR+gs0+ptQvBe82VlMSnHvOgIXfAT21EtH6WSoUmZBmsVw4FkdnhVyRn4exx8jd7S/DYNl8Pv636nCcmnB7M5ffFGDUdbQ19j7ub1xrLhxwMKyicl5ZLwjH05n3U1UhzDGbXqNJwdlpumBFUgBmmDNKaKmjte/oAsNrr4r3qLZxYb2RhfDpTEjM4wZRBuj6BhCFyuScmWqC5PGyg8ZHXxUfVW5lRt5sL4lIoTbIyM9GMWZ8wZG74ju5makLejQDON2XEvBYMYNHHc1myjU2th8LexsbOeqYnWQY9N1tr4O7UXO5tPOol6EHw+6YKJselcFZ67oAptxoltlmoW6XiWWsJd9Xvpa6vrQrwcOshpsSlstBcMKxASkF/fQwKK1urMHcPHT+SYzAxO8n69Q+KU4CzMvKY21zOWq874gNVeM9j5z2PHdoOUajWcaExiTNTx3Fyio30AaIzFZR+a+hbfB6uqNka05v5XHfqMTfoCYqaH2RPocxj5xVH76ccANb7PNx/6HP+UHxKTEVLQmfi2giB2+PzcGXNtph6/bPCk/sZ9EpnJ+4hineoVArF8SmD5rBXiQA31u0mlgTE35uLx8SgCwQVjo4hUxo1KhXFkWvCEQNGBYX5qdnc5Wjj123VweNvujpZW72V9r4PWQEma3T8IGsKdVFmIkOl/dj9Xt5sDR8cnGJIYkpfTEGOMZEbTGZ+39UQ/Ptz7TVcYZtI1jEsRuEK+Hm5bm9fsZOjTNboyYyQGeVI/mzIqx6nNbLAOp5dFZ/yacjg5E1XJ0XV2/l5/okYVZpej4UYesIbbQ39DVcHb1RvjUnWG5Osx9Sg39tRCx01Q/7uQl08J6dk9ZvVnpBk5bL4VJ5ytIZ7K1DY4nWzpe/66SoNF+hNLEjJZn5aDrYBBuAzksxcH5/B3x0t/f62zedhW1cDdNVjVmk4X2/irJQszk7PI3MAmamM4q4vTcgYlrFRgJMSzRhbDxHqu7LH4NJ2iwCXmwtp8br5feshnH2apE4EuLt2J1lGE5PiU6Oe2yNEzFUmv5WeR4ffyz2N5XT1hVd2CMG9dV+QazRxwjD0kkJ/fawCftiwLyY9eG9qHrMSLWMe43Vc0tbSdEYeK5jDzQc3stHrpmeALjvg9/K4vYXH7S2c27CX/82eximpOcMYScXwO2Xs1vnMOiN3586govwTPg+JIH7O0cr4w7u5LXf6l+oO/F3NDv7Z3TTob0rUOj4tvQBVTAFOSgy/GBsB9gvBbVWf8+EQLulzdXG8PPW8CK9P/2cyqNRcZ5vMp/ZWPuyL/PUA9SHuOYHCTy0TmGxK43AUgz7UGvLu7haedx6tSBUPLM4oCAaT6VVqFmbk8/uu+uAzlvu9rG+t5ju2icPqyR3uLpY17A8tSEgAQXWPk+32Ft52deAM+aMBuCY9f8jqb0d6YlJ8KndnTeX6qi3BiG4X8Nf2Worjkrk6ohrc8Zb143Fv1QDSHafWcE/BbFwVn/KqqwP3ANdvCfh5ztXBc64OTm7az83WiXzbWtzPQ5mg1nJvwSxcBzbwqrMdzwDXawq53pnNB/ihtYTzzYX9Bhz9iwgJsnTDz1LQa/TEKwquEDmq83rwBALohwjcNag03Jg9hT2uTl53tgf9IRu9Lh6s2sYfik7GrBtdsJlWUfE920R2OTt4vrsp6Gna7vPwYPU2Hiueh00fN+LrB4ajB4/TWqnqeH0apYlmXpl4No9bJjBLoyNpiE5Y1ePkvys383bTga9VsE1JQgr3ZE/rl0P7p5ZKVrYc+lJbEhAB7EP88wv/16avY2mPCMQuPXlGE7fZJmEeYMnnelMGl5gLR1SBr0cEeKc5PDd5gkbPnJSssKtNMZm5RH/U9ekCnms+iDswvLKoT7s6uLRmO5fVHv33ndod3NZUzgvOdjqECCokDfAtQyLnZRQM6x7z03K4NaMQU0gLmkWA39fvZUtnI//J2AwJPFlyBi9nl3K21kjGEAp9g6+Hmw7v5M9V26KuI2caEnhywum8kDWN07RG0pXBh8prvG6ur93BU9Xb+5UE1kYZrI9kb4WAEP2WSowqVdQqnNEGS1ZdHHePO4ETImIE/ulo5ZnDu/Ecg4DiVI2eu8bNYJ4uLqy/XnN18mTtLlx+/zdK7o5bLXcFsOjjuCF3GlfaStjZ2ci6zkbWdNVT7uuhKooQHxQB7qrdycxECzlGU8h4sn+OtkVRmKkb2i3pR2BQj12zVSiclz6O/3V2cHNTefB4gwhwX+1OHlJrY6yU11u0Ikw4FRWzdcaYZr1a1di10URvvWNDDEFgpq9ZpsKZaTl8v7OBB9vDXa6lah03ZU0ecR5pjauLv3XVhx0r1sWxvbspYu1dIVWrI3Qa9pnXyca2OuZHqRc+WuJR+JYxkYeLTo5agESIAO4BlL1OUfH9rMmUOzv4a3dTcICwy+/loaptXG0uimmSHW0NvUilYYLWMOS3ElAUVMe43sIcjY5U9dDvOVNrHHRGlKDRcXHmBBaYC/iiq5l1HfWs625kn9fFvojALAG0CcEDzQc5JdnGScmZUb+ly20lLDDns7e7hU2djazpaqDM62J/lECvViH4bUslc5JtzAq5Xv90QIUdznZOTssZVj81ubtxRMhGukY/ZAxUvKIKxjpNSkjl/uxpXFu1haaQa/2+pZKpcSlEVn0wKKphv+98YxK/yT2BKw98GmZn/txWw7S4FDwxDGai56HDfK0xWEtlMNI0huPicDruu62pUEjS6Dk1LZd5abn8yO/loLOTnZ0NvNFWwzJPd1hFpP0BHxvbasjOmhTsj2h56LN08Sybel5Mxm6s3R9aRcX3siaxzdnBUntzUCB2+r38rHobnbGY9Ch56FN1cSybcm5MBWOitTGWgUQs49V8lZpnJ5xBdgzrumPZ1bFMKsQwfSJGlYbrsiazwdHKR33rwyYUlliKKR1mJayjrjnBhy3VNEUo3WXOdt45uKnf7yOVWLMQvN58gNPSco5pRbQZah0/sYznIkvhgPUSFEVBO9iATa3lttwZ7C1fF1yqAHjD082eut0xuiP7r6F/N8nKA0Unx7QD27EOGPx15hTOsBTGps+GuLdCb+GZ2Sk2ZqXYuKWvAMzuriaWt1XztquDdnFUStsQvNtSxQlJ1gFrcCRr9MxNyWJOShZLRIAKZyf7u5t5o7WKFRHXqxcBVjQfDDPo04z9A3R3dTXhCfhjriXgF4J3O+v7LZ+ajUPnkvcQCH67KhTOSh/HrY527myuCP6mHcGPD++gK+L9+xDD/qYVYFZyJndbJ/Lj+j04+s7vRHBL3Rcxedyi56EL/l58Kvkx5M8ryvGJiP9Stk8N7aQEtZZppnSmmdK52Dqe02p2cktIeU0fsNnVwWVCDGmIVShficIy9H10d46bQVX5Oj7sMwwBYKfPM6oeU6GMWIHdapvMEn/xEH3Ym1ISiyJTfYl9rVYUfpcznd8EBq/cplHUUQtCDEaBMZGfZE6irHor9SLApQlpfMdSPOLNbjq8Hp5uOxRFsUGslaxXOtu40d7CFFNsRXZOV+uYbjAFVV+dz8Nyjz3sfvlaAwvNBUMUP1J6DcsgOrQgLom7c0qprdxMecjSwD5/zygkvVf9fRnfs0phTGT7SHsmxKcwIT6FCyxFnFVfxvfqvggbdK9zdxAQYsjBm9I3eZgYn8LE+BTOMRfwSl0ZP2vYE1ZCudrdjSvgD84kJyVmMF2lYXvIu/qLs43vdTQwJzUrprbs7G7mY0d4mqJeUTE3yTrkuZHR4lpFxfezJlHm6uDZkMyJyigBvD4hRrTNrlpRuMxazA5nO090Hq09Xz/KFDZljGTlK2/Qyx3t7LW3cn5GwYCVzkwaHd+1TuCW1sqw6Zcj8PVc5xgfl8wd2dM4dGgLhwK+Lz0SoOQ4Vlwb+8GgwuSksUuHOyd9HNd0NfBeVyM/zpoStl3jsLwIwKftdewcZdGMyoCfVS1VTDbFFo18eaKVHxbNCf5/a48L774PWe6xB+XwDXcXC+rLuD5n2qhn/vNSsrjVOZ5bG/aGBUn9p9LocbKmrZqFGYUkaKL7OPQqNQvNhcxqOcjmkGwBh9/Xz59W53Gwoe0wZ2fkDbjsY1Rp+HbmeN5oqWS59+j13EL0pRD2GvQ8QyJnJqSxPaRaoRq4r2YbfzOayBkifa25x8XD1dv7uflvSEgn0ziy7KF0rYE7cmewv2I96wcowjNakjQ6fppbSkV5d9iWrN8kjktQXIPHwc8PbuLi6m08cHATe+2tAxZDqPc4+vlSC7VxQ6e+AF+xHP/elL3UbG43F4cFDo12RCgZJSKWHGM1P8yexq9sUyiNcVasV/q7Kz0BP882VRCqovJUar5lSOTCIf7lhcRBKMCyjsPUu+0xDyRCSdMZuSOnFBEhQHc3lbOls2H0MwNF4ZrMCSxJsn0jhoujocvXw32HPuOq2p3cXPYx2zsbBtyBscvXQ0dEwKNZYwj70O1+L48c+pzLa7dxS9ladnQ2DZjj3+BxcDjCa2XWaEkIqS+gUhSuzZxEQYgnzg+82+PkR+Xr+LyjIWogsl8I9jnauLtiAy+6wrNL0hQVi60lGEcRuzM+PplfZk0lS6UeM1WebTBxZ04p49XaY3KP/7jCMh0+D7879Dmvu7tQgPvaa/hnZz2Xm8ycnZJFtjERrUqDXwQ45Ojg4fo9YecnANNMaWHuzmiFZer9XpY1VMTcvXEaHaenZh/TTR2iKzoVV2ZOYJernb91NhCrryFaYZkWfw9vNlTEPJuKU2s5PS3nmLexSwjeaz5EWoyzVpWiYn5azlenlG+M/ZdrSCDLUhRzf0eLTt7Z3cyGiHzvW9LyuTZ7ypDXe7OhnP+q3x000Ot9Hta0VnNN1qQRNXtWso0n0gv5cchaZbMIcF/VVp6PO5M0nXFU3Zqg1vLDnGl84e7mvQF2khtI1iO/izJ3N282VsTsXjXr45mbnHlM3J+fdDXSPoytRPPjU5jeF1/hFQGW1n7BM32z32ecbbxdvo6r49M4IyWb8fEpaNVaBIImt52n6vexP2QLUTVwnik9KHM9gQDP1H7Bw10NgMKzzjbeKV/L1aYMTk3KpCQ+DZ1GQ0AI6l3d/KOhjM8jNhDKi0/rpxenmNJZkp7PL5oPhOWRv+Wxs6liHf8v0co5qTmk64woikJHj5t32mp4q7uR3VE2KLorLY/SUXrMFBTOTMvhTlcnP2oogzHwaSrAKUmZ/DJzIj86vIuOGOVroMIyq1qrsHQZY1Q7CnNSbFh1cWOm2sbUoAtgeeMB/tZXKONIdxwM+PhdZx2/66wjRaXGrKhwiAC1UVzrM3RxTDWZ+734yKC4z3weLoup6Eov5+lNzEq2jrlBP+LquT13BhX71/JvjyOm0o/RCsvs9nn4Tu32mO97oT6Bk1Iyj3kbD4kA1/cZmtgkWUV1YsZXqDZ/7Ep/OK7oyFlNAMHbzZU0hCiCOJWac9LzYoqWPyt9HLOb9rMpRIG+21bDRZaiEfWlWlG42jaJT7oaedVz1OX4YY+DZ2p3cVv+SaM2iLkGE/flTufggQ3sj3V/9ShBca+5OngtpsIyvdyWZGNWspVjsUHl3R210FEbs5Z70jopaNA/ba/jty0Hw3LPm0WAx+zNPGZvJk5Rka1S40Nw0O/vZ7RsKjXzUnOC7djQWc89zRVhgcJNIsCjXY082tVIsqLCqlLjRXAgyprzVJWGC9JyowyyFW7MmUa9x8HjXQ1hgZgNIsBvOuv4TWdd3+BXGdCrpaV3Z7/rckpjKn08FFpFxTWZE9jrbOfJrrFJfVQpCpeYC/nC0c5D7TUxa4xohWVuaoh9j4ckRcUHRtOYGnTVWKvNS63FPGQuIneAl90e8FPm90Y15jmKivuyp2HRH/sOON6u63EGE3flzqBAffziEL/cPdnCO/s/caXgoLOLtzrrw1T2TQkZFMRYBjjLkMD8xPBykS+5O9nR1TTiZ0rVGbgtp5SkkO/RBTzeVs2HrdXH5Js/IdHCLzInkXAcP7IvT77C7zw3OZMnsqYxWaWJ+v05RYD9fi8Ho6yTp6LwG+tESkKqpM1OsvBM1jQKB3Bld4gA+/zeqMY8TVH4iWU84wfYYSxOreWXhXO4O3UcSYO5TwYw5umKwi9Tc7mrYBYmjfaY9WiyRs9tuTNYcIyreUZ6k27OKeUyY/KI9eRws+T1x0FOx1znJ6i13JQ7gzeK5rEk0UJhDKM4LTBHo+eZcSdyamrON8YYnJKUyS+tE0mRC+H/Efy75RD7ItZHz08bhy7G7W8V4NvpeVgj5GVZU8WoNpg4MTmT+9PDi8gcFgF+V7uTeo991O1WKwqXWwq5LSXnP+6d61RqLsssZlnJfH6eks2kGL1jpWotj9om893MkjCvkEGl4ZLMCbxTcga/SslhYoxr1NPVWh61TeGakHTfaCRqdPw0/0ReGXciF+kTiKU2mwE4RxfHs7kzuT3/pGGVtI6VfGMiP8+eRskY1tPI1Mdxe+50pn2Nd/WM5LhMF9WKwsxkK9OSzNxkb2NzZz2fdjVR4bHTIgJ0iAAGFHJUGnJ1Rs5LyeHUtJwB61erUJiki8M2CsOYpo3r556LU2u5KmRUKISIupWgWlE4RxdPIKT4RE4MQq1WFC61FFHl7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+DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:10] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:10.284570 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:10] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.571376 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.597269 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.625073 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:23:30.649162 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.687156 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:23:30.720828 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.743914 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:23:30.766949 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.796841 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.832563 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.894021 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:30] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:30.950556 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:35] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:38] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:23:39.465363 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:23:41] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:26:49.347366 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:26:49.347366 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:26:49.348383 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:26:49.348383 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:26:49.348383 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:27:06.202239 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:27:06.203245 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:27:06.203245 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:27:06.203245 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:27:06.203245 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 10:27:37.029071 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.032072 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.034114 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.039076 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.044078 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.049627 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:37.060587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:37.077603 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.079587 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.085587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:37.091589 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:37.093587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:37.821184 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:37] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:38] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:46.110982 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:46.114986 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:46] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:46] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:49.227545 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  neutre   part 3 part nom 3  

Situé :adresse03    code_postal03   ville03    pays03

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   adr site1  , cp site 1 - vile sit1 
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    03/12/2025 10:00  au 03/12/2025 12:30
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Du    05/12/2025 09:00  au 05/12/2025 17:30
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Du    10/12/2025 09:00  au 10/12/2025 17:30
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Du    15/12/2025 09:00  au 15/12/2025 17:30
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Du    16/12/2025 09:00  au 16/12/2025 17:30
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Au plaisir de vous retrouver prochainement,
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11/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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ttx9kB7oARSbstqdiAxrubiiy9e/KDUZTFixIji29/+dvF6jWLljM4hE1onoKCVxNCJxx0/ScGtVqTRhx4WJbhrtTvVgtalVGw6paH3lNS1R+pDbRaYa6Atar11BsdrVA+6GlZefoXYa/vUkxNllZoVujSOOuqoSGijKnLkCfvvv3/xjW98o/jZz35WeSajq8iE1glQztASpSUnyXHDo4+0NKuvudrqHRq/pnKdvlnS2Z/SoCqywrLLxof/byboAhi+8y7FSccfP4lkUzX+/Nlncc6Bxv33ewER6AoZOHBgJLSzzjorxtMSDjnkkGLqqacuXnrppcozGV1FJrROwI/wwAMOiD2KZH0S6OnrdTz7jDMrzyCND4rbbh1fXHnFFcWEUrsQa+7kE0+KzeD6ObUBUYRQXElqm+UxYcKEaKkYywavvfpaVKEw0ehnP5u83Qe4alq27r7rruLKK6+IY/fKI/lYO3fdcUdU2zBoheDhisstH+cI/Ptf/4ok+2awQB3Hddde26qDRrXX5+iJaWn6vBLI9pnXX3stNpub5JRalCxcLUvXh214kBdK8J4bwvtJCHEra8G1oCHHGk4QZ9IOZrbCtddc0+pmagV7/rnnw3WqT3zNAq1uCyywQIyVvVU1ZpDLOVP4PRhhmNE9ZELrJMhVa9bWGI5E9COS8SHmaCHDhMcmFCuvsGK02jSLU+7Yfdfhxd8DqVGw1VitWdpnNGOLBZ195lnxOWqxpLtJ5OhL/P7ll0cXTEO756nIvvTi5HdylhapH83xmsM1zO8xfLeosKFUgGoF9RCvLbvU0vF9SE2sSo/jyuH//T14rbWKmaabPpDHNTHrRh7J+bJK7Z/8ESAXTeaOy3EfHlxuIM7ovc7N5whTgvM2Wcp7nf+Siy0eruXEsXkJelldky2GbR7/1iR/4nHHRRWT+eeeJ/6b9uXYqH78pIaqbbPBTYp1Nm+4XtV9uiNHjoz1aO/X6E3N6BwyoXUSMlXkghDCRx/9KloLCGvYJptG6wSBbLDeesWcs85W3HLTzTGmRjfMTMlLLrooih8efcSRUWLHSLaHHngwWj2nnXpqVKhYZsBSxeWXXlY8+cQTMWhPOYJkkB87i4c8D6KqbmwXj2PB0QD7RSC3zYcNi+oYXGMqE/6f/I/Xvnf++ZHwBq64UiC0X8XPIhuqGCP23CsORmFZcYmJNl595VXxbyoXSIXFSdEDuTjHX/z8F9FaYgUOXGnluO1HH300Cj9yIQ0Kds2WW3qZcE4vxqG/yJCqSXUxKcttgfnmLYZuOCT+fd+99xazzjhTsd7gwcXLwYrUkG8bdOLWXXudYsnFF49Tqpod48ePj4Q2dOjQyjMTscsuu0QLrZY6cEbnkAmtCzjogAMjsXDfLr/ssijYaI4lICFWkAWZ1CQeDKSFLJIg4p2BMPxtelLCmFNOjduhFptgAPJss8wcR+VxXU864cRIcIazfPy7SWcZiN3df//9USNss0CurBykSSljv2ABcJMfCK8Dkl1p+RWiy8lC+02F0Ej4fPJxy/g5U6XE2FhaZKyd57CNN4lDfa8O7ue++4yIIo+sQgSJqFmsW262eSTPDdZdP36GC/lEsE642OsE6+/SSy6J7rp9seCq41801hZaYP5i441aFr5hKa71NcFiLEN8jTqu7SDxZsfYsWMjoW233XaTxM+cx3rhhjVPsFw7Ip2e0TYyoXUBjz3ySCQfAobbbr11scA887beXZ995tlIOttvs21rgsBAXuSy1x57xL9pdtUjNPGohNPHnBbft8aqqxXbbb1NJLYdtt0uZlSrM4AmMbGmNg9kRrrH+332xhtuiJLZYnzPlSaVs6S4a4nQjNwzET3Fo8waRXJcym222iqO5nNOtvtksLB+99vfxalMhq0gK8fGajLUZN999okWmOf3G7lvMT6QqmMjUrl9OH7bMh+UG55mmiZUExphyLlmm32ycXrNRmi+D+RdD2PGjGlNCJQhPjhkyJBi5kDauUm9+8iE1gVE2erVVy/ISLNgtttmm1byQhaIAhmkhXZqsLpi0qDyYzb6zQLfdaed49/A5URorJ8EwXiksMduu7daeyynJGedoIREHE98Kk2Gop5L0lrMj7ouCw3pgcQB62iV6HJOJLTVVlk1LMoWQrPQuHTzB7KWDACEJYngWIzYA0Tef/El4nVARmkmp1kFpsdTsaW/xj3lOqf6sj9/9ue4gFl1ZVQTmilS3PX9R+0X9+/x29/+NsbWmoHQJHuQFCvrimBFp++pGgcFSxOhfa+UTAJS6msEK3f2cMPraMlPRn1kQusiTCufdqqpopw2kcQyDAMWR+LSDdlg/Sgtve5a68T4Fbzx+hvRimP9iLdZ5CZMfecb34huWoKMKAlw2zI6b9gmm0Rp68sumfgeQD5mTxrB53XurvosJDr+1ltjhnDxhReJpGLwC3dTgmDpJftHUpFZXbRfvxjjKlsZ3FXzNpWqbDJ0aIxjsUgJK7KyNlx//bg9x7fNVlvGshZxQc+T3W6xQveMi9z18rfkA8VbNXBp/mkZYm5zhvchU3B86wXicgMwf9TjhOOOj27boGC5LjT//F9q7Omiiy6KROUx11xz1SXX4cOHF1/72tci6ZXBsps/nMOywb034T2je8iE1kWYiH5+RZG1LF0NAvasK3LXpjeR3U5kBqySG66/PtZQkdqmIvvC8y8UZ5955iTlCkAvi5Ui/mbOAGL4wdsTq8wTLPwTjjsuFv4iWMkGUt1KOeCxRx6N+9p3xIjinrvvjllKcTlkIzD//UCkV1919STJBqQx4dHHomu56847R3IyYZ5Vctkll4Rj2jUeE+vSXACquo7VOZtZYEpV6k/0GdanbdiWbZbnjCY434suuCAmGxIkRJS62JfPG1IDYpimv9cadTcloG5szjnnjGQ2SyBc/54SrPFqqxNYaF//+tdjtrMMvx2Etnqw+DO6j0xoPQg/7OpsZBksq1o//lrw3ra2BQjI++qhM/srI51H9WfrHZPn6x1H+kw5MN4ReH+tY/iywJo69NBDi//3//5fzFzec889MQ4mY1kNx67W7H/+538mIzRZ6GmDS7399tu3WUjcFbC2kT2r0X6Ui6RuhGa5jo1GJrSMjC6A5bnEEktE5YzzzjsvFiCTBRo0aNBkxITEEZai2meeeabybAtYeSw7WdBGgdV9d7DC991332LuueeOGVT6a/avuNexsCRZvm0lMnojMqFlZHQB48aNi0SEKCSCAFEgEEmLauy3337RQqNUW8aNN94YXdHLSrHTtvDQQw9FN7WeheV1+3JsCy20ULHFFlvE1qrRo0cXu+++e7QivcaylIi49dZbY6KlryATWkZGJyGjvddee0Vi2GyzzWJgH8HUIzQu5xFHHBHfX22hHX/88cV0003XocZ0rVEsQJahAu9qIEey3gsuuGBxzTXXxOlf1VC6s+WWW8Z9Oh4Ep+Wtr+ArQ2iamX//ySfdmp79ox/+KGYNywN2O4zwo/bDTo8vCwYC6zH99UeTKn04Jouy3rGl41bWIZifejctRNckyeFwoW4bH7b/655TEknHUu9YexpctSShzfqBRGjUZ6trBEEMjXta3YDOLURAHalBe+KJJ+I2ZpxxxtiJUcbDDz9crLXWWsWGG25YPPvss5Vna0O3hffZlsc+++xT85h7I/o0ofnB+6IVoypRUD2v+t0C7Apk7VStK3jtLE4/bWwsVzCIV8X9LjvtVFxy0cU177SdgXPkggj4thfotfxV3pv2/nBwTcrgdiiHUM+meb0M2USlGIp+773nnmK2784clUXUnN1w3fWxpGLsaS3XxKR0RcTV228U1LRtPmyzYovw2HTjjWOhrwzolCzdYGVpVeJCnnNOS4cIcOtkO2uR+WGHHRbdvHIDuljXkksuGcmuPSCh1VZbLRIQIj399NMrr7QQLJFIMt5+7x0Bq0yZiW0Z0tJXauD6NKFdeP75sfZqrtnniEWYKtPXWn2N4uILL6q8o3M48/RxsfhVmUJnMXznXeNntSXtstPOxYDwQ1Y0O3znnTskOVQPWq2WX3qZ4sD992+X0EC5hJalatICbVczTDNtsdfuu1eeaanId8yzByK/9+67I3kedsihsbQCkJzzGFO5JvuOGBkJrtb2G4ErLteXOmPsA9XTukb413VdbZWBxU+mUIEtEkME//3f/92atXTtDz744OhyKmGphsSBz2hPS2AVDRgwoDjppJMqz9QG8uFmUrq1DY9jj20RCXBDu/fee6PVZh+dwc0331x85zvfids74YQTOvT7aXb0WUKz0FWvq54nfZO+LI3gZfPa+8456+xibFiQquqrK70fDz/YscEiI5Nz7NFHRwtt7JgxlVeL2BhtqrjnNFLXm5q+x/Dd40J/qjKujFQQi1FRapJe1sytgZ0ckXqvcixG07v6sdODJcRStHg1fas9m37qqaPVd/+998Vzk7nSbqUX1Pu1WlH6AL2eswYL66EHJ7egxFwU+660wgpx2/Dee+/FImAFuwp9dSUgq6Qscs1VV8em+tMq10StmwJawekE21Wf5lhYbu2Vn7SFq664MvaKnlGxUNSt6UCYcbrpiksuvjiGFB4O56a42f7uDt8pUlYHR/HDsafv343E8Tz22GPx/5U32MYpJ54Yrfh6GUBzAZCAYL4hJwk77rhjzCLWKr84++yz42fuumuiwgi3sV+/fm12OigPETdLRJYepLwdn/Nl5Rm4Uq9Uph6ECyQNbE9crS+gzxKaRm4tM/oY6y0g0jwayRdbaKFi6f4DotyPglDkAdddc01c4Bb0CssuV/RfbPFIQInQnnvu2agiQS6HxTXXHHMUxx97XM07XSI0Wl+AKFZcfvm4PcW0T4fntQnZH7d47mBVbrDuulFayF34iMNGx+PTAYAIL734kkBg9xaLLbxwlONxjI5FfI9G2BKLLBq3M2DJJSLBkNz54ovPo8tZj9Asjs2DW2x7yBn0hSIsVhm89eZb4Zr1i/2dzhPx1iK05HIiVm1gi4TPkAyy7TPHjYuvVcP2tGElMq2FRGga5sGi3mmHHeJ3rVD48ccmxK4I595/8Zbvy3eCjEkzcZfTudFz87pC4FdffiV+x66j72Hw2mvXdMO45mJlSEA5RDn2tffee8fMYtK+KyNZaLfffnvlmZa4V//wffqO60HMTVwuEVlyOREneSnJBoQn2N8VCyupgLAs3+kFqiXtoc8SmubnmYNrckZwE2vBj8iit9ieDz8GdUSar7lPN914Y6yetygQhsWpiVoMzOviYbDJRkMjmamm1wmwblgE5HVqVfLrx0RoiPbmm24KbueOYVszxnYmlhi5n9lnniU2ctt3tLymmSYsxmMLEj8Dllgy9o7qq/zNr38TBSQlOqh8fHf66Yvttt66ePH5F6KlQRvt0YcfidvVZsUdcx7iTDoN6hEaiOul/QKCd84C0oB8+803f7FVRQ+uHqEhMpbKWmsMig3sSJZuGUtvkWCV1FrE4nP03tYZtGZdsUOEZn/Dd9k1Xqtjjz6qmHuO2SN5IXPXhbyR75NopTYvRCoJQkZp5hlnKA4LriGwdLmrdwQL9sxxZ0QrTwzwD7//fbC8351M2ihhq0DmSIC2WYqBummaraniv1bnwh133BE/k9xC7xeM10HQFi699NL4OQ8WoX3PEW6c3F3kuUK4iYnP1TvW9uA34pgRZXUGtjeizxIaGecW16Q2oZHSsXD3DAs2QTvSjNNOF9UsLA7upR7GhPPPPS8ubtvUIM66o8d1wvHHx15M/YnkdR4sxUkSEJqFznrwWHrAgKi+odnbnRG56lPkQgEl2/kCOZLj+ehXHxVbb75F3DdCOOuMM1sXEjdquuByWogp6/dxWMxcPFYUzTNWR7/5F4gDbo8cPbpNQnvzjTejBUjT//XXXg+EsHyxViCYdFwIbaGwra2Di9IWoSEVmVBWJYvn5ODGnXLiSXF7ekw1r1djmy22LGYJBON7ExOsBYQm6cBKdM2QFXf7kUownIXHeqP+QWSTxbvQAgtGtw7JacJfdeVVohXuBoUIJTeQKVUPN6idg+tIj64WEJFuAATD1StbcRtttFFsNK/l+pmM7jPHHHNM5ZkiuntiV21BfC0RmrkDJ4breOSRR7bGvlhn5ba6rmDnnXeO23rggQcqz/Re9FlC0z9JedWP/U9/nDwlTaMMoY0IbkICqZ2ZgrWjaZpgoYW6RXBTEhBJIjQ/ZISmcVt/pB5DUjkeb4dFX41koZHS1l8pfpFcYSqtSyy6aJwzkNQqIqEF94ySB1fQMBMa+sjBMe4ZtgeIGaEhksBoLVXpwdKcMyxO1thdd95RDB3SIsbIxWqP0GCbQFZij9RmHbPsZ0JnCE0pB0JbKrhVnneN9t93VHHAqP2Kn747ucqsZIv3k2MSm6sFhDbLjDPFa+G6vfPjd1pDBNzPLTYdFrch3nlnsIo01FMMSVnQg/Y/oFgwkJYe3KUCIR16UIu15magnEVzPbcYEdYavsICVvKAADSUp+8L1g/fn0yk76saLFyfkTgArUg+X61eCynG57uk4rFpIN5dd901fv6SSy6Jvz1kuEq4uZVnW3QW6QZ4dLhWtn11Sbqqt6LPEpp6K9LVCMg0ppdeeDEG0h8JrtAbb7wRhQUXCIt2zWBuc3+4R2Ip3i9wy0Xx+vLhRydlLjhL8tnr44LLiYxIViM0ahZgJJzt1vpBpxharYZsP+D1w8JjSaUgs6A3wj0p3JHFbd6vzBIQg2OhDFxppThzQJDb+5SBWGyykJIhLBHWigVD4QJJdJTQiDCKLYnXsVhS3A86SmgC3q4ZeR8k/Ga45vC3QD6uUSLzMsSeSBvRmytXr1vYyMr3EF1sMbTgLlaD2gcy42ZyG1nZNNgWDC5ymkPA8nJ9VgnWmxtSivX5DUgI2RfLeZqppoqkVw3freJVBLBouAmJzYFz5f4puK11bo7dIJRhw4bFvyUilg/WarV1Ja6mNi2NtNMnqk3pwgsvjGUfKXiv9er99xsj2W0KVSLL3o4+S2hA/sZdmEWDLFhBFpusJpw1blwxb1gA3MYVllsuvkbRATFYrEcdcUSU2Vk8fA6B9F9siWKGqQPJnHBi/LxYm8Xhjr9quFsikR223bZmPGOn7XeIckMsl1oQYxFbsshWWWnFSFrcvl9++Mu4UO0fgVqgSiiOOerI+DmLltvl2EkMiaMZvoJkxAfFo7hm4nPabmQ5p/n2t4OrOrlbnCBhgcimm/o7xbprrT1J1o7lSt4HubtGAvG2l2YHSMLIuiZ1XHJIrD3nxV32fXhPrUxgLXifwDh3Tu3XOuusU3zra1+PmeBqIMT11103hgqQ6DprrhVvauruqKOA70YNm9gZiaMUwLe9/oF8HSPrbNmlBkQpo2o4np3CzQMB6N3kxoLtiGkho1pAloL7Jqa7bty8ZK0lKPcQVyMzxKJDdiuF712h7PXXXx/3SZkj7bNRcCzc2epi3d6IPk1oYMGTfD76yCMjQUnnlxUHHnrggeLYY44pjgiWiwLSdMcFP0Iu4ujDDouTkLiBSLL8Q1d+wYo6PLyHq6rMw3ar8dwzz0bN/+q2mDJefvGl4pSwsLhTF4c7stgZWCykd0YHF/LoI4+KRJoWIogfOT9lCuJnrI3Tx44tjj7qqJiweO7ZZ4rxt9wag9VKRCQl0rZrgRXix+19r7w8ae8hF0sZCEuHy2LWgPela6IMxnkmEUrvMUNAnNE1OuWkk+ICTe5OW2AtcanEpSxmD8FrNW/lQb1lvBOs8NPGnBpczmPCMT4ZLWKuZPl7PSZcFwmAcWMnFqe+EazX9D1K+ogl1gLLMcWcEFqKLSIZMTV9lLW+f/tfKtxgEBKXUdlFuTgWXHPEMn24AZuf4H3fDTcmNyLXwTBipN5eJ0Bn4Hw2DzdACYdarVK9DX2e0DJ6JxAeC2XjjTeOE5Fk8rQbLRcs6a7on3EDufYkwk22Yg13tUxhhx12iITG4ko3KC4lIqrntrHsEAfFC1YY8itnet081w3Wpe2Krflb4Ss31j64oMjc5xqZjXRdJBrEz2qFSnobMqFlNC0ODO6x9iJV8SrsVcuLKdUreG0LssISLLKaEiQXBQu4K2B9OS7EoxYsdQUgR5X8bQXWkbLPKfdQf8a1T2BxLh6OzeusN7Afz7Gi1LtdcMEFxXXXXddhd72jELftyjVtRmRCy2hKUI7gfqm7Qhq3BTfXYi+3DnUGLB6zHYQPlLp0B6cF116AXlIgWVl33nlntCAF++shFdd6kOQuw6yB9BpSRFqSD8o2kgvLmuKGNxKSDY6lrVBIb0ImtIymA2tF8Fz1uhYqrqISBQHyerGzKYk0wWmGGWZoPZ4rr7wyWmhlq6saYl/UaX12/1KdHfc6WX3qy9SscbdtXyV/T8GxmzilqV12vC+gVxKau5dslfqj6ocMZRnubuRsBPxTjEBRp6D7ezVqgHoC+juVUEhGSO9XB8QdswLbX4S7vXPoCHyG1ZG25ZpYBJQevqjcxZ2795RLIMrwuuC9EoD2gvT/CPtTha9jotpKsB3STIan/CXsrz189umn8b21YmG+VzEd8aKUBZTxQwTVWUFwPSUmJCuqz+E/8bh+H/flOrSHzz79rOW4KkXL1eC2KjlJfZmykYL3wB1sa0gKqIVDUqw7emUJEjzI2jY1q/tujzrqqFjiUU5mNBo33HBD3Kfe1L6CXklo2oL0La65+hqx586EIANvtc3svuuulXe14MLvXRBLBR4ouRlqsRTd3nHbxL66ngKi0bWgFKClRmr5SWZvalMauuGGsZjTQylBvSr1BPV0yiZSg7b4zRabbR4/r4zkqCOPjMT4+Refx7ow6h7lUhKEJPsr46iOTnFxrdqpBIvUlKe555gzll+Y/K7mDpCIYTFKX5SaDF5r7djmVA9333lXHJ9njJ7SiptuuLHySkvGjYv1ja9/PT58n5r5JQYE4KutH9X9A8N77Ne2ZKLL8N0rxfD62oPWLJ55un4wXX+nbTku5Tfq6xJcm4svuii2n3ld3y53mDWlrhEMEBbAr76hlqEmkEosEilbXsg2ZXIV5iJnbiCrrdEuZoJ9LLbYYrGNqiwk0NvRKwnt5PCjJxuj7kp9mYWs7cjfqtETWAA6BqoJwoJXh2SCeU/Dj1V1vMr37513XhzAq68SoYBU+SEHHVzcctNNxbHhrmzBkMZhedQCK1MRrXo0Vt3nYbFtV+kMOPOMM2K9mx5WjfeggV0NGhWJBIXF/cJ1U0+mfk0haT0rDiFrI3KNFbPusuNOsbDVtCVQCKsIV0eF81N0SystVbuXIRMoKK/Ql6qIurqFF1gwNryD2ripvv3tmAhQCa8vdkD//nGyksxg+ZogdfNAjQrUo+lGIXPp3ECczLXcbJNNohqK5ng9rX/4/eRWIcJeasn+cZ7qJRdeVKy28iqxX1UhMjz80MPxHDcZunEkyTlmnS32UiKgq666Kr5H98Cq4TdY7zqCmwrtMedXJhFEJx5nexrfxdpkM9PErEYDSbIov/Wtb8VOhBSj6wvo1TE0agOan1lg1GTLcFe97977Yk0XAnM3T1+cmi0V/x0htFdfeTXWVdUjmAR1TPoVq3/QLJiy9aOo00J7tmIteC25SgKzrBJ9is6tFhTmKppFHsAaYvkRsfRDFX+RxdOnCCrzNx06NJJk2uYPAomOGjGiGHvqmNgvitCMoKsFtXcsHJ0BwF1HkPZn27TT/K3mC8ztVNiqHq8aaWjw9wLBgJuNvs4LK8N31193veJrwdWUBZQIoKLxnammirGpai1+zeQKpkkkgRo8f6cOAiMCKWs89mhLkH7HQPS+89TzWcaFYXE7rjQIetzYsfFvXQmgQR/xp66CocE65jYiIEF1GUKERE67LXAfZWrVfJWLWIUi1JfZHrJToCsp0hY5dgdq52RSdS4k0YG+gl5PaNxO7TWpEjzBlHAL252bNYNELr+0ZRBFRwnNHXVQsDbKFk890N1yl6+V/v5dICrKDwpQWRVbBvetXBgrLvPKKy8XZ59xZnAZ54/HV8/VINCo8p5yBeg/1RCf1DFYbSxA5532wTUtt10lYvc3y6stQtMJgKCOqzRVc29db430iFFNl46EdDwtah7fbb3WZSAG+3uw0gTNrUMUhxx4ULQE5w9EZlGnWq69grXt702Cy1kNljgyTMSp2FcLmOvDKnZcWrdSD+exRx0dJ8mLnVaDy+2mQMASbg5kwiLbf9SoSCprB8vfNU9SQYeFm+R/VwhNszlrlPtp6HBb+OEPfxhjaD53ZkX+CLTaIRfPe5D1TtezJ3BxsNbth35bR6S/0w3ZemMBs2jFalNjfnvx1ymJPkloRBcpWmh9kb15JVgZJoP7mxtqcXaE0Cx8VeNUIF6riDCW8Z/wn1Yg3QJIQ+zFEFxEIXieYIjv/IFcuWqIJok8JliE+kZnDFYBWWkEVwviMyaVrx3I5I+VgLouiOnCYkq9lGJn3DrSR3/6Y0vjNLfTAtWjWYbm6/YIjcVDASPF60gZaQ9afeCqxUsvvhTdNFYlIoWzzzwrEtqF57dYXQmuJetUS1UiVsSGSDT0s8BYZ1xOC9/NRIznf4Jrd3CVxA63e4fttovXKwlN2iZC23/ffeMNxPlT20hlFUkpJVldZWyz5VYxxvn4hMfj36SP3AxH7LV3/I05X6GNlCw45+yz43EhBS1ZDz74YAzqJ3e3Ht56661WlYwDwneeQD3Dc1xrfZupj7Mn4BjVwBmSUhabrAXnLkwgacCi8zlFzrOF35Jj5WIjX3HE9jyYKYU+SWisFgvFoiNDY8EKZrOOkJ0WpY66nG2BFbXzjjtFy0zA2I9+uaWXiWKRt958S+VdLfEebqsYF2sRqVm0CbFd6KabY1sT62rjIRtNouKQ4HwHrb56se1WW7VaggQYWWiJ0Fgn5H8QTcqYandiYTjvMjpCaGJGCCoRmju6vlJJmDdeez0u9oErTSQ07/P+6sZud3FuqmuUCE0gXqKBJcRd427NFMiTa6aui6z01wPJiZGVgRxNX+cWJkITJ6U6cmAgCkQuDiZxlAhN/24k2op7W4aYpOuTCE3Dv+uy38iRMWsrXovwEqFpWSoT2rXXXhuPleVDv+z555+vaWFfHr4r7Us+p1RCVlrLlMlRMpopY9pTYEkmOaI03KUWkJPeYhbczME69/62Hm48ZhqUOx++LPRJQuPaITQW2fHHHBvdDYtZDIcaakcttPZgkYp7Cd6StVl+mRY5GHMa//Ln2oJ7p5x0chRklBmsBdI9Fl6t2IYFJfGx9RZbtGbTxAann3qa2KcKXELkPXSDIfFv0AdogSaV14SOEBpXjlt4eEWx9u0334qBf1YNt0N8jpLvjyrXn7XFRX3ogclnChx68MExHndX5bojPcmZcYEgiAyKl80XiIWFqk1omkBQ3P1ajfQHHXBgtMjS7ALqwjMFq+P0MS1KKGSANOWnhMPBgehc1/vuaVGrLYObzILV7wpXBgL1+0i9ngbEuE7KQ0CWXBbWYpa1TOobYn/+RW612qoSmSBucTQqxeJnMrgmr/ck/FZZfiwr06GQT9lVTP9/U1g7FENSjFDygzKvJAXilc3Vw5qsPO/x4DKrHaS592WiTxIaxViLWuzDD8tXpQ4sZRZTDE2Gzt2eW6WCXGN3NcTOWHlpbFs93HP3XcWywTqrjqEpyxDIZy1RmmWlCFaL0wDrSeCdFBDzfvWBA4t5gtVSq4A0LtRg+rOKUlO04+JiyuApa0DaXFuB7QTlKWJorMQyOkJoZIuiUkY4rth+c/750TIShIcjRx8Rg/FaicRUWEWs1VqV55rqvZcYpePfftttoxLGcccdF12xdcJCQ3DbbrNNtGT6LbBAvEmkWE0ZZjz4DvfdZ0Qk+h222zbGSZM776ZlX+efd15UK+EWU/z9qNKqVIY6Re8VS3NcBB7LiQ7bck1ZeYjAtr4b9p0Ws3o0bVAyscogZA+rG8hZnVtvvXV8r8wiUmOlSQBQuu1psBjXXnvtWCunZKTct+k1cTFlIsjYOSErQpasTjdoay2B9+B8JC5YekpYfEbtoHOqpzY8JdCrCc2PL6b+w4IToC6Dbr3FKnZFNsj/c+ngsPAlTP3tqQKh3R1/oFL6U4cFVJ2Z++tf/hrcwxWKb4cvrL3eP6KN3LNyRhPosokbKddYOPzoSf+oS0uFnldfeVU8NvVgguIsS1I89ZICxx9zXFxs5fmOyIVVZD+xvCC4QeUYHit1vrnmbtUkS6CCgRS4b21l1Iyos13uon+5xKmkgOuMYFlx3LIF5p2vuPbqiUWjZShMlQWddabvBisvHOusswXraHRx6KGHxmA5a5O7znphrbHmWEu14PqxElldvv+5wnGxnJKl4UbGVUSYjpvIowRHLVigJNvTcfmM40okzzJL5+gai69tWLHK0kOLlkWPoFhq1STseJEJC8e1o4XmcxQ4zBkoW0s9AXE67qN+0nI4w34lMwYPHtxKSuJ7XE5ICaR6EJOmdEtFxOd9d7aVBv9MafRqQrMIxR0MiKiusPeaEgOunXQ8GaDk43MLLeZPPv4kEscd4Qfl9XLxacKERx+NmTGB5q7AtKX7wkI99+yz40PcqLwfx8ByOTu4g0oxxJdYa/WAlJDTAftNbJ1xrlwvweprg+vFGk1w3BbjFsOGTVb0+cc//ilaaZRf21pQimhNUpI5vj5sv/payMixZFmH5jO0tQh++5vfFjdef33clmJn1hOJHHd6NwOzLalW7BSsJN9fPWIHBCleSknYxKty5hje++l7McbouGyrreMSy/I9OC7fUfW18tsRy5NU8B2xXFItGgUNPaaORzO5AtvqCn+Bc9aPLgjHecstt8ShKsikpxvDNbRzGal5vF8RhXStERvrENGxHLn9yLX6OnYEkg1KUlwP7qeuDpbdlEavJrSvKk46/oRo1cletgckN0dwN5PgYjMBiWoBYtGI3XB7NHhb6M0Ox2vxeiTNMgtYPdm5NeKjEgmIL2nxKVNBsD0t2SMWK8bHgpKsAIQlfpesMu7+2LFju51djcmniqUmG0pQYEojE1ovhLu/MoRrr7q6+FeVi1uGH66snoB5W5bOlwlTwzWhy6yJ8Sh/EKvraResu2CRJUJbc801I0EhBLG05K4lODfS2Yilp6r/a0E4YM8994zkwiIEvwmdCMsss0w89oUXXjgW+VZblF0Bq5ayrrIO23ajmpIT7SETWsaXBmULYkksMg/V9kQNkUOzg0XGNbZwZQ1BUF1tVjUZc0W5m+11EjQSrEUTpbiSSRnXdXUDkZnlFmqzarR6iZuRoS6ui+SIUEKKF08JZELL+NIg9iYZ4CH2JBhdzqY1M7hXSQpIQkCMjRVmpkC1G6nzAVlz86aE5SlQrx4OoZApEmNFqmrdlGNwkVlpyf1tNLTfpQJicbVafb09hUxoGV8KLGyxJlk1i4xlU6t2q1nBQnPsFq0yDJal/2elQZm41HVpSq+VdGo07ENgH2kpE1ErSADB/E7Hx72XoKhVuN0oSLAgd98rd7faBe9JZELr4+B6dNXkl22lXdYRq8J77EdWt6NgPVhkiKGrSrRfFpBEqtlShyXg7/+5cqrm77vvvujOSXooZdDE3tOQLaWYK44nrucYXdeBAwfGY3PTaLSLWQ9uVvbpMW5c7WHfPYE+S2gffPCLWAahH0/B5A3XXT9ZYPy1cJclq6PHrhralQwU1gSteNPQ2t4Gpr72r+qWp47GqC677LLYatVWGUkCy0DRr2HBHcGbb75Z9OvXL/7glQ7oGrg8uElkidT8/exnE7XP1BsqvTBcWdkE9ylBkJs0k+Jg9XvicmUoc1E0PWKffVoKqdtJjljwBivbl33WK2EwqCQpZKRHUtLw/wpTUzmE9+n37EmkEiZDZByHQD+3099cY8mBVLIxJTBhwoSYsVbaooF/Srja0CcJTUP6umuvHfsm/Zj323dUMTL8oMndJFjU22+zTfGdb32r2HHb7SrPtkCRrILdVVdeJbYUmSM5+tCW1p/ehM//+c8oJpmmaztnEkf12q6qoVVK0Sq12vbAOiPceMRhh1eeqQ81ULJh3BGxlpNPPikWBtO0Mz1eh0fSsPOdGQA9MGzbsSu83WfPvYp//buFmLS16ZRA2muusUax8ZAhrUq4b7/1drHsgKVi5b95pAp/6c7VwzPPPB23v9kmm8baxX1HjqyrasxtS+1BHuJTfndqImVrk6qGh6nnPQnlH7KJ6sxkGPWWarNCbFxP8wo6oqrRSIiFyqA6f9p2PV1rl9AnCU1FuIWopSjBHax8l9BYrRF8k6FD47/lWZt+zMQCSWInWIT17jKsk5dferl45qmnJxkC60tkTaSCTp+32KqLNstADBqun3v2uUkKWOmDKegUjC5/XiO2/ficCe7Oo1xAysJIVobz0VjO6vzzZ5+1djW0HP9Lkx2/GrbFFlmk7o/x88+/iNfRZ7U6qcw/UoV9ZbvOlxiAyetiOQmuQSobECzXoaED4a1AQMCSTteaesm8c84VC3ZBCYpeUh0YrGhtVoqiQZM/ocs7KvVPWta0U7letklfbYN116t5Pq7RBuutV2y52eatrzuGet85YUdBd+fAAipbYM71oIMOil0AylDcUNoq6u0OHJ+uhG233Ta2i1HrkFxBZixEQpKJ4KckeAfG8bk+1HinVOa6TxKaim9yPONLihfVoB9G7VTHwJKLLlaMCT+EBJ0B7ub1ppyXoa4IKZLRXnuNQcHFW63Vurjt1lvDglozkEQLMalH2mjDDeq24JCI3iDcZVX2rxlcPVYljA/bMUV9ow2HRKUOFougrh/zDttuH6yPgwJJ7RU1yohdanVKmbZ9gst9zNFHR8LjlmkDog6yyUZDY5aLO+f/0/GvEY4/9UO2RWhI8KAD9o8WENlwZEHlY7NgqZwTXDV3aD2yrK71Bw+OPbcEN0GMiSvGwjGFnCuItBCj7ZZJhEw4ee1kXUscaCPTIXDn7XfEljE9sKBbhGyQodHAyj42nHsCYUnXp7o2yndI1n2eOecIVvu2sVuA+KSe4HrQwmSxejgX7T9lIEj7EcPsycXsBjRq1Kh4HLsHT4I1aKAMQhND+7LqD/1m0kBmZS1TKtPZJwkNcey4/fbhBzpXbISu7vNEBiutsELrD596xeqrDIwDNeDXv/4oLnCkpvm6rfS2xujbb7s9Lrhf/eqXMWZFMQPooOn7Sw3R9msB6jOthrv6issuF6WsHa8ygEQs3JjXXn0t3uXvuvPO2MBNBQNWX3W1KIukXeejj34diVmTNqKGoYEEd9t1eLSaPKc3dYdwN9cKhADcvTWvx+MPi0+TO3kiaIvQLrvkknh9rrv2umidmWae1GWpM1CBXaTfQsUjwUJgHY8aMTLq+h8dCEaJRpKcViN1+/jxsfMBkVNIMW4OAYNYljkF6RjowNGdcw21ktH3TxOLEIc+1t122TWqqujhRU4J1DRY4yy5MpAC8UnflanqPiMWWP27SfA9yhpqME+KEwaOTGk4DrVt9s8KMnuBFLg6sCkZL6uHpPMmGVGOe/Yk+mxSwJ3+/HPPiaqlLIdEAHDrLbfEYSLcGTAAQwzngQcmZtpMMTK7gDTOMv0HBGttcknpBNYIkcdbb745WljkrkFjtf2kRnHuIWUQfZvV0INpQb1Zo/0EkZn4/dgjjxYXfO/8qN2VpKfXCIS274gR8f/BPpDmGRXS3HTjTWIMEBA9cjikSjCxfPzrDw7HH6xDqEdorD9ijUmW290XUaWAuMfAQE5ianpFCUGedMKJxcwzzRS1s5CBhAPZHPVQXCaiio899mhsMNcEfkFFIBI5lQnN9yo2yvrzYHGlGwbi5DLuMXy32M+K0MrX2oAWv4WkoZZgsbmGZhiwCAlhUul4553aVe7cfllNyYx1gnXqfNWfJVd7SgDhnx8sTvsWi3STEMejXJJ6lr9MsLKvCJ6IpIDvPFtoDcKHH3wYXTeL3F0LOVCXmHv22aMVZlFKIFBt2Gv3yWVcBIW33nKrYtWwQMsKFgm0uijIGsZh2Mn6gdC4izAZoYUvlUVRi9BYBAOCpVWO24FFcuzRx0TiIkRIKcRgkURoLMKyW8VKWSa4gawcqCY0FhAXNUFTd8vxb9py/NzDcLeHeoTGsnOOe4cF7YdL+cOCSmTmsXBwC5HHtlttHVUxVllp5RigZplxxfQVKnFQM1WG89106MbRjQdJHTeIFDdEVJIA1197bXzYRxKXdJy+S5+REGHJlWWUJEiWW2rpyeZPsI4PPfiQqO4hgcDKJRlUrU6SIF7GOlOOcNppp8XznZJxItfCMGLHkK63WJ16r3Ks8suGUIA4nlhattAaCMFyMjliW6RgxJHIxSgBOOP0M+KDAmuMr/xo8ruymZ5kcapluFkEKX6UYhVcF5pmIFZmX+mO6V8uT9kNSqDvNe+cc4ZjndQdejpYOCYQja/04slW2WbZQhuxd0usDbhJ8841d+t4uEkI7dNPo9uXLDTHjwAs4hSI33348Bj3gjYttOAaI3FIMRwxsVSbNcsss0QLzXuRljgKUUDV8kAvzPs0eZfhOCiDbLfNNvHvq6+8slgwXHvuMLBSF1to4eKF556PSRLxtBTrdPNaMFyr64MbDIjRTSBh9GGHx/NP7mwZFtySiy4etfLaA7kjpRiC/WJnMrVqv6ZElwPSpObLtU9ZVseiCb1eicmXBao22sNkfdtKhDUSfZLQKNFSpHgw/NjuufvuOAHJ3dqPlmIsscNXX550ipCxaiSc1a4R/DvtlFOLh8Od2P8L7K8XLBdxmTJYEzGYHiwcZEcWh5sjFgQWr7s+RVSketD+B0QF1mrlWBDHYW0hVlJATz35RFyYMoT95l8gBq2Vkxx2yKFR4/+8c1pKLyxQQX66aq+++kosRVlx+eVb67E22mDDqL8GfvCOd/11BgdCeC5aO8ocZAId/w2BVJcIBJYImWQ4/a9aP0a1YoQouWjkciysb37jG9Ei4/ZwNWafZdZYrU66RqW8vr5E/ApPZQnFnq74/hVRspzb61qRR0ozU52H2CIrW6ZTAsOMUAvb+Wy80Uax/u2F55+LiRHXXkYYyJoj/2uDNeN7XHyRReMMhnpgmSFPSaE3Xn8jJh4E9ashqcHa9J3ZF0IXN+xpCW03B/VlLFtupvgdMiVlxPpuNrBkHatZoylJ1dPok4Sm5IE09LLBvfDYOVhQLwbLh0Wi+PK4Y46NsZgyxKgU0HIHSe1sMHjdmMGjmMrCqed+KDngprFGjguuH3WLo45ouctze5SA2MagYEmx2OiYIdlaeCdYh9xhLqM4EWFFpHnm6eOKFcKiHrL+hpG4uIySACB7KHAuBuRzCKo8hGVMIGbCkylzKPOqvs6De6vvDlnH4w9ultjVURUhTMc5auTkvYnA7TzpxBOjm5xiZ6sFy84kJxaZUoZvBStCBnC68P9LBNdQoiBBRbtFKYbm+Fwjx29otEJZ31WCZIb6NLFMbm6Swga1ZkIC6seED5RzJCC9c4IVLputXMV36zupB6RgNsNK4f1uIqsGYuc2lUsuZESVY2jtSRYR0vO+nrSQXA/FvIhUwapjIBg5cuTIKLvUjOAW+10YsFJt5fcU+qzL6cf858/+HB9pcVjUCKJeTdC///XvqFLqfb6A+PngnrSX+mbBpPf57L++mPh+f5svkH7sXqu3f3Cs9uszqard++M2/vq3lu1X9vPF519Eq44Sr78dQ/UPx3udV4L3ISPb8/9Q7/j/8+9Jz6UajktcUhaL+6Ncw3Mp86alSXsTt4z6b9ofsLwQmnot+3U8zruea5K+j1pS4QjXa7WI1z7dvJxzef/1gPB0KyxcKQpVClH+HKuMiyeDV0ZHtt1V+E3Q6teH6TE03KzFzBTSNnPL2BnBwncNiT1OKXwlYmh9FX7oKy63QkwUfJnQ2uKHS95ZZiu5oO7Q6txqQfDa4uSSNhNcU7plLCF6XixMiq8JtwYL19wABas9SWIJbsDasbjsjkeje3Ljy7M9mxFJRujYyszYKYFMaL0YLJsTgjV0843123l6GhY1IUFFlBZ6ynbSOWsr4ybju35wI2U9mykzd3dws1XcU1tNA3lZkQlnnXVWDHRPiWNGZtxJWUJkhhhIlC+44ILF8OHDK+9qTvCQJIJY6eKlUwqZ0Ho5EMqUsBTagyJPmUtN0EhgyJCJY/TqwVQhiQHxp2bBBRdcEGvMlKIgNedCVpqLzHU1h1PcqqdjQm5WyIzOv1gZd978AZYZC5gL3cxgVcp4UyJ5qjKHdUqg4YQmhuLOIv6SIPj8s/d6RkyuDPv2Q6iHeFx1Fn9bsbVq2Ee9/aTzr4e2jqEa9lHvmNo6Btvv6H7ae29H9lNGipsoOnWXTmj9XVT241+uqloqrqnXOnr9ewqOQUsTC42Cbuo3ZZGJYSE05RlJATahre+p1jUqo9Zn/U38kutLXZYE0b333tvafF4eUt2soKbiZmVWZ61McU+hYYTmjqHafbddd41V5CP33qe1pmuXnXaOjb+16n86Cq05bf0wHn/88WL3sO9tttqquOrKKyd5r/oghavqmw4+8ICY0UzwI1WysdXmmxf7BOtCVXs9+PHdefvtxU7bb1/sGH74Ks/LP0ZlGnvutlvMtml7+vzziUFqLUYG6m652WbFAfuNiiUY9SCOowhUC5Ks5+MTJvaU2t+9wS3aZccdY4nG7eNvm4RwFJnKVjrXo0Yf0abKgmyhIlT1ZLK/5bIU1++G668vttt667ivRx5+qPJKC1gPBgf77JhTTo4tSaA5Gglw1xKUhIwKVo1zV/uXMswynTKkawQrxGtUNDT5NwLq1JxT6qst46477ihOOfHEqN7hO1EmIymhY2GvioWpzisJOHqwkChYILlUFoKwTYLym/O7f/qpidllIEt1wH77xe/izDPGTfL7l/zQkaBNzm8mNd9LHgkjLL7YYpFYzS41WZ4MEGuHkGS9xEkzQaxR6Y44Wr0bYk+gYYR26sknRxUECgd0pPyAU2uR3rknH3+irhXQHpQo+OLrjZLzY1D/dciBB8bjUEuUGsARgLILaXs/IK092pOSAoH364VUn7TT9jvE0oByWUAZ2qcWXrBfceLxJ8R6Kft55KGH42sUTLVJ+fEpt4j1TIEoE/Qyaiynv6Y2bPBaa8WMWS0obzD1W7/i3nvsWSy1xBKx3QaMxNMjqXtA36GCX/MsQdmB6zR4zbXjuSrNQEi13CMuoqJgE8Zl9ZZfepmowpEI2lg63RVmfioJ6R8WmFo6+Ph3H8dOgS3DTcD5LL1k/7hwLXDTtVldV4abCui0WDXcpXfeYafivHPPLRZfeJFINIAULVo9oIjFTUKpTHf7EB2HXt5pw3aVe7hBlKG5X5uZazM0uMaUWZZbdtmoPJsITNbWsaW/FYfusMMOUW471XwpySFs4F+EtuyAAa2qLQZM+74VXfttOe9jw/eVoPdVx4O14ne3wjLLRvUQlo1WIWS65qBB0TiYZ6654zGsv+56rX2rzQ5dC1z16qb9nkZDCM3ioHKgdaYW3JlMJbdY/LjcCd2lX3/t9UkULfwYNCqXBRdZfpQxyPkgrmQJlIGwDL+1faTJUltv7XWilfH8s4HsAjncXwlMWpQG9SJJjeUqzYkLws/DQkKMimqroVzA4mBFxL/DtrU57bDNtvHv/UbuG+vRUumAQtA1V1s9Li61UX74qVj09UBOhuzqKa0GkkO+RAbBMapJQ16gSHjXYPFy6Z2rQtMtw48eHn7oodiYnmqxiFIqLH28Rh8qK9Yk8aQ8QZbHkGN/W7C6BfRVwqd/+lPUI0stU5dcdHG8CbxfadpPjepiYXobZQjTdlnGfht6Y4FumXYlRb1cp28Ht+R/wp1cnIUIQCTRMS1T2buKtwMp+L3oBnH+5bo8QD6uY7J0hoe/EYjAu2NHyINWHxQ7ARBzGobiPTwB0D+qvm3smDHxbzdbnSZ6VkHLFZUQc0jT336Hvl+zSL3GWgVdEAjvsEMPja6uGB69NccnpmffEi6KrHsLuJnOod5Nu6fQEEL7ayAnxZmq0H1Z1VAZT/VBpb7gquZn7h03dIdwV4azzzwr3sk3D+b5SsG8/l5FhFAhqR+KH6aF7o5WBsJgXZx8UssPCZJMjFYjLoEG9VQ5n9QaWGYTHn0s9kWmdiM/oM3DD52ZX42fvPuTaD1YzAnHBaJVEPrpp3+K1tDRpTvw5cHldAcWC9E6hdDeq1h+CH7FcI6svGq88cbrxdyzzxHdoATWhuuiB1HRZ1oI4E5PE4yrMubkU8JCWSa6T8DSQdAXXTC5/PO+wWLcMBB0coMMijXZnQDi++//LB4DWZ8ELVG+L3VaCnlV56faOha4nlWtUlRoBbG5ur4bfZwkeRKQruZzpPvow4/EoluuCX0x27Nd59sdnBhuBr4Xx+VmUN2Mj9DKx79LcOsdg4Z02Vmu3V677xlfA2KUSEU9lZs3vPjiC7FT4vHHJ94sttpii2i1FsV/YjcD6yxZh488/HAkWS6wm6r2tOeeeza+BizeRQOZq6xHBMAlR67c8rPDte1tmJKuZkLDXM5Hwo+TkoQ7j17Fcne9uxYyUpPkLuwOrSKcXhOSc9dbcrFFozQOXHLhRdENYMmZF3jUkUfGz1gAv/5o0nS5mJH+yLIKqzYad3qxG8S1QiCP1GfHMqQtdtABBxTXXn1N/Gy5C8DCVW1fHad4/rnnozV3U0kmRlcA4qTesHRVI7T4mrsusqQK4fU0k5ELGGV9dplcyZQlSewwxVTg8EMOjS1OTwS3nVV11RUt7hwgbMflRiJuSe016frr3bSgxYrKYG2K81l8yaLkZqvUV7VPWgjplONPlGHpi/3m17+JpM89THFK8UDXAaGLPQmss5aJSFargbjW2sEs8KuuuKKYZeaZI1mQvfHd7BbcwU2GDu2QSm4tCCW4uaTaPC67G1pqYAcWvJYpclHv/+z9YsYZZiimn266aDGq8eJuLtV/QLjhjA6/kwNjLJG1JjGQQESybA3DAaP2i83/n3z8STE4uKis9BRmERv0Gxa28ODyJnki4YQBwW1HXMpGgDv+3ZlmiseydUXOKaN9NIzQgDrpiL32iq6L5uVUq3PySScXqw0cGIPO3BQkIhCfQC1iycUWL6656prinrvvCQRwZvHd8CNL7T1665YKP8rf1hjSmgitbLlx7VhHb7z+enEKQgsuTwp4Sy5stMEGMaDNzdLoXCY0rTU0tVgXZbirLhrey9pK4GpZyH7UFo14UwIVC8fw8osvtRBaeJ2bBbYtmJ6axstIhKavMYEMuBvAU088GS29FB8EfYoIzbW2gNZaY1Cr5eFcnXtS3khIhOY7+mflPH/+/s9je5XWJ61GCC1pqgFXUZ8kFwqhsawToVl8VCx2CJYVckp1W6r3KWWM3Gciof0okAZCE2qgNMtVnX666WPjupuOAPmmG2882fXnBrMAXYsjDjuseL50fcq44/bbozWffjvIiDSU5v+EfcJvlP4aq2jJ8B2xgjYP1wKScGO/YLmzFFldWrGqkQhN7DSBJehmyb2uJrTXX30t/Fb6F3fdcWcroQmxIErdFLom3HhdUzf5FSvFySzejI6joYQGzEwLj7V29BEt7SGnnHTKJIQWLZ0bW9QgALmwyOhYkfBxV/V48YUW3aoLKi5kLfkeixZZCConcPdYJsgOGS671FKt5MriWyVYi+PGnl48eP8DgQwXKl6pNBVzDwSKuQrVsBC5qlde8f3KM0WMn3AdWUICwGVLSE+j/SpXoRiB3JKVIC5IrpqSbDVeeemlSGhlMkF8MmksWgR18YUTeyKJHLo2LC0uMEs41SixZn0Pho9UY6+wTZZQsuZ++IMfFIuGG8PmwWrjajoG7mGCJA+r5p//989i1512igs9kQ7xSb2aG4YbhUV4TyVJwRLdfNNhxfBddo5/w7NPPxO3bTFTsO23wPzRRWWdaFTnopYVMhK4xhddcEFx4gknFMcfd1xw+SbVNAO/PdaX7YsBugmsFqy1OWaZJYp4BnaJ70tJIplkirniZqmxnOKrc1g3EBMgmJQoKePZp5+OhEZ8M4FqyXbBvdZqJtnC2k9uF2sXeT77zLMxpodQxeeUtwwIvyt9ozLaPAPH5Bg0npctwIz20RBCcxeq/tItliQBQ864LUI7c9wZ0VWVGaoFChgWbbJwqiEovkNp0AmVWvEex/XQA0hr4dbAsIU09xxzxsUqxiZLeHPlWH71y1/FbNMZgeyqYUGxNg4/tGVYih8qC0dJA0gOEBdMP2AuDxWOf4UF8cSECdES5DIDS3becIdmTVRD7EnD9zlntcRM/vrXv0QtNkkCBLLuOuvETGqC+NS2gQTglptvjgtFtgycI7f3qRqlC2cHK1hMMEkbORZul4X02KOPxWzv2Epwnvu3VnBl07lTpUCsSViRysgCwSrSXygG9HpJpJJkD/WOZDWyVt0YBIvFFFlo3E37PTRcMzeis8LvoStwXckHIZKbb7o5qpWY9kXrTYwPmSq5KCcFVN5r9k6lGOJkjkUpSVtwo2Itu2GCm5okATEAGH3oYfG8UxILGYt1SvK8+867wUKbp1g2nCslCu1imut5JkpDENn/BquRSGd1hjajbTSE0ARKWVRiZ2JMLC7qn5dfell83WJkwcQYmh/xPPNM4gIk64c09KMPP1zcW3E7U3r8umuvjW6KxVAtnwx333V3dDOoKbRIP/eLnwEN3ciVmylG58ctRsZSA/EdstQUIrgIKyyzXGsCoRq2vVBwRS4L58U6W2TBhYrHJ7RYUoL4jmFccDuVTCDtKy5vseZYKuJVyiRkHlk3Ske4FrXAcmN1kq9xLZdbeqnirTffjK8pp7A4L7rwong9HMNDD7RYUqSwuVGsOfuhdbbT9jvWbNoWn1w23ERYanfcfkeM8ZlURMdMtpLMEquSiCKpcseT3Kv3fvpe0T9YfqPCtSPL47vdI2yHnA1SKxdSmhNgO4cHN5H7Z+GOOaUlMwhGDCJDJDIbFYngln3wQdcmFLGQSUO9VLHsE2STbX/11VaPQoxuCkPC78HNY+lwDbYPrmW6EZ0QLEDvnX3W2aL7yxrdf99RNW+2spLLBSv85ptuimUrSD7VF775Rkum1U3Azdv1S+Uq6hWRqISIwcSugfik6UwLhd+NBMXMwWrcbuttosUprkgxxvedCa5tNITQLBjaWRuut34csuHuZyGkhSSeJGAu6CtOooaqPJEJpKS3D1YWORzkgzxSjMZC3T9YXSRuLr34kvhcGd4nHsPFUFph3+kHCu6IMnOUKQ4I1o3yjAQk627KNWHyc5/qgYXEchKg51I4r/9ULFP7Yw201LmtN1lxLxIQu3EMZIrKxb3VkFChfzYoLED6YoQME/ygueCCz0pV7g4kXbaO6XjtvP0O0eWSRW2rbon7w8UTuN82WNPKEnasWJxuJkjNMXDXyCSVoa6QRer104LFdmNYtOq2KEFU47577i02Ccfqup1/7nkxTJDAUttlx52KbwSXUyN4OT7YGYgLSmiwav5SydwmcKfXCtcLUXlsv9328ffl2iBwOm0JqdNh3cGDY0zM+DtlQ8mCK8MNSTmNa+BmXE7kAD2+YRtvEuOa55x5VgwFEGLUlM8qHRbWiWuPrPx+FaFKAiwZbhZqAt3M0kN9p3rB8m8qY3I0NIaWXM8UCO0s2vt8rVhGGT5X77Np2/XQ3rbLaOsYu3MM1WhrP+0dQ0f3471uPHovLeQTg5VT3m5Hz5Wr5PMsnPLNJKH83mqwYFlOPi9+lDoJGgWab2nknEdS+LglWG5qzB4OXgE4PplMWmfKWDqKjlwjN0PijKxYccrUsO2zLFqk6thWDJaaco2MrqHhSYGM3of3g8WqpUczMdnkzgIhkbWxIPUcdhasjjQhSIC8kVLWLM1BgwbFbXPl/CuTCYpWxavUCiYgmHqSR10Fi1uihAWLzFJxLriZmHDuuLj83//+xKRTRueRCS0jWg7cPQHqrrTWIA0yQKrZy10enQFXTKZTCUVZf6w7YCmywhC18getS4gjTTLn9hnQm4qLewLIUfZWWQYyq5bp1iGBVB0XPbmM7iETWkYcVGJBGf7RFbBwTPehXNtVKLhWi+Y4jMRrBLh5SIxlxMUzOg9pUrFA3BICspw9BbFfViC3VnysWs5bUoIckHMmS5SSYBldRya0jDhT0qKiKNEVSAj4vDhQqk3rChTk2o5G8JSF7g6UQ9ieuBS3Gqn5m4S2obymi9cK9jcCyExcEZkhK5nzcmxRgkCszvEgck3pZbLL6BoyoWW0Vsdzz7qCNPCWtE13QBeN6yuW9M4771Se7TyIC4pL0RJzXKkPkgKE7XtO2QT12Z5wN2U/kTOrlYIHt7NMVmKGyM55Og43hFQMndE9ZEL7ikPsKqlJkEymlX/XXXe1qaNWBouMtaPavrvKpILn3ED9oOJ6XcElJKLWXz+ej4cuBNOSgIS158SzjKJLYgGNBII0WAWZIrNyT3OC60vfzHlyeXuLJFBvQCa0ryhUycu2DRw4MKpLWOhzzjlnlNDxt8B5uUC2HmTpZBEF3btrZSjXSNYiC6azYCGussoqccSbAlXbocefilFJ86jz4uolfblGIsXsJEfE6WqVn+h7Vcjr2BBvueE9o/vIhPYVhHjNqaeeGgPk3CKLiyXDYmEZjRgxIj5HIrs9cO+QYFLL6C4IAjouswnaQ7n2yzkhCgTGXeVOOof99tsvunhiaIQTWUYTqoqEGwHEjiiRmTmUtcgd4Y0ZMyYel2uWel4zGodMaF8xUHfgbqnJ4mLSxzeDEiEl90jjNyvHNPD2Fr8CVFZPR8ivI7A97pr9a8+CaqKUrURejl3dm0LUww8/PJY/kH4GcTPEofIfEK8KfYNGGg3kNWzYsNh1oGi3XkLDDE1k7bh6o75Zb0AmtK8QkIVK/KjIGtxE2lv6cLma3LEy0gi3cePGVZ6pDYoRCO3ckh5ddyATiKwE7xGAzKsuhtTwTlMulTp4OBdWpmPgJqdM4oUXXhjLNdJxOT+j9hoJgX43ASUZMqduFLKbtaC0JY34875a3RQZ3UcmtK8IuFwHHHBADESzfmQUQUbO39UuHovG/EcDbpOlVAtHHXVUjLl1plWoPahDs/CnnXba+C+yMFIOlFmQqGZdpoHGHo6hTKqKc5Gd83SOCO3Oqr7X7sB2BPMVy7IMZTXrlYAQnUxxMy1eFE7qtUpldA+Z0L4CYIWdd955sUyANTZ27NhWC0E2E2lx2aohwM1SSlnCaohNaWZHOI2crclylIlMREWeO0EngmC6f5WLpISGc0tzDEAJCvcOiXM7xc8alU1ERlrEdBmwAo8//vi6pC9u5tpzR43AY3V2p1Yvo21kQuvjQDqas2UhLX4B/6RNBvomkQFLqwyLlpwNsqARVsuiECtChjKlaYpWI0CmiCVp3wbtlmNoLEEZRPtW34WovM+8ynIfqlmW3FCxQv9yQRsFGVJkpuH9zDPPrEtmrLjnn38+Zl5ZcRIxjbxOGZMjE1ofhxiPSUwWvbhZdeM3ElDcWavdiMa+hShGVAtcLAkFA3AbCRlLVp9jduxlOH61W2JVWoUMsvU+7md5DoQp7pQtvCbhUd1D2VVIkshmujko3m3L6kO6w4cPj8fgM11p/M/oHDKh9XEcccQRcUEhiFo1Ty+99FKMVaXgf9kSE+sRR+Mq1apJU0jLuuPWNTLILYvJlXPcu+yyyyQumuMrF6smyWzCkuX4mGOXLWXhNUrBQpmFNia6cddee21dgc4ErqZjY8USdczoeWRC68MQBJ+vogaLJGqRjkJPbpmJ59VAJKwbcbRahagWqW030p1jZWmSt10Phbbc5npgrXkfty6NmAPnKq6nTKURULSrx1RcTjN/2W2vBR0YLF+JiTR0OaPnkQmtj4JFtc8++8TFLnBfr82He4ewCDPWgliRbdRqa2pUD2cZ3DTxPJOQzCeQzewIoYnj9VQ/pHgcvTjWqHOtFU8sg2vJknNczqO992c0DpnQ+iiosApaKyZtS19MwoAVoe6sFmjeW5j6D6vBkmKxNLonEoFx58Tn9EO2ZQ0lpRCKGo0qySiDu6rAmNudSkfaAndY8J/LLP5HFikT2pRDJrQ+CA3SFriFLgbVFsTQZAHpdtVCqrgnUlgG8hDwFqeyaBsNrid9tTXXXHOSmFk1koUmOVB2ObsLLqtGd+Uj4nPc9/aAiPXHpunxVDS0RGVMOWRC62NANEoJWAjzzz9/65i6ehAbY8nViqHBaaedVtNCI7stsyjo3lOlCLKrLKN6rURQ1lBri/g6A/sTF0T0+jKT/n97YFUmpQ/dALlEY8ojE1ofg4HKFiFXELG11zCuaFbWrp7LmZqpq8seWFA6DBBaWzGu7kCpA7ezXjaRFaXDwfGx5pBsd6EURceBbdp2Z7KTyVp0zN3Rc8voOjKh9TGoqreoqLGmOZptQRbQ+8vV+JDiPiw0Ra5pMlICN1MGVX9kT7hVJH8QMyuwrfIIxb+ytILw3U0K6LfURSFJctxxx8UMcEfBvTS7gFXXkVhbRs8gE1ofguA8iwlBsc46AqQne0dupxaSBVQdQ5PJa8tVbQSQJWunLZdTJT4S6Yp+Whl6VwlAigmy0MpFuu2B9ZqKl1lpPTl0JaNtZELrI2BRkdJRHY/U2oudJSRCq5cUoM5hoSqlKBOLRcwi6eocgo6A8qvC3rbG2rHKdAV0R7BRXyjdNFZtZ+WFqH8gQladOB6CzfjykAmtD0ERLPLRHdBRN1BvJJet2uUEcaCk/KrVZ/z48ZVXWspCyG5Xu6KNgngYq0dsrCebubV3qdOTJe0smbnGms01nns0SkIpo+vIhNZHgGxYZxRTOyKdncA6oSdWq9qfcCKpHjM3EZvMaSqi1UYltqaOrScg0aD31KzQngIX3TwExbtd6XbQxykxgvApk2QVjS8fmdD6AGT7uIQWFhXXzmQd33777VjeUR1Dsw0ulG2yXC6//PIoPaRZ/frrr4+uFRnpntLEp6TBdR46dGiPEAXSV+M2ePDgLqvYJnecq5oHnTQHMqH1AdABE88S0O6sC0j4UXN6kqpOUFDredtMMaw0NcmUKPVWFFh7KgAuNsWlHTVqVOWZxoFSh95PLi3FjK5A7FBrFguWJZvRHMiE1svBekm1Yl2RmKblxeUsZwmVLyAvUteskFSwighS4aggOFf0d7/7XXyt0UDSXNxawpPdAXJW+c/6Y3V2BQbJ6B2VXZVNbisLmzFlkQmtl0PwXKyJNfPII490um9QPRlL67DDDqs8U8T2nSOPPDJutzxTwLZT8agHC6eR7UZl6KFEGOVERHfBjdUStvzyy8ftd6Ug2A2AXJLzJ6vNZc9oHmRC6+WQnZSltFB1CXQWFrnSiL322iv+zYKhakv+hrunFKQMMbM0+k5msKcULhS4yqx2pDi4PWgHS24m8nbNutJVIKupHk8XhrhZI8k2ozHIhNaLoa0pWQsEB7sChKTin0wQiKmJK9keAqjuR9QaJBlgnwMGDOgRd0tcTnbTDM2O1tPVg4SJY2ZtSn6QAurq/FD6ajTOuNvmCGQ0HzKh9WIgH64ma6GrhaXairQXqWEDrph4GkFIahPVkjziaSS3EZrG8Z7IcrISqbwqqegOHDsX0bkhItnZrhIwCaPUDeC4EGVG8yETWi+F+I+2IwtM4L6roMsvwJ00+QXKuVLqqqrdzQTDdO2Xq6uHsdGwTRlWlmJXtcR8Tnxwiy22iFlZmnBdjffZluSEJn5WXk/IJWU0BpnQeik0b2vItli1/nQHXEsZS+SGrFS9EymsBxprCM0Cp1rbaCgh0SfancEmGst1ACirEDNrq32qPSgmNl2KNtodd9yRNc6aGJnQeikM7FCp3904E9eJC6neTHGoTGm9RnVgraQiXg+k0cjCVy4tchXT60yDeBlKPvbYY48YvOc2d6e0xLYcC2tUS1m9YcIZzYFMaL0QrDNZQISiALarQE6yfdwyi19GsTpmVgtKOhKhqeeqR2jcYq/51zG3lxF1PFqpdCSog+sKEJDsLAIydakrmd8EhKrzwnnqmuiuJZzR88iE1gshC8iK4RqqGesuttlmm7hoO9plQI3VWDxxLuUiYkoSFAgRwUoqqFcbNmxYDMgjTLMB1lhjjRjva0tySNZWAF+nQGeBzA455JB4Loiou9aU6yGjKfGSJzf1DmRC64W49dZbY4wJQbBquos0DLej8yv33nvvYquttooiiD632WabRZcVEXGBZV0NFjGghVvM+jOIxXu1Cyls/fDDDytbmwhFquJ5LKzOZiN1NyRXmHXXmQb9WvjFL37ROpXd5PiM3oFMaL0QqvpV0bMaukNoPuuhkNbCNeGpPajh4mayXpR2+JyHoSASBGJy4mAKdpECC1KRrpIJhEnyu54S7AMPPBCD+HfffXflmY6BhXjiiSdGN9M5dLd2TXJEltd5cTWzYGPvQSa0XgbFnWq0SAU1KqbDArF4O1L+Ia6k6FUiQWFtIjTZ0e5ALI/lpp1IvK2jUGdGJpxrKBHQ3ZF69i32phvC9CZ1dh2JK2Y0BzKh9TIY2sGKkXlrVHGnqnek1JFRcDoIvFf8jrSPBnLW4sknn9xla9Hnbrnllrh/VlxHtyPgnyZcIdTuDiaxXxakujzlMN3pKsj4cpAJrZeBogZCEXjvKoFUI42q0wLVlq4XNzLtX7xKnEpvpL+VR3QVzkMvqfhbW0OFy1BXZkAK4tlggw1i/K27lpSuCTMUuK6s1lpxvozmRia0XgSZP5LUtM9kFRuFNLZNHIwLVw/KLlKXQFLnSOob3SmwVawqocA66gjEuHQ0zDbbbNGa0vbVFeWMaqTrQCLJAOaM3odMaL0IBt5acEOGDOlSWUM9SC7YrmzkhAkTKs9OilRrZn6ninnlFYBYfJZ71hWIeSnrMDC4IzVjYnhao/SR9u/fv3juuecaUrnvvFl7WpsQbEbvRCa0XgKEksoSGj067qabborb9ajVm8kyU1/GzfNAJqmUQQYzVeR3FshJj6VSDaUo7UHA3gR3yQjusa6GrnYTlGEkH0tPSUlHx/9lNCcyofUSIDRZQO4myedGxc9AM7p6MbGjq6++uvJsC8SlZP1OOOGEmIlUkqE+a+TIkfF1bUWKbHUPdBbKLZZZZpkOyWw7DkqxMqwykIitEeUU5JFYm+r6xM8yejcyofUSqPtCZko2kiR2o4AoEBoLTUtVGYQR99lnn6hcK6uKSC183QLAYqOP1llCsy1ZUjVtHSmiffHFF+P705CWRijlukkQbBS/MzAl15v1fmRC6yUwmQjhcDsbVa6RkKaP2351ca3iWSPsymoVEgE6BZAbMmI5drb3UswMObM22wvoq72TXeXaGjfXiDkGLD7bVSri/BT7NtLqzfhykAmtF4A1ojQB4VS7hI2ALCG30fZZYwl6IUkUIZG02P2LjDbddNP4N5hrqR+0o2UTyi2QmXIRpRJtQWnIoYceGgnXMJhGlVKwzpCkRIAOhZT0yOjdyITWCyCjKQgudtXdtp5aMD08yWrvvvvurVlDZEL4sVrokfCiZvMECq4ItyOlE+J14mYKgzWTtwWuNSkjx6XpXL9mo0BzzcwCJKm+LqNvIBNaLwACsajVoPVEnEftmTiSfWg0T5aWroBaLU0ITmaSdcX93W677eKjvZYlWUnnIKPYnkoIUpV9lajYddddi9dff73ySvfx4IMPxsb5TTbZJE6Oz+g7yITWCyDDiGy4aj0B3QFKMexDUWkiNHE71lQ1iXJ7lU4kfTM9lNzOtkooxOm8hxIHBdj28NRTT8VEBfkhGmmNAqtQHZ8i4jy1qe8hE1qTQ5Zx6aWXjmRz2223VZ5tLATZWU72QcMs9S9qr6o12UnN2MILL9xKdPvtt18kRBX8taDBWzbTZ5Bke6DSQeSRu3v77bdXnu0+WJRUObia4nIZfQ+Z0Jocsm9afJBao8s1EtKgFITGekn9lDKcmtCrhR+VUNA/SxOfEJo+zFqlFG+88UYkRZaZuFV7U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+DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:50] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:50.151429 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:50] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:52.611314 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:52.613315 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:52.615315 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:52.619316 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:52.630332 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:52.634323 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:52.641322 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:52.646711 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:52.651711 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:52.656709 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:52.662711 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:27:52.670755 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:52] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:53] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:53] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:27:55.423381 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:27:55] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 10:28:51.814063 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 10:28:51.816062 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 10:28:51.816062 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 10:28:51.816062 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 10:28:51.816062 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 10:28:52.374981 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:28:52.377984 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:28:53] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69130196995b26cde9611ac4 HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:28:53] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69130196995b26cde9611ac4 HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:21.644620 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:21] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:21.720615 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:21.726630 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:21.739143 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:21] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:21] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:21.751663 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:21] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:21.760661 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:21.769667 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:21] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:21] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:21] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:52.420092 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:52.423693 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:52.426727 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:52.435942 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:52.438459 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:52.444097 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:52.450207 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:52.458841 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:52.465821 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:52.471997 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:29:52.480644 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:29:52.483725 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:52] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:53] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:29:53] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:30:40.864922 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:30:40.871025 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:30:40.877923 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:30:40.882923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:30:40.895923 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:30:40.898924 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:30:40.917546 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:30:40.918673 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:30:40.927684 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:30:40.930679 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:30:40.947186 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:30:40.956189 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:30:40.963192 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:40] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:41] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:41] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:30:42] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:34:23.849427 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:34:23] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:37:10.786807 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:37:10] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:45:38.973255 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:45:38.976240 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:45:38.981239 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:38] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:45:38.988255 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:45:39.002243 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:39] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:39] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:39] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:45:39.040840 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:39] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:45:45.097688 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:45:45.100687 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:45:45.102690 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:45] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:45:45.109689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:45:45.115687 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:45] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:45] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:45] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:45:45.144239 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:45:45] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:48:15.536039 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:48:15.539040 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:48:15.543038 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:15] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:48:15.550043 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:15] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:15] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:48:15.565556 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:15] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:48:15.581629 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:15] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:48:21.853675 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:48:21.856676 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:48:21.859680 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:21] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:48:21.866685 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:48:21.872685 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:21] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:21] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:21] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:48:21.895659 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:48:21] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:49:38.467907 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:49:38] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:51:01.215937 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:51:01] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:52:22.044988 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:52:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:52:25.773440 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:52:25] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:52:30.742395 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:52:30.743395 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:52:30.746393 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:52:30.750396 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:52:30] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:52:30.761393 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:52:30] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:52:30] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:52:30] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:52:30.791396 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:52:30] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:53:24.195569 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:53:24] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:53:29.440867 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:53:29.442868 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:53:29.446382 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:53:29] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:53:29.450388 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:53:29.463381 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:53:29] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:53:29] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:53:29] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:53:29.489919 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:53:29] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:53:56.299636 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:53:56] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:54:54.955174 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:54:55] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:54:59.935302 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:54:59] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:54:59.946304 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:54:59.953303 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:54:59.959302 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:54:59.966310 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:54:59] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:54:59] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:54:59] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:54:59.984833 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:55:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:55:17.802125 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:55:17.806123 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:55:17] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:55:17.817123 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:55:17.824157 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:55:17] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:55:17.827124 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:55:17] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:55:17] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:55:17.852648 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:55:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:56:47.369282 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:56:47] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:57:01.631927 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:57:01.634927 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:57:01.636927 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:01] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:57:01.642927 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:57:01.652929 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:01] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:01] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:01] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:57:01.676989 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:01] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:57:38.697829 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:38] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:57:51.545801 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:57:51.547799 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:57:51.550799 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:51] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:57:51.558799 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:57:51.564800 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:51] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:51] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:51] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:57:51.594723 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:57:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:58:34.668911 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:58:34] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:59:01.743702 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:59:01.749741 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:01] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:59:01.763704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:59:01.766703 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:59:01.771709 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:01] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:01] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:01] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:59:01.793256 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:01] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:59:08.585882 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:59:08.586881 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:59:08.590882 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 10:59:08.595883 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:08] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:59:08.609361 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:08] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:08] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:08] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 10:59:08.631893 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 10:59:08] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 11:04:36.811173 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 11:04:36.811173 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 11:04:36.811173 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 11:04:36.811173 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 11:04:36.811173 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 11:04:47.871553 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 11:04:47.871553 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 11:04:47.871553 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 11:04:47.871553 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 11:04:47.871553 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 11:05:18.014842 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 11:05:18.014842 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 11:05:18.014842 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 11:05:18.014842 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 11:05:18.014842 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 11:06:00.080151 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 11:06:00.080151 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 11:06:00.080151 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 11:06:00.080151 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 11:06:00.080151 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 11:06:10.385823 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 11:06:10.385823 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 11:06:10.385823 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 11:06:10.385823 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 11:06:10.385823 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 11:06:18.599523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:06:18.601526 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:06:18.604524 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:06:18.607524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:06:18] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:06:18.624037 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:06:18] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:06:18] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:06:18] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:06:18.649057 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:06:18] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:06:31.389429 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:06:31] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69130196995b26cde9611ac4 HTTP/1.1" 200 - +INFO:root:2025-11-11 11:06:35.018095 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:06:37.022111 : Get_Stored_Downloaded_File_From_Id -'' is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 583 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:06:37] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/undefined HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 11:08:15.610544 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 11:08:15.610544 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 11:08:15.611543 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 11:08:15.611543 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 11:08:15.611543 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 11:10:51.879357 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:10:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:10:57.696088 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:10:57.699087 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:10:57] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:10:57.706097 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:10:57.708093 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:10:57] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:10:57] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:10:57.724815 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:10:57] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:10:57.750324 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:10:57] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:11:57.024089 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:11:57] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:12:19.615304 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:12:19] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:12:31.819149 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:12:31] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69109a98995b26cde9611abe HTTP/1.1" 200 - +INFO:root:2025-11-11 11:12:34.914111 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:12:36.541888 : Get_Stored_Downloaded_File_From_Id L'identifiant du fichier est invalide +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:12:36] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/undefined HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 11:13:10.027008 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 11:13:10.027008 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 11:13:10.027008 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 11:13:10.027008 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 11:13:10.027008 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 11:13:10.404382 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:13:10] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69109a98995b26cde9611abe HTTP/1.1" 304 - +INFO:root:2025-11-11 11:13:28.262451 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:13:28] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69109a98995b26cde9611abe HTTP/1.1" 200 - +INFO:root:2025-11-11 11:13:34.643620 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:13:34] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69109a98995b26cde9611abe HTTP/1.1" 304 - +INFO:root:2025-11-11 11:15:43.525506 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:15:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:19:30.610409 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:19:30] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:23:32.802845 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:23:32.808850 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:23:32.810854 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:23:32.813858 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:23:32] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:23:32] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:23:32] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:23:32.851899 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:23:32] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:23:32.870902 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:23:32] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:28:27.417625 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:28:27] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:30:18.934135 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:30:19] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:30:29.001591 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:30:29.007598 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:30:29] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:30:29.020142 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:30:29.028171 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 11:30:29.033157 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:30:29] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:30:29] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:30:29] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:30:29.051172 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:30:29] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 11:30:41.956242 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 11:30:41] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69109a98995b26cde9611abe HTTP/1.1" 304 - +INFO:root:2025-11-11 14:28:06.036555 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:28:06] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:29:55.937104 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:29:56] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:32:26.647782 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:32:26.647782 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:32:26.647782 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:32:26.647782 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:32:26.647782 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:34:14.591624 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:34:14.591624 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:34:14.591624 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:34:14.591624 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:34:14.591624 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:35:24.938556 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:35:24.938556 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:35:24.938556 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:35:24.940059 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:35:24.940059 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:36:01.350293 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:36:01.350293 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:36:01.350293 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:36:01.350293 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:36:01.350293 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:38:57.167301 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:38:57.167301 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:38:57.167301 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:38:57.167301 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:38:57.167301 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:39:29.924858 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:39:29.924858 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:39:29.924858 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:39:29.924858 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:39:29.924858 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:39:49.421874 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:39:49.421874 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:39:49.421874 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:39:49.421874 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:39:49.421874 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:43:28.354218 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:43:28.354218 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:43:28.354218 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:43:28.354218 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:43:28.354218 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:43:35.453231 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:43:35.453231 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:43:35.453231 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:43:35.453231 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:43:35.453231 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:44:31.117725 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:44:31.117725 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:44:31.117725 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:44:31.117725 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:44:31.117725 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:48:35.045577 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:48:35.045577 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:48:35.045577 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:48:35.045577 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:48:35.045577 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:48:42.019479 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:48:42.019479 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:48:42.019479 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:48:42.019479 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:48:42.019479 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:49:42.372269 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:49:42.372269 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:49:42.372269 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:49:42.373268 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:49:42.373268 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:49:55.186748 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:49:55] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:50:02.579311 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 14:50:02.582334 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 14:50:02.586311 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:50:02] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:50:02.593311 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:50:02] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:50:02.608312 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:50:02] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:50:02] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:50:02.631339 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:50:02] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:50:18.353496 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:50:18] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\main.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:51:06.729316 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:51:06.729316 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:51:06.729316 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:51:06.729316 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:51:06.729316 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:51:06.834811 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:51:07] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:51:44.721145 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:51:44.721145 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:51:44.721145 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:51:44.721145 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:51:44.721145 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:51:47.929930 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:51:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:53:01.412713 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:53:01.413714 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:53:01.413714 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:53:01.413714 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:53:01.413714 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:54:24.812376 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:54:24.812376 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:54:24.812376 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:54:24.812376 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:54:24.812376 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:54:31.840292 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:54:31] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:55:05.351012 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:55:05.351012 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:55:05.352014 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:55:05.352014 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:55:05.352014 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:55:06.968739 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:55:07] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:55:26.876933 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:55:26] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:56:09.474057 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:56:09.474057 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:56:09.474057 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:56:09.474057 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:56:09.474057 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:56:40.560191 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:56:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:56:49.408264 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:56:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:57:12.178772 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:57:12.178772 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:57:12.179772 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:57:12.179772 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:57:12.179772 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:57:12.257066 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:57:12] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 14:57:52.236771 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 14:57:52.237771 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 14:57:52.237771 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 14:57:52.237771 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 14:57:52.237771 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 14:57:55.934053 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:57:55] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:57:57.968970 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:57:58] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:58:09.374832 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:58:09] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:58:22.556994 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:58:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:58:36.182081 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:58:36] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:58:43.585796 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:58:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:58:49.210235 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:58:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 14:59:22.702867 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 14:59:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:02:10.813424 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:02:10.814419 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:02:10.814419 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:02:10.814419 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:02:10.814419 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:02:39.880050 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:02:39.881049 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:02:39.881049 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:02:39.881049 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:02:39.881049 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:02:50.042816 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:02:50.042816 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:02:50.042816 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:02:50.042816 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:02:50.042816 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:02:54.201611 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:02:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:03:07.802514 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:03:07] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:03:24.124746 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:03:24] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:03:56.304219 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:03:56] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:05:15.911207 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:05:15.911207 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:05:15.911207 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:05:15.911207 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:05:15.911207 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:06:02.004653 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:06:02.005655 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:06:02.005655 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:06:02.005655 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:06:02.005655 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:06:11.973306 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:06:11.973306 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:06:11.973306 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:06:11.973306 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:06:11.973306 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:06:57.492108 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:06:57.493106 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:06:57.493106 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:06:57.493106 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:06:57.493106 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:07:11.257786 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:07:11] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:07:56.403638 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:07:56.404621 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:07:56.405717 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:07:56.405717 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:07:56.405717 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:09:17.562760 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:09:17.562760 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:09:17.562760 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:09:17.562760 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:09:17.562760 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:09:24.213969 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:09:24.213969 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:09:24.213969 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:09:24.213969 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:09:24.213969 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:09:38.163983 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:09:38.163983 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:09:38.163983 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:09:38.163983 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:09:38.163983 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:09:49.144526 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:09:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:09:56.589972 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:09:56] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:10:04.381511 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:10:04] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:10:40.005360 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:10:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:11:25.550457 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:11:25.550457 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:11:25.550457 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:11:25.550457 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:11:25.550457 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:11:53.840369 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:11:53.840369 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:11:53.840369 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:11:53.840369 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:11:53.840369 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:12:00.324464 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:12:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:13:18.518434 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:13:18.518434 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:13:18.518434 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:13:18.518434 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:13:18.518434 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:13:24.425625 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:13:25.700892 : Get_List_object_owner_collection_Stored_Files_With_Filter -'filter_class_external_code' - ERRORRRR AT Line : 1357 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:13:25] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:13:45.799275 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:13:45.799275 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:13:45.799275 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:13:45.799275 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:13:45.799275 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:13:47.321775 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:13:47] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:14:27.711089 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:14:27.711089 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:14:27.711089 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:14:27.711089 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:14:27.711089 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:14:27.902661 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:14:27] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:14:32.459285 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:14:32] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:14:35.734492 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:14:35] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:15:14.589895 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:15:14.589895 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:15:14.589895 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:15:14.589895 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:15:14.589895 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:15:14.650300 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:15:14.652299 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:15:14.653298 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:14] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:14] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:14] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:15:19.077339 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:19] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:15:24.213233 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:24] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:15:35.596383 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:35] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/6912fa9c995b26cde9611ac1 HTTP/1.1" 200 - +INFO:root:2025-11-11 15:15:37.725212 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:37] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/6912f783995b26cde9611ac0 HTTP/1.1" 200 - +INFO:root:2025-11-11 15:15:54.719353 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:15:54] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:16:06.599479 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:16:06] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:16:08.593102 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:16:08] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:16:12.142175 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:16:12] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:18:57.197859 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:18:57] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:21.016849 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:21] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:39.526381 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:39.527380 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:39.531888 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:39.533888 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:39.538888 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:39.543391 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:39.547396 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:39.560629 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:39.563669 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:39.573628 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:39.582629 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:39.587629 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:39] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:40] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:41.974705 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:41.976704 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:41.979706 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:41.983707 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:41] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:41] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:41.990720 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:41] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:41.995707 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:41.998733 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:42.009743 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:42.013724 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:42.019705 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:42.022707 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:42.028734 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:42] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:49.951671 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:50] "POST /myclass/api/GetAllValideSessionPartner_List_filter_like/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:52.597514 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:52.601513 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:52.605517 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:52.610512 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:52.616545 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:52] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:52.621512 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:52] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:52.626512 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:52] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:52] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:52] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:52] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:52] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:19:57.190073 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:19:57.194040 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:57] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:19:57] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:20:10.773904 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:20:10] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:34:12.237107 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:34:12] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:34:12.324424 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:34:12] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:34:16.355134 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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N° de déclaration d\'activité :  NDA-001254 

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 Est conclue la convention suivante entre
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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes : prenom nonn 
Contact :   
Téléphone :  
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Et

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Et le bénéciaire :
 qsdsq qsdqs 
(Ci-aprés nommé le client)
Situé :     

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PRÉAMBULE
EZUS Lyon   Colas Rail filiale de Valorisation de l\'Université Claude Bernard Lyon I, s\'est vue confier la gestion des activités industrielles et commerciales des centres et services de l\'UCBL, ainsi que les actions de formation continue par la convention cadre signée le 23 janvier 2008.

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A cet effet, la société Colas Rail  fait appel au : Docteur Eric J. VOIGLIO, MD, PhD, FACS, FRCS Directeur ATLS France.

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Est conclu un contrat de formation professionnelle en application de l\'article L6353-3 du Code du Travail.

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation

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 Colas Rail 

\nFormation : CONDUIRE UN PROJET 
Durée : 15.0   heure (s) 
Lieu de formation :   vile sit1 
Dates de formation :  17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 
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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.

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Article 4 : Prix de la formation
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire :  1500.0 €

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 11/11/2025 

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Pour l\'organisme de formation prenom   nonn 

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Pour le client :
Nom & Prénom du Signataire

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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_51252.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:34:19] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:34:19.785050 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:34:20] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:36:32.405212 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:36:32.405212 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:36:32.405212 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:36:32.405212 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:36:32.405212 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Session_Formation.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:37:05.473855 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:37:05.473855 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:37:05.473855 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:37:05.473855 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:37:05.473855 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:37:51.642218 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:37:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:37:58.729242 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:37:58.730243 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:37:58.736242 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:37:58.740242 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:37:58.746242 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:37:58] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:37:58] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:37:58] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:37:58] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:37:58.782384 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:37:58] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:38:06.422014 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:38:06] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:39:00.622050 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:39:00.625051 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:39:00] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:39:00] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:39:15.962443 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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N° de déclaration d\'activité :  NDA-001254 

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 Est conclue la convention suivante entre
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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes : prenom nonn 
Contact :   
Téléphone :  
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Et

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Et le bénéciaire :
 qsdsq qsdqs 
(Ci-aprés nommé le client)
Situé :     

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PRÉAMBULE
EZUS Lyon   Colas Rail filiale de Valorisation de l\'Université Claude Bernard Lyon I, s\'est vue confier la gestion des activités industrielles et commerciales des centres et services de l\'UCBL, ainsi que les actions de formation continue par la convention cadre signée le 23 janvier 2008.

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A cet effet, la société Colas Rail  fait appel au : Docteur Eric J. VOIGLIO, MD, PhD, FACS, FRCS Directeur ATLS France.

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Est conclu un contrat de formation professionnelle en application de l\'article L6353-3 du Code du Travail.

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation

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 Colas Rail 

\nFormation : CONDUIRE UN PROJET 
Durée : 15.0   heure (s) 
Lieu de formation :   vile sit1 
Dates de formation :  17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 
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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.

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Article 4 : Prix de la formation
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire :  1500.0 €

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 11/11/2025 

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Pour l\'organisme de formation prenom   nonn 

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Pour le client :
Nom & Prénom du Signataire

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\n

 

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\n

 

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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_03017.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:39:17] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:39:17.348009 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:39:17] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:43:04.131958 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:43:04.131958 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:43:04.131958 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:43:04.132963 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:43:04.132963 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:43:29.465036 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:43:29.465036 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:43:29.465036 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:43:29.465036 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:43:29.465036 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:45:34.195159 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:45:34.195159 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:45:34.195159 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:45:34.196160 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:45:34.196160 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:47:10.470485 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:47:10.470485 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:47:10.470485 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:47:10.470485 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:47:10.470485 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:48:01.469093 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:48:01.469093 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:48:01.469093 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:48:01.469093 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:48:01.469093 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:52:39.416262 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:52:39.416262 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:52:39.417263 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:52:39.417263 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:52:39.417263 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:52:53.936222 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:52:53.936222 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:52:53.936222 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:52:53.936222 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:52:53.936222 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:53:03.807638 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:53:03.811637 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:53:03] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:53:03] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:53:12.083504 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

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Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

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xddd   qsdqsd   mysy1000formation+04@gmail.com
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Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_17318.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:53:13] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:53:13.390286 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:53:13] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:53:51.770826 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:53:51] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:53:52.719059 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:53:52] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:53:57.813369 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:53:57] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69134dd9995b26cde9611ac5 HTTP/1.1" 200 - +INFO:root:2025-11-11 15:54:02.964851 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:54:02] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/69134dd9995b26cde9611ac5 HTTP/1.1" 304 - +INFO:root:2025-11-11 15:54:18.071375 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:54:18] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:54:22.797306 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:54:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:56:01.724357 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:56:01.725356 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:56:01.725356 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:56:01.725356 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:56:01.725356 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:56:39.512418 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:56:39.512418 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:56:39.512418 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:56:39.512418 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:56:39.512418 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:56:39.574710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:56:39.576719 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:56:39] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:56:39] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:56:46.959382 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:56:46.962381 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:56:46] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:56:46] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:56:51.295989 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_77507.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:56:52] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:56:52.596912 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:56:53] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:57:38.170184 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:57:38.170184 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:57:38.170184 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:57:38.170184 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:57:38.170184 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:57:47.133812 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:57:47.156684 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:57:47] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:57:47] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:57:49.774009 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_33137.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:57:51] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:57:51.846189 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:57:52] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 15:58:56.596888 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 15:58:56.596888 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 15:58:56.596888 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 15:58:56.596888 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 15:58:56.596888 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 15:58:56.675931 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:58:56.678935 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:58:56] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:58:56] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:59:05.141563 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 15:59:05.145566 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:59:05] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:59:05] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:59:07.546028 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_61576.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:59:09] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 15:59:09.133465 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 15:59:09] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:00:16.107178 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:00:16.107178 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:00:16.107178 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:00:16.108177 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:00:16.108177 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:00:45.768789 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:00:45.809884 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:00:46] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:00:46] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:00:51.616913 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_40636.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:00:56] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:00:56.520049 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:01:03] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:01:46.153335 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:01:46.162335 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:01:46] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:01:46] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:01:48.438433 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_67785.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:01:50] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:01:50.197910 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:01:51] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:02:38.972309 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:02:38.972309 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:02:38.972309 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:02:38.972309 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:02:38.972309 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:02:55.496992 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:02:55.500979 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:02:55] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:02:55] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:02:57.816761 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_81778.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:02:59] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:02:59.017323 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:02:59] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:03:28.703973 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:03:29.845319 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:03:30.244330 : Get_List_object_owner_collection_Stored_Files_With_Filter -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 1564 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:03:30] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:03:30.245720 : Get_List_object_owner_collection_Stored_Files_With_Filter -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 1564 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:03:30] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:03:58.341602 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:03:58.345605 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:03:58] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:03:58] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:04:00.344943 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_42058.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:04:01] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:04:01.665676 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:04:02] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:04:15.056172 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:04:15.082388 : Get_List_object_owner_collection_Stored_Files_With_Filter -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 1564 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:04:15] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:05:09.756193 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:05:09] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:05:20.365450 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:05:20.378431 : Get_List_object_owner_collection_Stored_Files -'68eb6ed8d980c4ab7268ba70, sdsddsdsdsdsds' is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 929 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:05:20] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:05:21.029007 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:05:21.046442 : Get_List_object_owner_collection_Stored_Files_With_Filter -'68eb6ed8d980c4ab7268ba70, sdsddsdsdsdsds' is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 1564 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:05:21] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:09:57.521036 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:09:57.524025 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:09:57] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:09:57] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:09:59.833417 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_91069.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:10:02] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:10:02.233646 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:10:02] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:17:34.400501 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:17:34.401619 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:17:34.401619 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:17:34.401619 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:17:34.401619 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:17:39.217939 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:17:40.416083 : Get_List_object_owner_collection_Stored_Files_With_Filter -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 1566 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:17:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:19:49.607899 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:19:49.612910 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:19:49.615938 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:49] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:19:49.626936 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:49] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:19:49.644485 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:49] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:49] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:19:49.863354 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:19:53.254651 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:19:53.258630 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:53] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:53] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:19:55.689913 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 11/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_76967.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:57] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:19:57.204106 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:19:57] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:20:21.742636 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:20:21.760623 : Get_List_object_owner_collection_Stored_Files_With_Filter -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 1566 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:20:21] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:22:26.364488 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:22:26.364488 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:22:26.364488 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:22:26.364488 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:22:26.364488 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:22:28.556944 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:22:30.186152 : Get_List_object_owner_collection_Stored_Files_With_Filter -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 1566 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:22:30] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:23:01.199049 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:23:01.199049 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:23:01.199049 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:23:01.199049 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:23:01.199049 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:25:43.226105 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:25:43.226105 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:25:43.226105 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:25:43.226105 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:25:43.226105 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:26:43.507069 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:26:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:27:05.668960 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:27:05] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/6913541d995b26cde9611ace HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:27:55.823880 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:27:55.823880 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:27:55.823880 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:27:55.823880 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:27:55.823880 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:29:25.275467 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:29:25.275467 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:29:25.275467 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:29:25.276467 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:29:25.276467 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:29:57.477856 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:29:57.478839 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:29:57.478839 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:29:57.478839 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:29:57.478839 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:30:43.429353 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:30:43.429353 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:30:43.429353 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:30:43.430353 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:30:43.430353 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:31:07.457245 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:31:07.458245 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:31:07.458245 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:31:07.458245 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:31:07.458245 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:31:35.234544 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:31:35.236544 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:31:35] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:31:35] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:31:38.127817 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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N° de déclaration d\'activité :  NDA-001254 

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 Est conclue la convention suivante entre
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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes : prenom nonn 
Contact :   
Téléphone :  
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Et

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Et le bénéciaire :
 QSD SDS 
(Ci-aprés nommé le client)
Situé :     

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PRÉAMBULE
EZUS Lyon   Colas Rail filiale de Valorisation de l\'Université Claude Bernard Lyon I, s\'est vue confier la gestion des activités industrielles et commerciales des centres et services de l\'UCBL, ainsi que les actions de formation continue par la convention cadre signée le 23 janvier 2008.

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A cet effet, la société Colas Rail  fait appel au : Docteur Eric J. VOIGLIO, MD, PhD, FACS, FRCS Directeur ATLS France.

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Est conclu un contrat de formation professionnelle en application de l\'article L6353-3 du Code du Travail.

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation

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 Colas Rail 

\nFormation : CONDUIRE UN PROJET 
Durée : 15.0   heure (s) 
Lieu de formation :   vile sit1 
Dates de formation :  17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 
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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.

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Article 4 : Prix de la formation
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire :  1500.0 €

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 11/11/2025 

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Pour l\'organisme de formation prenom   nonn 

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Pour le client :
Nom & Prénom du Signataire

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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_83451.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:31:40] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:31:40.528804 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:31:41] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:32:03.159501 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:32:13.479497 : Get_List_object_owner_collection_Stored_Files -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 929 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:32:13] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:32:15.056898 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:32:15.081860 : Get_List_object_owner_collection_Stored_Files -"['68eb6ed8d980c4ab7268ba70']" is not a valid ObjectId, it must be a 12-byte input or a 24-character hex string - ERRORRRR AT Line : 929 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:32:15] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:33:54.811611 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:33:54.812614 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:33:54.812614 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:33:54.812614 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:33:54.812614 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:34:05.035155 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:34:05.035155 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:34:05.035155 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:34:05.035155 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:34:05.035155 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:34:10.905565 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:34:11] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:34:22.365177 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:34:22] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:34:27.670113 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:34:27] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/Q5rl1SB7yMgqvVejJzQPL95U860yzsUB1w/691356dc995b26cde9611acf HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:35:32.428606 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:35:32.428606 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:35:32.428606 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:35:32.428606 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:35:32.428606 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\attached_file_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:35:52.280143 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:35:52.280143 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:35:52.280143 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:35:52.280143 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:35:52.280143 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:36:04.889878 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:36:04.893905 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:36:04] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:36:04] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:36:07.913166 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

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Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

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xddd   qsdqsd   mysy1000formation+04@gmail.com
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Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 11/11/2025 

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Pour l\'organisme de formation
prenom  nonn

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Pour le client :
Nom & Prénom du Signataire

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Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

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N° de déclaration d\'activité :  NDA-001254 

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 Est conclue la convention suivante entre
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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes : prenom nonn 
Contact :   
Téléphone :  
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Et

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Et le bénéciaire :
 qsdsq qsdqs 
(Ci-aprés nommé le client)
Situé :     

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PRÉAMBULE
EZUS Lyon   Colas Rail filiale de Valorisation de l\'Université Claude Bernard Lyon I, s\'est vue confier la gestion des activités industrielles et commerciales des centres et services de l\'UCBL, ainsi que les actions de formation continue par la convention cadre signée le 23 janvier 2008.

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A cet effet, la société Colas Rail  fait appel au : Docteur Eric J. VOIGLIO, MD, PhD, FACS, FRCS Directeur ATLS France.

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Est conclu un contrat de formation professionnelle en application de l\'article L6353-3 du Code du Travail.

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation

\n

 Colas Rail 

\nFormation : CONDUIRE UN PROJET 
Durée : 15.0   heure (s) 
Lieu de formation :   vile sit1 
Dates de formation :  17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 
\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.

\n

Article 4 : Prix de la formation
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire :  1500.0 €

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 11/11/2025 

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Pour l\'organisme de formation prenom   nonn 

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Pour le client :
Nom & Prénom du Signataire

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\n
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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\t
Signature Client

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

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Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

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xddd   qsdqsd   mysy1000formation+04@gmail.com
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Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 11/11/2025 

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Pour l\'organisme de formation
prenom  nonn

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Pour le client :
Nom & Prénom du Signataire

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Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

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Signature Client

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Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 4096 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'PLTE' 41 6 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 59 597 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 4096 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 5223 6 +INFO:root:2025-11-11 16:41:05.855303 : Internal_Usage_Store_User_Downloaded_File -'NoneType' object has no attribute 'append' - ERRORRRR AT Line : 382 +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:41:05] "POST /myclass/api/Create_E_Signature_For_E_Document/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:43:59.033608 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:43:59.033608 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:43:59.034607 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:43:59.034607 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:43:59.034607 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:47:38.804424 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:47:38.804424 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:47:38.804424 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:47:38.804424 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:47:38.804424 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:48:44.620919 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:48:44.620919 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:48:44.620919 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:48:44.621920 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:48:44.621920 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:49:48.599596 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:49:48.599596 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:49:48.600605 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:49:48.600605 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:49:48.600605 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:50:05.602672 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:50:05.602672 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:50:05.602672 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:50:05.602672 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:50:05.602672 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:51:13.661898 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:51:13.661898 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:51:13.661898 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:51:13.661898 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:51:13.661898 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:51:44.204275 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:51:44.204275 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:51:44.204275 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:51:44.204275 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:51:44.204275 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\Inscription_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-11 16:52:52.798991 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-11 16:52:52.798991 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-11 16:52:52.798991 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-11 16:52:52.798991 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-11 16:52:52.799991 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-11 16:54:51.889466 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-11 16:54:51.890471 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:54:51] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:54:51] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:54:56.580337 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

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Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

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xddd   qsdqsd   mysy1000formation+04@gmail.com
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Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 11/11/2025 

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Pour l\'organisme de formation
prenom  nonn

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Pour le client :
Nom & Prénom du Signataire

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Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

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' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_47443.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:root:2025-11-11 16:54:58.683652 : Create_E_Document Le champ 'class_id' n'est pas autorisé +INFO:root:2025-11-11 16:54:58.683652 : WARNING : impossible d'envoyer la convention au client : 68c535af5fd368bd641dceae +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:54:58] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-11 16:54:58.690638 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [11/Nov/2025 16:54:59] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:26:32.932804 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:26:32.932804 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:26:32.932804 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:26:32.932804 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:26:32.932804 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:26:39.395522 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:26:39.395522 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:26:39.395522 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:26:39.395522 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:26:39.395522 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:34:14.594521 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:34:14.595521 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:34:14.595521 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:34:14.595521 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:34:14.595521 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:34:49.840448 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:34:49.840448 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:34:49.841453 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:34:49.841453 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:34:49.841453 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-12 12:34:49.938946 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:49.939946 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:49] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:49] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:34:55.715175 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:55.724177 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:55] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:34:55.740135 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:55.743115 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:55.748120 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:55.767116 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:55] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:55] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:55] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:55] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:34:56.149069 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:56.152063 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:56.154065 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:56.160073 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:34:56.166171 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:56] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:34:56.175157 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:56] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:56] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:56] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:56] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:34:56] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:02.402806 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:02.405280 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:02.408604 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:02.412761 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:02.416759 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:02.422774 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:02.428877 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:02.438387 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:02.446705 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:02.451219 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:02.461209 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:02.468205 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:02] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:03] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:03] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:07.584672 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:07.591318 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:07.595327 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:07.600541 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:07.606943 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:07] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:07.617496 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:07] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:07] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:07.628498 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:07] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:07] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:07] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:07] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:09.950692 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:09.954488 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:09] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:11] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:16.466405 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:16.471835 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:16.475781 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:16.478788 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:16.484304 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:16.489420 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:16] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:16] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:16.498302 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:16] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:16] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:16] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:16] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:16] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:18.855539 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:18.859554 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:18] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:20] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:30.539897 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:35:30.544345 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:30] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:30] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:33.165315 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

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Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

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xddd   qsdqsd   mysy1000formation+04@gmail.com
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Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 12/11/2025 

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Pour l\'organisme de formation
prenom  nonn

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Pour le client :
Nom & Prénom du Signataire

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Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

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' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_95198.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:root:2025-11-12 12:35:35.126289 : Create_E_Document Le champ 'class_id' n'est pas autorisé +INFO:root:2025-11-12 12:35:35.126289 : WARNING : impossible d'envoyer la convention au client : 68c535af5fd368bd641dceae +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:35] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:35:35.133701 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:35:35] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:38:05.558820 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:38:05.558820 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:38:05.559822 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:38:05.559822 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:38:05.559822 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-12 12:38:05.942685 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:05.952687 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:05.962681 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:05.968686 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:05.976696 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:05.987791 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:06] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:06] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:06] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:06] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:06] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:06] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:11.870120 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.873301 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.878311 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:11] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:11.888349 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.898603 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:11] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:11] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:11] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:11.966599 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.970607 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.973765 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.978774 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.983956 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:11] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:11] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:11.992458 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.992458 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:11.998552 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:12.008584 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:12.016585 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:12.024006 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:12.035018 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:12] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:13] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:15.340258 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:15.344482 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:15.348481 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:15.351480 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:15.357482 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:15] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:15.365502 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:15] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:15] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:15.372501 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:15] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:15] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:15] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:15] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:17.520095 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:17.523192 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:18] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:26.648474 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:38:26.654593 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:26] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:26] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:28.751322 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

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\n

Paris , 12/11/2025 

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Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_53845.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:35] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:38:35.532379 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:38:35] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:39:39.312657 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:39:40] "POST /myclass/api/Get_Given_E_Document_Not_Signed_No_Token/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:40:17.870051 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '


 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 12/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

\t
Signature Client

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Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 3901 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'PLTE' 41 6 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 59 600 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 3901 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 3954 6 +INFO:root:2025-11-12 12:40:21.443582 : Create_E_Signature_For_E_Document -name 'class_data' is not defined - Line : 1341 +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:40:21] "POST /myclass/api/Create_E_Signature_For_E_Document/ HTTP/1.1" 200 - +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:42:25.311556 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:42:25.311556 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:42:25.311556 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:42:25.312554 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:42:25.312554 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:42:46.810235 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:42:46.810235 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:42:46.810235 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:42:46.810235 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:42:46.810235 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:43:52.298970 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:43:52.300076 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:43:52.300076 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:43:52.300076 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:43:52.300076 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\E_Sign_Document.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:50:52.832423 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:50:52.832423 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:50:52.832423 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:50:52.832423 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:50:52.832423 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 12:51:03.892491 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 12:51:03.892491 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 12:51:03.892491 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 12:51:03.892491 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 12:51:03.892491 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-12 12:51:25.866961 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:51:25.870963 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:51:25] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:51:25] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:51:29.180712 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

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Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 12/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_44815.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:51:31] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:51:31.995866 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:51:32] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:52:21.665067 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:52:21.672066 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:52:21] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:52:21] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:52:25.289166 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 12/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_39512.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:52:28] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:52:28.274655 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:52:29] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:01.611326 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:03] "POST /myclass/api/Get_Given_E_Document_Not_Signed_No_Token/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:22.480212 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '


 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

 

\n

Paris , 12/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation
prenom  nonn

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n
\n

 

\n

 

\n

 

\n

Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

\t
Signature Client

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Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 4096 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'PLTE' 41 6 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 59 597 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 41 4096 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 4928 6 +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:24] "POST /myclass/api/Create_E_Signature_For_E_Document/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:56.985277 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:56.991276 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:56.999279 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:57.006275 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.035806 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.110337 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:57.118337 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:57.123349 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:57.132349 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.142863 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.157865 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:57.167885 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.180864 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.199865 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.214875 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:53:57.224381 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:53:57.242965 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:57] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:53:58] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:54:00] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:54:07.741022 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:54:07] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:54:13.559655 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:54:13] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/CpP6CowvwoiFG_-qAFK12ECBRcc5i72yug/69147534995b26cde9611ad4 HTTP/1.1" 200 - +INFO:root:2025-11-12 12:54:30.172764 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:54:30] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/CpP6CowvwoiFG_-qAFK12ECBRcc5i72yug/691474fc995b26cde9611ad3 HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:27.442997 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:27.449998 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:27.455999 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:27.468997 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:27] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:27] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:27.485022 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:27.497018 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:27] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:27.510548 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:27] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:27] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:27] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:27] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:29.463619 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:29.469618 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:29] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:31] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:40.172364 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:40] "POST /myclass/api/archive_session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:40.280265 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:40] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:47.311289 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:47.317289 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:47.323306 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:47.327305 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:47.343843 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:47.347850 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:47] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:47] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:47.369848 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:47] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:47] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:47] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:47] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:47] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:55:49.301667 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:55:49.305669 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:49] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:55:51] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:05.034231 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:05.039231 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:05] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:05] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:08.361178 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:08] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:08.498914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:09] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:26.264050 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:26.269052 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:26.280052 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:26.296070 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:26] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:26] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:26.311707 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:26] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:26.320703 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:26.339704 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:26] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:26] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:26] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:26] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:28.095193 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:28.097189 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:28] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:30] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:34.912355 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:34.917355 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:34.922924 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:34.930957 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:34.939935 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:34.948951 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:34] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:34] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:34.963930 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:34] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:34] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:34] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:34] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:34] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:36.673025 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:36.679929 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:38] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:45.665921 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 12:56:45.673014 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:45] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:56:45] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:56:52.735348 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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A l\'attention  mme   prenom test01  

Situé :        

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   BESOIN DE SÉCURITÉ : UNE AUTRE LECTURE DES COMPORTEMENTS
Durée :  1.0 jour (s)
Lieu de formation :     , -  
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    27/08/2024 09:00  au 27/08/2024 12:00
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Du    27/08/2024 13:30  au 27/08/2024 17:00
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Du    28/08/2024 09:00  au 28/08/2024 12:00
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Du    28/08/2024 13:30  au 28/08/2024 17:00
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Au plaisir de vous retrouver prochainement,
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12/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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N° de déclaration d\'activité :  NDA-001254 

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 Est conclue la convention suivante entre
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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes : prenom nonn 
Contact :   
Téléphone :  
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Et

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Et le bénéciaire :
 cherfi balde 
(Ci-aprés nommé le client)
Situé :     

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PRÉAMBULE
EZUS Lyon   Colas Rail filiale de Valorisation de l\'Université Claude Bernard Lyon I, s\'est vue confier la gestion des activités industrielles et commerciales des centres et services de l\'UCBL, ainsi que les actions de formation continue par la convention cadre signée le 23 janvier 2008.

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A cet effet, la société Colas Rail  fait appel au : Docteur Eric J. VOIGLIO, MD, PhD, FACS, FRCS Directeur ATLS France.

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Est conclu un contrat de formation professionnelle en application de l\'article L6353-3 du Code du Travail.

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation

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 Colas Rail 

\nFormation : BESOIN DE SÉCURITÉ : UNE AUTRE LECTURE DES COMPORTEMENTS 
Durée : 1.0   jour (s) 
Lieu de formation :    
Dates de formation :  26/08/2024  28/08/2024 
Nom formateur :  
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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.

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Article 4 : Prix de la formation
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire :  227.0 €

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 12/11/2025 

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Pour l\'organisme de formation prenom   nonn 

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Pour le client :
Nom & Prénom du Signataire

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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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A l\'attention  mme   prenom test01  

Situé :        

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L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : Christian XXXX
Signataire dûment habilité aux fins des présentes : Emmanuelle XXXXXX
Contact :  contact@elyos-si.org
Téléphone : 01 XX XX XX XX 
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à le plaisir de vous convier à la formation ci-dessous :
Formation :   BESOIN DE SÉCURITÉ : UNE AUTRE LECTURE DES COMPORTEMENTS
Durée :  1.0 jour (s)
Lieu de formation :     , -  
Vous êtes invités à vous présenter 20 minutes avant l\'horaire prévu.
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Les séquences de formation  :
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Du    27/08/2024 09:00  au 27/08/2024 12:00
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Du    27/08/2024 13:30  au 27/08/2024 17:00
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Du    28/08/2024 09:00  au 28/08/2024 12:00
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Du    28/08/2024 13:30  au 28/08/2024 17:00
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Au plaisir de vous retrouver prochainement,
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12/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:59:46] "POST /myclass/api/Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 12:59:46.457916 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 12:59:46] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:00:09.049599 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:00:09] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:00:09.114601 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:00:09.162128 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:00:09.185127 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:00:09] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:00:09] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:00:09.231136 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:00:09] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:00:09.276192 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:00:10] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:00:39.741507 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:00:39] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:00:48.582157 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:00:48] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/CpP6CowvwoiFG_-qAFK12ECBRcc5i72yug/69147607995b26cde9611ad5 HTTP/1.1" 200 - +INFO:root:2025-11-12 13:01:17.118004 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:01:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:01:40.009350 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:01:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:02:30.084394 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:02:30] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/CpP6CowvwoiFG_-qAFK12ECBRcc5i72yug/68eb7b78d980c4ab7268ba74 HTTP/1.1" 200 - +INFO:root:2025-11-12 13:04:01.438575 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:04:01] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:04:02.829870 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:04:02] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:04:09.224005 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:04:09] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:04:17.717625 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:04:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:05:18.307152 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:05:18] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:25.481278 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:25] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:36.227365 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:07:36.232442 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:07:36.238546 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:07:36.247451 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:36.264962 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:07:36.276208 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:36] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:36.297934 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:36] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:36] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:36] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:36] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:38.586162 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:07:38.592115 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:38] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:40] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:47.052915 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:07:47.058926 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:47] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:47] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:50.945281 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

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Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

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Est conclue la convention suivante. 

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Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

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Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

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Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
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Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

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Paris , 12/11/2025 

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Pour l\'organisme de formation
prenom  nonn

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\n

Pour le client :
Nom & Prénom du Signataire

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\n

 

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Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

\n

 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_05813.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:54] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:07:54.202836 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:07:55] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:08:04.103975 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:08:04.135177 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:08:04] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:08:04] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:08:07.151168 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

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N° de déclaration d\'activité :  NDA-001254 

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\n
\n
\n
\n
 Est conclue la convention suivante entre
\n
L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes : prenom nonn 
Contact :   
Téléphone :  
\n

Et

\n
Et le bénéciaire :
 qsdsq qsdqs 
(Ci-aprés nommé le client)
Situé :     

\n
\n
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PRÉAMBULE
EZUS Lyon   Colas Rail filiale de Valorisation de l\'Université Claude Bernard Lyon I, s\'est vue confier la gestion des activités industrielles et commerciales des centres et services de l\'UCBL, ainsi que les actions de formation continue par la convention cadre signée le 23 janvier 2008.

\n

A cet effet, la société Colas Rail  fait appel au : Docteur Eric J. VOIGLIO, MD, PhD, FACS, FRCS Directeur ATLS France.

\n

Est conclu un contrat de formation professionnelle en application de l\'article L6353-3 du Code du Travail.

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation

\n

 Colas Rail 

\nFormation : CONDUIRE UN PROJET 
Durée : 15.0   heure (s) 
Lieu de formation :   vile sit1 
Dates de formation :  17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 
\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.

\n

Article 4 : Prix de la formation
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire :  1500.0 €

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

Paris , 12/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation prenom   nonn 

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n

 

\n
\n

 

\n
\n

 

\n

 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_17924.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '

 

\n

\n
\n
\n
\n

N° de déclaration d\'activité :  NDA-001254 

\n
\n
\n
\n
\n
 Est conclue la convention suivante entre
\n
L\'Organisme de formation  Colas Rail   ci-après nommé l\'Organisme de formation
Situé : rue de la république 77 paris 
Déclation d\'activité :  NDA-001254  Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes : prenom nonn 
Contact :   
Téléphone :  
\n

Et

\n
Et le bénéciaire :
 QSD SDS 
(Ci-aprés nommé le client)
Situé :     

\n
\n
\n

PRÉAMBULE
EZUS Lyon   Colas Rail filiale de Valorisation de l\'Université Claude Bernard Lyon I, s\'est vue confier la gestion des activités industrielles et commerciales des centres et services de l\'UCBL, ainsi que les actions de formation continue par la convention cadre signée le 23 janvier 2008.

\n

A cet effet, la société Colas Rail  fait appel au : Docteur Eric J. VOIGLIO, MD, PhD, FACS, FRCS Directeur ATLS France.

\n

Est conclu un contrat de formation professionnelle en application de l\'article L6353-3 du Code du Travail.

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation

\n

 Colas Rail 

\nFormation : CONDUIRE UN PROJET 
Durée : 15.0   heure (s) 
Lieu de formation :   vile sit1 
Dates de formation :  17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 
\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.

\n

Article 4 : Prix de la formation
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire :  1500.0 €

\n

Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

\n

 

\n

Paris , 12/11/2025 

\n\n\n\n\n\n\n\n
\n

Pour l\'organisme de formation prenom   nonn 

\n
\n

Pour le client :
Nom & Prénom du Signataire

\n

 

\n
\n

 

\n
\n

 

\n

 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

\n

 

' + dest = <_io.BufferedRandom name='./temp_direct/Convention_43598_75645.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:08:17] "POST /myclass/api/Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:08:17.822340 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:08:26] "POST /myclass/api/Get_Editable_Document_By_Partner_By_Collection/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:08:43.268318 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:08:44] "POST /myclass/api/Get_Given_E_Document_Not_Signed_No_Token/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:09:19.718510 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '


 

\n

\n

\n
\n
\n

 

\n\n\n\n\n\n\n\n
\n

Entre L\'Organisme de formation    ci-après nommé l\'Organisme de formation
Situé :    
Déclation d\'activité :   Représenté par : [PDG]
Signataire dûment habilité aux fins des présentes :  prenom nonn 
Contact :   

\n

 

\n
\n

Et le bénéciaire : FRANCE TRAVAIL   Réprésenté par
(Ci-aprés nommé le client)
Situé : Bat D1 - 4 ème étage 5 rue Saint-Christophe BP 1067  97200   
Représenté par :  FT contact_prenom FT contact_prenom  en qualité de
Contact : francetravail1@francetravail.fr 

\n

 

\n
\n
\n

Est conclue la convention suivante. 

\n

Article 1 : Objet, nature, et durée de la formation
Le bénéciaire entend faire participer une partie de son personnel à l\'action de formation suivante organisée par l\'organisme de formation Colas Rail 

\n


Formation :  CONDUIRE UN PROJET 

Durée : 15.0   heure (s) 
Lieu de formation :vile sit1 
Dates de formation : 17/11/2025  18/11/2025 
Nom formateur : nom_Enseignant_2 Prenom_2 

\n

Article 2 : Programme de la formation
La description detaillée du programme (méthodes pédagogiques, évaluation) est fourni au client

\n

Article 3 : Engagement de participation à la formation
Le bénéciaire s\'engage à assurer la présence du / des stagiaire/s aux dates et lieux prévus ci-dessus.
Liste des stagiaires : 

\n
xddd   qsdqsd   mysy1000formation+04@gmail.com
\n

Article 4 : Prix de la formation 
La formation est réglée en totalité par le client
Coût pédagogique par stagiaire : 1500.0 

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Article 5 : Modalités de réglement
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article 6 : Moyes pédagogiques et techniques mises en oeuvre
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Article x : Litiges
orem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

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Paris , 12/11/2025 

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Pour l\'organisme de formation
prenom  nonn

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Pour le client :
Nom & Prénom du Signataire

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\n

 

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Colas Rail 
Téléphone : 
Site web : https://colasrail.com/ 

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\t
Signature Client

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Par la presente, L\'Organisme de formation  Colas Rail   
Situé : rue de la république 77 paris , déclation d\'activité :  NDA-001254 ,
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Atteste que :  part 1 part nom 1  
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a suivi la formation CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   vile sit1
Dates de formation :  29/09/2025 au 07/10/2025
Nom formateur :  nom_Enseignant_2 Prenom_2
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Contenu de la formation  :  
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Paris , 12/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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Par la presente, L\'Organisme de formation  Colas Rail   
Situé : rue de la république 77 paris , déclation d\'activité :  NDA-001254 ,
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Atteste que :  part 1 part nom 1  
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a suivi la formation CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   vile sit1
Dates de formation :  29/09/2025 au 07/10/2025
Nom formateur :  nom_Enseignant_2 Prenom_2
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Contenu de la formation  :  
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Paris , 12/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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Par la presente, L\'Organisme de formation  Colas Rail   
Situé : rue de la république 77 paris , déclation d\'activité :  NDA-001254 ,
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Atteste que :  part 1 part nom 1  
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a suivi la formation CONDUIRE UN PROJET
Durée :  15.0 heure (s)
Lieu de formation :   vile sit1
Dates de formation :  29/09/2025 au 07/10/2025
Nom formateur :  nom_Enseignant_2 Prenom_2
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Contenu de la formation  :  
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Paris , 12/11/2025
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 Colas Rail 
Téléphone : 07 69 20 39 45 
Email :  mysytraining+dev@gmail.com 
Site :  https://colasrail.com/ 

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Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': None, 'height': None, 'align': None, 'id': None} +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'sRGB' 41 1 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 54 4 +DEBUG:PIL.PngImagePlugin:STREAM b'cHRM' 70 32 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 114 9 +DEBUG:PIL.PngImagePlugin:STREAM b'tIME' 135 7 +DEBUG:PIL.PngImagePlugin:b'tIME' 135 7 (unknown) +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 154 8192 +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'gAMA' 41 4 +DEBUG:PIL.PngImagePlugin:STREAM b'pHYs' 57 9 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 28781 +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:27:47] "POST /myclass/api/Prepare_and_Send_Attestation_From_Session_By_Email/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:27:47.876980 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:27:47] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:01.045287 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:01.065867 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:01.085864 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:01] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:01.111397 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:01] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:01] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:01] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:01.145414 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:01.156414 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:01.195409 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:01] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:01] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:01] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:07.694126 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:07] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:13.868104 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:13] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.476157 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.520178 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.548179 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.585259 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.607260 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.610257 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.645275 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.674598 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.715600 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.756189 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.777702 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.800258 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.840885 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.865467 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_List_Type_Evaluation/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.880473 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.902488 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_List_Class_Evaluation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.935070 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:29.951091 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:29.981134 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:29] "POST /myclass/api/Get_List_Unite_Enseignement_Of_Given_Class/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:30.001129 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:30.022128 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:30] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:30.050146 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:30.069695 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:30.092689 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:30] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:30.140711 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:31.884206 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:31.894195 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:31.931084 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Class_Niveau_Formation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/getRecodedClassImage/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:35.512096 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:35.539119 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:35.589546 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:35.620550 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:35.647545 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Conventions_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:35.708094 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:35.750103 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:35.780643 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:35] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:35.833663 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:35.852179 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:35.875706 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:30:35.907403 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:36] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:36] "POST /myclass/api/Get_List_Formulaire_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:36] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:36] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:36] "POST /myclass/api/Get_Given_Class_List_Default_Documents/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:40.598425 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:41] "POST /myclass/api/Update_Class_Default_Document/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:44.270385 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:44] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:46.318319 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:46] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:30:51.204099 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:30:51] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:02.153083 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.158083 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.164083 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:02.182186 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.196151 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:02.239360 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.245358 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.253356 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.261469 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.271459 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:02.286403 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:02.310360 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:02.319482 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.323586 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.334125 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:02.348104 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:02.363061 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:02] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:03] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:05] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:06.888978 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:06.895551 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:06.902914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:06] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:06.929131 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:06.939130 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:06] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:06.951816 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:31:06.963593 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:06] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:06] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:06] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:06] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:08.825044 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:08] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:13.655286 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:13] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:17.971605 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:17] "POST /myclass/api/Init_Attestation_Formation_With_Template_For_All_Inscription/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:31:18.041910 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:31:18] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:17.151976 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:17] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:25.564410 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:32:25.567394 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:25] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:26] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:32.466102 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:32] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:51.405611 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:32:51.408611 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:32:51.412063 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:32:51.417273 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:32:51.420316 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_Partner_All_Class_Few_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:51.427314 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:32:51.433314 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:51.441320 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_Partner_Session_Ftion_Reduice_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:51.448641 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:32:51.449642 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_List_Unite_Enseignement_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:51] "POST /myclass/api/Get_List_Partner_Apprenant/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:52] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:52] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:32:58.476560 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:32:58] "POST /myclass/api/Get_Apprenant_List_Partner_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:34:09.038173 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:34:09] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:11.211262 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:11.216260 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:11.223268 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:11.229377 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:11.243902 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:11.247889 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:11.274889 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:11.286892 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:11.290992 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:11.298996 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:11.309914 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:11.321899 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:11] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:13] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:15] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:16.998325 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:17.002392 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:17.005334 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:17.011151 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:17.020136 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:17.029158 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:17.048675 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:17] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:17] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:19.871407 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:19.874315 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:19] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:21] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:35:28.240281 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:35:28.245179 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:28] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:35:28] "POST /myclass/api/Get_List_Convocations_Stagiaire_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:52.845576 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:52.852580 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:52.859578 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:52.863578 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:52.877614 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:52.897099 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:52.903095 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:52.912097 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:52.930097 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:52.946103 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:52.950612 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:52.957118 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:52] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:53.374185 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:53.382195 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:53.399710 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:53.405708 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:53.447719 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:53.461754 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:53.493805 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:53.503317 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:53.507317 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:53.532313 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:53.556316 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:43:53.580321 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:43:53.621866 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:53] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:54] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:54] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:56] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:43:56] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:09.054492 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:09] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:32.328744 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.330752 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.339741 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.344742 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:32.373742 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:32.418396 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.424390 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.430029 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.440030 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:32.453024 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.463023 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:32.482030 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:32.498059 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.510030 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:32.521049 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.539578 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:32.566162 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:32] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:34] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:35] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:36.805237 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:36.811986 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:36.814985 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:36.819161 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:36.828117 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:45:36.835806 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:36.846201 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:36] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:36] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:36] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:36] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:36] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:36] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:45:39.113665 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:45:39] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:04.484553 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:04] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:05.369693 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:05] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.044523 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.063524 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.088535 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.107054 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.115053 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.133651 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.152385 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.171398 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.181421 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.201964 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.220955 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.232177 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.263755 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.282750 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.298265 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:14.331296 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:14.345794 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:14] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:15] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:16] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:17.616066 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:17.622079 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:17.628065 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:17.638073 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:17.652071 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:17] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:17.672071 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 13:46:17.680072 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:17] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:21.480700 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:21] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 13:46:26.161119 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 13:46:26] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 18:37:10.722026 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 18:37:10.723025 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 18:37:10.723025 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 18:37:10.723025 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 18:37:10.724025 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +INFO:werkzeug:WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. + * Running on http://localhost:5001 +INFO:werkzeug:Press CTRL+C to quit +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 18:38:57.460867 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 18:38:57.461872 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 18:38:57.461872 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 18:38:57.478504 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 18:38:57.478504 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:werkzeug: * Detected change in 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\email_mgt.py', reloading +INFO:werkzeug: * Restarting with stat +DEBUG:matplotlib:matplotlib data path: C:\Users\Cherif\Documents\myclass.com\Siteweb\Elyos_Ftion_Continue\Ela_back\Back_Office\venv\Lib\site-packages\matplotlib\mpl-data +DEBUG:matplotlib:CONFIGDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib:interactive is False +DEBUG:matplotlib:platform is win32 +DEBUG:matplotlib:CACHEDIR=C:\Users\Cherif\.matplotlib +DEBUG:matplotlib.font_manager:Using fontManager instance from C:\Users\Cherif\.matplotlib\fontlist-v390.json +INFO:root:2025-11-12 18:44:40.740629 : ++++ ENVIRONNEMENT DEVELOPPEMENT ++++ +INFO:root:2025-11-12 18:44:40.740629 : ++ DATABASE mongodb://localhost:27017/cherifdb_dev_fi ++ +INFO:root:2025-11-12 18:44:40.741628 : ++ DBNAME Database(MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True), 'cherifdb_dev_fi') ++ +INFO:root:2025-11-12 18:44:40.741628 : ++ FLASK PORT 5001 ++ +INFO:root:2025-11-12 18:44:40.741628 : ++ LMS_BAS_URL mysy-hosting.com/ ++ +WARNING:werkzeug: * Debugger is active! +INFO:werkzeug: * Debugger PIN: 479-264-725 +INFO:root:2025-11-12 18:44:40.860224 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:44:40] "GET /myclass/api/ManualSendInvoiceEmailRIB_CIC_BureauVallee HTTP/1.1" 308 - +INFO:root:2025-11-12 18:44:40.871212 : Security check : IP adresse '127.0.0.1' connected +DEBUG:xhtml2pdf.document:pisaDocument options: + src = '\n\n\n\n\t
\n\t\tMysy Training Logo \n\t
\n\t\n\t\t
\n\t\t\t
\n\t\t\t\t\n\t\t\t\t
\n\t\t\t\t\n\t\t\t\t\tBVD Fr (Bureau Vallée)
\n\t\t\t\t\t25 rue du Gros Caillou
\n\t\t\t\t\t78340 – Les Clayes-sous-Bois- France
\n\n\t\t\t\t
\n\n\n\t\t\t\t\n\n\t\t\t\t\tFacture n° FACT_20251020\n\n\n\t\t\t\t
\n\n\n\n\t\t\t\t\n\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t
Date de facture: 31/10/2025 Date échéance : 15/11/2025
\n\n\t\t\t\t\n\t\t\t\t\tPériode : 01/10/2025 au 31/10/2025 \n\t\t\t\t\n\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t
DescriptionQuantitéPrix unitaire (HT)Montant (HT)
Prestation de service
\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t
23 jours550 € HT12 650 € HT
\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n\t\t\t\t\t\t\t\n\n\n\t\t\t\t\t\t\n\n\t\t\t\t\t
Déplacement Bureau - PapetShow -\n\t\t\t\t\t\t\t\t15/10/2025 et 16/10/2025
\n\t\t\t\t\t\t\t\tDeplacement bureau <=> papet show (Aller / retour) : 16,8 km X 2 X 2 jrs = 67,2 Km\n\t\t\t\t\t\t\t\t\t(https://www.impots.gouv.fr/simulateur-bareme-kilometrique) 47 € HT
 
Déplacement Bureau - Magasin Paris 5 -\n\t\t\t\t\t\t\t\t8/10/2025
\n\t\t\t\t\t\t\t\tDeplacement bureau <=> Magasin Paris 5 (Aller / retour) : 37,6 km X 2 = 75,2 Km\n\t\t\t\t\t\t\t\t\t(https://www.impots.gouv.fr/simulateur-bareme-kilometrique) 52 € HT
\n\t\t\t\t\n\n\n\t\t\t\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t
    Montant HT: 12 749   €
    TVA : 2 549,8   €
    Montant TTC : 15 298,8  €
\n\n\t\t\t
\n\n\t\t\t\n\t\t\t\tRèglement : Virement bancaire \n\n\n\t\t\t

\n\t\t\t\t> Relevé d\'identité bancaire : MySy Training Technology, 2 place des magnolias, 77680, Roissy en\n\t\t\t\t\tbrie \n\t\t\t

\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\n\n\n\t\t\t\t\n\n\t\t\t
BanqueCode agenceNuméro de compteClé RIB
30087338560002128550340
\n\n\t\t\t

\n\t\t\t\t> Identification internationale\n\t\t\t

\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\n\t\t\t\t\t\n\n\n\n\t\t\t\t\n\n\t\t\t
IBANCode BIC
FR76 3008 7338 5600 0212 8550 340CMCIFRPP
\n\n\t\t\n\n\t\n\n\t
\n\t\n\n\t\tTermes et conditions
\n\n\t\tPas d\'escompte accordé pour paiement anticipé.
\n\t\tEn cas de non-paiement à la date d\'échéance, des pénalités calculées à trois fois le taux d\'intérêt légal\n\t\tseront appliquées.
\n\t\tTout retard de paiement entraînera une indemnité forfaitaire pour frais de recouvrement de 40€.
\n\n\t\n\n\n\t
\n\t\t\n\n\t\t\tMySy Training
\n\n\t\t\tMySy Training Technology (MTT), société par actions simplifiée au capital de 10 000 euros, dont le siège\n\t\t\tsocial est\n\t\t\tsitué 2, place des magnolias, 77680, Roissy en Brie, immatriculée au Registre du Commerce et des\n\t\t\tSociétés sous le numéro 917 500 860 R.C.S. Melun\n\n\t\t\n\t
\n\n\n' + dest = <_io.BufferedRandom name='./Invoices/invoice_FACT_20251020.pdf'> + path = '' + link_callback = None + xhtml = False + context_meta = None +DEBUG:xhtml2pdf.files:FileObject './../img/MYSY-LOGO-BLUE.png', Basepath: 'C:\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__' +DEBUG:xhtml2pdf.files:URLParts: ParseResult(scheme='c', netloc='', path='\\Users\\Cherif\\Documents\\myclass.com\\Siteweb\\Elyos_Ftion_Initiale\\Ela_back\\Back_Office_FI\\__dummy__', params='', query='', fragment=''), 'c' +DEBUG:xhtml2pdf.tags:Parsing img tag, src: +DEBUG:xhtml2pdf.tags:Attrs: {'src': , 'width': 75.0, 'height': None, 'align': None, 'id': None} +DEBUG:xhtml2pdf.files:Unrecognized scheme, assuming local file path +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'tEXt' 41 25 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 6645 +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None, None, None] +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:None +DEBUG:xhtml2pdf.tables:Col widths: [None, None] +DEBUG:PIL.PngImagePlugin:STREAM b'IHDR' 16 13 +DEBUG:PIL.PngImagePlugin:STREAM b'tEXt' 41 25 +DEBUG:PIL.PngImagePlugin:STREAM b'IDAT' 78 6645 +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:44:41] "GET /myclass/api/ManualSendInvoiceEmailRIB_CIC_BureauVallee/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:46:47.445192 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:47] "POST /myclass/api/partner_login/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:46:48.637091 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:46:48.643078 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:46:48.648080 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:46:48.655834 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:46:48.665308 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:46:48.715820 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:46:48.719721 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:46:48.729748 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:46:48.749727 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:46:48.761823 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/Get_List_Class_domaine/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:46:48.772820 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/Get_Ref_Pedagogique_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:46:48.794867 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/Get_List_Class_Categorie/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/Get_List_class_metier/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:46:48] "POST /myclass/api/find_partner_class_like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:37.352158 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:37.355583 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:37.357707 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:37.362227 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:37.367901 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:37.371541 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:37.376541 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:37.387543 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:37.393415 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:37.400482 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:37.405593 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:37.410509 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:37] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:38] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:40.403402 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:40.407264 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:40.409968 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:40.414249 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:40.416246 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:40.420246 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:40] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:40.429132 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:40] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:40] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:40] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:40] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:40] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:42.616057 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:48:42.620916 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:42] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:48:53.758487 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:48:53] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:49:06.620564 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:49:06] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.204863 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:50:41.208867 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.220494 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:50:41.225494 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.239508 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.404064 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:50:41.409469 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:50:41.414116 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:50:41.421698 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.429606 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.440114 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.444108 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:50:41.446109 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.459965 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.464973 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:50:41.472973 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:50:41.485491 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:41] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:42] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:50:43] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:51:17.674606 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:51:17.680602 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:51:17.689587 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:51:17.693605 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:51:17.702597 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:51:17.714823 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:51:17.741825 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:17] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:17] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:17] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:17] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:51:22.008235 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:22] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:51:26.294943 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:26] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:51:32.579039 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:51:32] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:29.247811 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:29] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.244810 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.247318 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.255386 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.273906 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.293902 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.314901 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.321901 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.324900 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.330904 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.349919 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.352922 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.367957 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.385953 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.411957 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.415954 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:52:47.423955 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:52:47.438952 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:47] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:48] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:52:50] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:53:23.571133 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:53:23.577142 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:53:23.585136 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:53:23.597144 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:23] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:53:23.605136 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:23] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:23] "POST /myclass/api/GetAllClassStagiaire/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:53:23.624143 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:23] "POST /myclass/api/GetSessionFormation/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:53:23.639134 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:23] "POST /myclass/api/Get_Session_Sequence_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:23] "POST /myclass/api/GetTableauEmargement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:23] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:53:26.717909 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:26] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:53:34.603595 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:53:34] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:54:13.420854 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:54:13] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:55:15.682022 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:55:15] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:55:39.776933 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:55:39] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:56:05.766172 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:56:05] "POST /myclass/api/Get_Attestion_By_Session/ HTTP/1.1" 200 - +INFO:root:2025-11-12 18:56:17.727260 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 18:56:17.736258 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:56:17] "POST /myclass/api/Get_List_Modele_Attestion_Formation_With_Filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 18:56:17] "POST /myclass/api/Get_Given_Class_List_Default_Documents_For_Given_Type_Doc/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.524201 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.533203 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.545203 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.553204 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.556201 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.599724 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.603728 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.606723 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.610723 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.615721 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.618724 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.630725 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.635725 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.643724 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.652726 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:04:29.667721 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:04:29.688826 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:29] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:30] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:04:30] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:12.960158 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:12.963159 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:12.965160 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:12] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:12.976219 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:12] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:12.986221 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:12] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:12] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:13.031219 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:13.033219 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:13.036218 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:13.039265 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Get_Partner_Object_Specific_Valide_Displayed_Fields/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:13.047221 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:13.048222 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Get_List_Ressource_Humaine_no_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Get_List_Ressource_Materielle_no_filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:13.057220 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:13.061247 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Get_List_Partner_Or_Default_session_step/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:13.070225 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:13.072226 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:07:13.076738 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/GetPartnerAttestation_Certificat/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:13.088737 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Is_Partnair_Has_Digital_Signature/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/Get_List_Site_Formation_with_filter/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/get_partner_class/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:13] "POST /myclass/api/GetAllValideSessionPartner_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:14] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:21.570666 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:21] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:07:48.651667 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:07:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:19:29.788002 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:19:29] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:25:05.437956 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:25:05.443957 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:25:05.445957 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:25:05] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:25:05.456956 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:25:05.466951 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:25:05] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:25:05] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:25:05] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:25:05.485960 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:25:05] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:28:45.976669 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:28:45.980676 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:28:45.985674 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:28:45] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:28:45.994183 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:28:46.005698 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:28:46] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:28:46] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:28:46] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:28:46.031265 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:28:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:33:20.699836 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:33:20.708349 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:33:20] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:33:20.714351 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:33:20.721348 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:33:20] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:33:20] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:33:20.736350 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:33:20] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:33:20.753356 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:33:20] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:39:09.161634 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:39:09.172003 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:39:09] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:39:09.181001 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:39:09.197009 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:39:09] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:39:09] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:39:09.213044 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:root:2025-11-12 20:39:09.214042 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:39:09] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:39:09] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:50:27.344139 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:50:27.350308 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:50:27.354308 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:50:27] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:50:27.365215 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 20:50:27.376694 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:50:27] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:50:27] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:50:27] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:50:27.393587 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:50:27] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 20:51:26.222104 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:51:26] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/3Bll9zh0pefA-K_BToa9x99dBVJnVsXrZg/691478b1995b26cde9611ada HTTP/1.1" 200 - +INFO:root:2025-11-12 20:51:28.869555 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 20:51:28] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/3Bll9zh0pefA-K_BToa9x99dBVJnVsXrZg/691478b1995b26cde9611ada HTTP/1.1" 304 - +INFO:root:2025-11-12 21:57:18.946661 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:20] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 21:57:38.809760 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:38] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 21:57:43.644058 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 21:57:43.648551 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 21:57:43.654562 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 21:57:43.668565 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 21:57:43.693915 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 21:57:43.699913 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 21:57:43.710918 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 21:57:43.717913 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 21:57:48.000364 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 21:57:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:00:06.539397 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:06.543394 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:06.548393 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:06.554396 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:06.561394 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:00:06.578394 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:00:06.583394 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:06.588377 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:06] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:00:40.735501 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:40.739501 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:40.743518 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:40.748503 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:00:40.753502 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:00:40.764501 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:00:40.773501 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:00:40.789506 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:00:40] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:02:39.331689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:02:39.337439 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:02:39.342833 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:02:39.346829 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:02:39.350831 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:02:39.361830 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:02:39.374861 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:02:39.385832 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:02:39] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:03:16.464407 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:03:16.559985 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:03:16] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:03:16] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:08:03.065672 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:08:04] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:10:29.816888 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:10:29] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:03.524382 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:03] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:17.135837 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:27.859442 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:11:27.866443 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:27] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:27.874442 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:11:27.887441 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:11:27.892444 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:27] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:27] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:27] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:27.927443 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:30] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:35.011004 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:35] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:37.341694 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:11:37.348678 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:11:37.358243 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:11:37.366227 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:37.376225 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:37.389239 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:37.411225 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:37.427226 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:37] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:11:44.011395 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:11:44.140624 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:44] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:11:44] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:16.226337 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:16] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:26.714777 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:26] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:33.827974 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:33] "POST /myclass/api/getRecodedImage/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:33.838980 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:14:33.846486 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:14:33.857495 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:33] "POST /myclass/api/LMS_Get_Partner_Data/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:33] "POST /myclass/api/Get_Nb_User_Internal_Mail_Not_Read/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:33.883493 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:14:33.883493 : Connexion du partner recid = 43598820dd270936c3d2fd822717d0f18f194b1a1b894aaf89 OK. Mise à jour du firstconnexion et/ou lastconnexion : OK +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:33] "POST /myclass/api/get_partner_account/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:35] "POST /myclass/api/Get_Partner_List_Partner_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:40.760771 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:40] "POST /myclass/api/Get_Partner_List_Partner_Client_with_filter_Like/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:43.250827 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:14:43.252830 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:14:43.272378 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:14:43.278381 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:43.288380 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:43.295379 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:43.307381 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:43.318379 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:43] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:14:45.186382 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:14:45.272748 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:45] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:14:45] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:15:44.878687 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:15:44.882689 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:15:44.890685 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:15:44.893240 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:15:44.897803 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:15:44.906675 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:15:44.914681 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:15:44.929076 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:44] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:15:49.270794 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:15:49.354892 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:15:49] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:16:17.183232 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:16:17] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/3Bll9zh0pefA-K_BToa9x99dBVJnVsXrZg/68fb7dc779119ff4d421ae9a HTTP/1.1" 200 - +INFO:root:2025-11-12 22:16:21.047743 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:16:21] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/3Bll9zh0pefA-K_BToa9x99dBVJnVsXrZg/68fb7dc779119ff4d421ae9a HTTP/1.1" 304 - +INFO:root:2025-11-12 22:17:14.623948 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:14] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:17.913140 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:17] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:27.823797 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:27] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:30.240409 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:30] "GET /myclass/api/Get_Stored_Downloaded_File_From_Id/3Bll9zh0pefA-K_BToa9x99dBVJnVsXrZg/68984cc890ff4690b90d985d HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:38.513262 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:38] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:46.524819 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:17:46.527815 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:17:46.530838 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:17:46.536816 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:46.551819 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:46.560831 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:46.567845 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:17:46.572872 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:46] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:48.425235 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:17:48.525227 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:17:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:04.449902 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:04] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:48.760980 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:48.763022 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:48.769981 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:48.779982 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:48.785980 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:48.789987 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:48.800991 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:48.805988 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:48] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:50.612677 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:50] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:50.700797 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:50] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:59.213180 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:59.214181 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:59.218182 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:59.222183 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:59.229200 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:59.235260 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:20:59.242236 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:20:59.255733 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:20:59] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:21:00.374421 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:21:00.480535 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:21:14.299467 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:21:14.301468 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:21:14.304470 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:21:14.307466 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_Client_Type_List/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:21:14.315514 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:21:14.318922 : Security check : IP adresse '127.0.0.1' connected +INFO:root:2025-11-12 22:21:14.326950 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_List_Type_Organisme_Financement/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_List_Type_Pouvoir_Public/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_List_Groupe_Client/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:21:14.343928 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_List_Paiement_Condition/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_Given_Partner_Client_From_Id/ HTTP/1.1" 200 - +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:14] "POST /myclass/api/Get_List_Entity_Contact/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:21:20.590202 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:20] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:21:20.676491 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:21:20] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:23:24.317864 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:23:24] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:23:48.628751 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:23:48] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:23:52.596826 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:23:52] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:23:56.081814 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:23:56] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:24:00.028426 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:24:00] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - +INFO:root:2025-11-12 22:24:07.779063 : Security check : IP adresse '127.0.0.1' connected +INFO:werkzeug:127.0.0.1 - - [12/Nov/2025 22:24:07] "POST /myclass/api/Get_List_object_owner_collection_Stored_Files_With_Filter/ HTTP/1.1" 200 - diff --git a/Session_Formation.py b/Session_Formation.py index 08ee1b0..d508865 100644 --- a/Session_Formation.py +++ b/Session_Formation.py @@ -6174,7 +6174,7 @@ def Prepare_and_Send_Convention_From_Session_By_Email(tab_files, Folder, diction - return True, " Les conventions ont été correctement envoyées par emails" + return True, " Les conventions ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -6370,7 +6370,7 @@ def Prepare_and_Send_Convention_From_Session_For_Selected_Inscrit_By_Email(tab_f - return True, " Les conventions ont été correctement envoyées par emails" + return True, " Les conventions ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -6694,7 +6694,7 @@ def Prepare_and_Send_Default_Convention_From_Session_By_Email(tab_files, Folder, tab_files_to_attache_to_mail = [] - return True, " Les conventions ont été correctement envoyées par emails" + return True, " Les conventions ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -8038,7 +8038,7 @@ def Prepare_and_Send_Attestation_From_Session_By_PDF( diction): is_warning_message = "0" - warning_message = "Les attestation ont été correctement envoyées par emails avec l'attention suivante : " + warning_message = "Les attestation ont été correctement envoyées par email avec l'attention suivante : " for attestation_formation_data in MYSY_GV.dbname['attestation_formation'].find({ 'partner_owner_recid':str(my_partner['recid']), 'valide':"1", @@ -8608,7 +8608,7 @@ def Prepare_and_Send_Convocation_From_Session_By_Email(tab_files, Folder, dictio str(str(courrier_template_data['_id']))) - return True, " Les convocations ont été correctement envoyées par emails" + return True, " Les convocations ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -8748,7 +8748,7 @@ def Prepare_and_Send_Convocation_From_Session_For_Selected_Inscrit_By_Email(tab_ str(str(courrier_template_data['_id']))) - return True, " Les convocations ont été correctement envoyées par emails" + return True, " Les convocations ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -9005,7 +9005,7 @@ def Sent_Convocation_Stagiaire_By_Email(tab_files, Folder, diction): new_diction['list_class_id'] = tab_class new_diction['list_client_id'] = [] new_diction['list_apprenant_id'] = tab_apprenant - new_diction['list_sequence_session_id'] = tab_sequence_session # zzzzzz + new_diction['list_sequence_session_id'] = tab_sequence_session local_status, local_retval = mycommon.Get_Dictionnary_data_For_Template(new_diction) @@ -9224,9 +9224,32 @@ def Sent_Convocation_Stagiaire_By_Email(tab_files, Folder, diction): new_file['file_name_to_store'] = outputFilename + tab_key_word = "convocation,"+str(class_data['external_code'])+","+str(session_data['code_session']) + new_file['tab_key_word'] = tab_key_word + + tab_related_collection = [] + if( class_data): + node_class = {} + node_class['related_collection'] = 'myclass' + node_class['related_collection_id'] = str(class_data['_id']) + tab_related_collection.append(node_class) + + if (session_data): + node_session = {} + node_session['related_collection'] = 'session_formation' + node_session['related_collection_id'] = str(session_data['_id']) + tab_related_collection.append(node_session) + + if (inscription_data): + node_inscrit = {} + node_inscrit['related_collection'] = 'inscription' + node_inscrit['related_collection_id'] = str(inscription_data['_id']) + tab_related_collection.append(node_inscrit) + + #print(" ### new_file new_file = ", new_file) local_status, local_retval = attached_file_mgt.Internal_Usage_Store_User_Downloaded_File( - MYSY_GV.upload_folder, new_file) + MYSY_GV.upload_folder, new_file, tab_related_collection) if (local_status is False): print(" ## WARINNGGG Impossible de stocker le fichier de Convocation ") @@ -9345,7 +9368,7 @@ def Prepare_and_Send_Attestation_From_Session_By_Email(tab_files, Folder, dictio is_warning_message = "0" - warning_message = "Les attestation ont été correctement envoyées par emails avec l'attention suivante : " + warning_message = "Les attestation ont été correctement envoyées par email avec l'attention suivante : " for attestation_formation_data in MYSY_GV.dbname['attestation_formation'].find({"session_id":str(diction['session_id']), 'partner_owner_recid':str(my_partner['recid']), 'valide':"1", @@ -9421,7 +9444,7 @@ def Prepare_and_Send_Attestation_From_Session_By_Email(tab_files, Folder, dictio if( is_warning_message == "1"): return True, str(warning_message) - return True, " Les attestations ont été correctement envoyées par emails" + return True, " Les attestations ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() @@ -9901,9 +9924,28 @@ def Sent_Attestation_Stagiaire_By_Email(tab_files, Folder, diction): new_file['file_name_to_store'] = outputFilename + tab_related_collection = [] + if (class_data): + node_class = {} + node_class['related_collection'] = 'myclass' + node_class['related_collection_id'] = str(class_data['_id']) + tab_related_collection.append(node_class) + + if (session_data): + node_session = {} + node_session['related_collection'] = 'session_formation' + node_session['related_collection_id'] = str(session_data['_id']) + tab_related_collection.append(node_session) + + if (inscription_data): + node_inscrit = {} + node_inscrit['related_collection'] = 'inscription' + node_inscrit['related_collection_id'] = str(inscription_data['_id']) + tab_related_collection.append(node_inscrit) + # print(" ### new_file new_file = ", new_file) local_status, local_retval = attached_file_mgt.Internal_Usage_Store_User_Downloaded_File( - MYSY_GV.upload_folder, new_file) + MYSY_GV.upload_folder, new_file, tab_related_collection) if (local_status is False): print(" ## WARNINGGG Impossible de stocker le fichier d'attestation") diff --git a/attached_file_mgt.py b/attached_file_mgt.py index 375a23f..3322dc2 100644 --- a/attached_file_mgt.py +++ b/attached_file_mgt.py @@ -86,7 +86,7 @@ def Store_User_Downloaded_File(file=None, Folder=None, diction=None): Verification des input acceptés """ field_list = ['token', 'file_business_object', 'file_name', 'status','object_owner_collection', - 'object_owner_id', 'type_document', 'metadata_field'] + 'object_owner_id', 'type_document', 'metadata_field', 'tab_key_word'] incom_keys = diction.keys() for val in incom_keys: if val not in field_list and val.startswith('my_') is False: @@ -159,6 +159,33 @@ def Store_User_Downloaded_File(file=None, Folder=None, diction=None): elif ( diction['metadata_field'] and str( diction['metadata_field'] ) <= 500 ) : metadata_field = diction['metadata_field'] + """ + La table des mots clés contient au max 5 mots, chanque mot ne doit pas faire plus 50 caracactères + """ + tab_key_word = [] + if ("tab_key_word" in diction.keys() and diction['tab_key_word']): + + tab_tmp = str(diction['tab_key_word']).replace(";", ",").split(",") + if (len(tab_tmp) > 5): + mycommon.myprint(str(inspect.stack()[0][3]) + " Il y a plus de 5 mots clés de recherche ") + return False, " Il y a plus de 5 mots clés de recherche " + + for tmp in tab_tmp: + if (tmp): + if (len(tmp) > 50): + mycommon.myprint( + str(inspect.stack()[0][3]) + "Le mot clé " + str(tmp) + " fait plus de 50 caractères") + return False, " Le mot clé " + str(tmp) + " fait plus de 50 caractères " + + tab_key_word.append(str(tmp)) + + tab_related_collection = [] + local_node = {} + local_node['related_collection'] = diction['object_owner_collection'] + local_node['related_collection_id'] = diction['object_owner_id'] + tab_related_collection.append(local_node) + + object_owner_id = "" if ("object_owner_id" in diction.keys()): @@ -185,6 +212,8 @@ def Store_User_Downloaded_File(file=None, Folder=None, diction=None): mydata['file_name'] = file.filename mydata['type_document'] = type_document mydata['metadata_field'] = metadata_field + mydata['tab_key_word'] = tab_key_word + mydata['tab_related_collection'] = tab_related_collection mydata['full_path'] = Global_file_name mydata['file_extention'] = file_extention mydata['object_owner_collection'] = object_owner_collection @@ -225,7 +254,7 @@ Important : : 24/12/2024 - metadata_field : est un champs de texte qui prends au maximum 500 caractère pour stocker des metadata pour effectuer des recherches """ -def Internal_Usage_Store_User_Downloaded_File(Folder=None, diction=None): +def Internal_Usage_Store_User_Downloaded_File(Folder=None, diction=None, tab_related_collection=None): try: full_file_path = "" @@ -235,7 +264,7 @@ def Internal_Usage_Store_User_Downloaded_File(Folder=None, diction=None): Verification des input acceptés """ field_list = ['token', 'file_business_object', 'file_name', 'status','object_owner_collection', 'object_owner_id', - 'file_name_to_store', 'type_document', 'metadata_field'] + 'file_name_to_store', 'type_document', 'metadata_field', 'tab_key_word'] incom_keys = diction.keys() for val in incom_keys: if val not in field_list and val.startswith('my_') is False: @@ -324,6 +353,35 @@ def Internal_Usage_Store_User_Downloaded_File(Folder=None, diction=None): if diction['document_display_order']: document_display_order = diction['document_display_order'] + + """ + La table des mots clés contient au max 5 mots, chanque mot ne doit pas faire plus 50 caracactères + """ + tab_key_word = [] + if ("tab_key_word" in diction.keys() and diction['tab_key_word']): + + tab_tmp = str(diction['tab_key_word']).replace(";", ",").split(",") + if (len(tab_tmp) > 5): + mycommon.myprint(str(inspect.stack()[0][3]) + " Il y a plus de 5 mots clés de recherche ") + return False, " Il y a plus de 5 mots clés de recherche " + + for tmp in tab_tmp: + if (tmp): + if (len(tmp) > 50): + mycommon.myprint( + str(inspect.stack()[0][3]) + "Le mot clé " + str(tmp) + " fait plus de 50 caractères") + return False, " Le mot clé " + str(tmp) + " fait plus de 50 caractères " + + tab_key_word.append(str(tmp)) + + + local_node = {} + local_node['related_collection'] = diction['object_owner_collection'] + local_node['related_collection_id'] = diction['object_owner_id'] + + tab_related_collection.append(local_node) + + mydata = {} mydata['file_business_object'] = file_business_object mydata['date_update'] = str(datetime.now()) @@ -331,6 +389,11 @@ def Internal_Usage_Store_User_Downloaded_File(Folder=None, diction=None): mydata['full_path'] = Global_file_name mydata['type_document'] = type_document mydata['metadata_field'] = metadata_field + + + mydata['tab_key_word'] = tab_key_word + mydata['tab_related_collection'] = tab_related_collection + mydata['file_extention'] = file_extention mydata['object_owner_collection'] = object_owner_collection mydata['object_owner_id'] = object_owner_id @@ -512,7 +575,10 @@ def Get_Stored_Downloaded_File_From_Id(diction): if diction['file_name']: file_name = diction['file_name'] - + if( not str(diction['_id']) ): + mycommon.myprint( + str(inspect.stack()[0][3]) + " L'identifiant du fichier est invalide ") + return False, " L'identifiant du fichier est invalide ", """ Verifier la validité de l'identifiant @@ -807,6 +873,11 @@ def Get_List_object_owner_collection_Stored_Files(diction): else: ret_file['file_extention'] = "file_extention" + if ("tab_key_word" in retval.keys()): + ret_file['tab_key_word'] = retval['tab_key_word'] + else: + ret_file['tab_key_word'] = [] + """ Recuperation du nom du client @@ -826,8 +897,87 @@ def Get_List_object_owner_collection_Stored_Files(diction): ret_file['client_raison_sociale'] = client_raison_sociale ret_file['client_nom'] = client_nom + tab_related_collection = [] + """ + 09/11/2025 - Traitement du contenu de la 'tab_related_collection' + - aller y chercher si on a un apprenant ou client ou un RH (les tuteurs par exemple) + """ + if ("tab_related_collection" in retval.keys() and retval['tab_related_collection']): + for tmp_data in retval['tab_related_collection']: + if ('related_collection' in tmp_data.keys() and tmp_data['related_collection'] and + 'related_collection_id' in tmp_data.keys() and tmp_data['related_collection_id']): + + if (tmp_data['related_collection'] == "partner_client" and tmp_data['related_collection_id']): + # Aller chercher les données du client + local_client_data = MYSY_GV.dbname['partner_client'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', 'locked': '0', + 'partner_owner_recid': str(my_partner['recid'])}, + {'raison_sociale': 1, 'nom': 1, 'email': 1, '_id': 1}) + + local_node = {} + local_node['related_collection'] = 'partner_client' + local_node['related_collection_data'] = local_client_data + tab_related_collection.append(local_node) + + ret_file['related_client_nom'] = client_raison_sociale + elif (tmp_data['related_collection'] == "inscription" and tmp_data['related_collection_id']): + # Aller chercher les données de l'inscrit + + local_id = "" + + if type(tmp_data['related_collection_id']) == list: + local_id = tmp_data['related_collection_id'][0] + else: + local_id = tmp_data['related_collection_id'] + + local_inscrit_data = MYSY_GV.dbname['inscription'].find_one( + {'_id': ObjectId(str(local_id)), + 'valide': '1', 'locked': '0', + 'partner_owner_recid': str(my_partner['recid'])}, + {'prenom': 1, 'nom': 1, 'email': 1, '_id': 1}) + + local_node = {} + local_node['related_collection'] = 'inscription' + local_node['related_collection_data'] = local_inscrit_data + tab_related_collection.append(local_node) + + ret_file['related_inscrit_email'] = local_inscrit_data['email'] + + + elif (tmp_data['related_collection'] == "session_formation" and tmp_data['related_collection_id']): + # Aller chercher les données de la session + local_session_data = MYSY_GV.dbname['session_formation'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', + 'partner_owner_recid': str(my_partner['recid'])}, + {'_id': 1, 'titre': 1, 'code_session': 1}) + + local_node = {} + local_node['related_collection'] = 'session_formation' + local_node['related_collection_data'] = local_session_data + tab_related_collection.append(local_node) + + ret_file['related_code_session'] = local_session_data['code_session'] + + elif (tmp_data['related_collection'] == "myclass" and tmp_data['related_collection_id']): + # Aller chercher les données de la formation + local_myclass_data = MYSY_GV.dbname['myclass'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', 'locked': '0', + 'partner_owner_recid': str(my_partner['recid'])}, + {'_id': 1, 'external_code': 1, 'title': 1}) + + local_node = {} + local_node['related_collection'] = 'myclass' + local_node['related_collection_data'] = local_myclass_data + tab_related_collection.append(local_node) + + ret_file['related_ftion_external_code'] = local_myclass_data['external_code'] + + ret_file['tab_related_collection'] = tab_related_collection RetObject.append(mycommon.JSONEncoder().encode(ret_file)) nb_val = nb_val + 1 @@ -1028,7 +1178,7 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): field_list = ['token', 'filter_object_owner_collection', 'filter_object_owner_id', 'filter_file_business_object', 'date_create_start_date', 'date_create_end_date', 'filter_type_document', 'filter_nom_client', 'filter_formation_external_code', 'filter_session_code', - 'filter_class_external_code'] + 'filter_class_external_code', 'filter_nom_prenom_mail_inscrit'] incom_keys = diction.keys() for val in incom_keys: @@ -1068,7 +1218,55 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): filt_file_business_object = {} if ("filter_file_business_object" in diction.keys() and diction['filter_file_business_object']): filt_file_business_object = { - 'file_business_object': {'$regex': str(diction['filter_file_business_object']) , "$options": 'i'}} + 'file_business_object': {'$regex': mycommon.regex_replace_cartere(str(diction['filter_file_business_object'])) , "$options": 'i'}} + + + # Gestion du filtre sur le nom, prenom ou mail de l'inscrit + filt_nom_prenom_mail_inscrit = {} + tab_inscrit = [] + if( "filter_nom_prenom_mail_inscrit" in diction.keys() and diction['filter_nom_prenom_mail_inscrit']): + # Filtre sur le nom de l'inscrit + tmp_filt_inscrit_nom = { + 'nom': {'$regex': mycommon.regex_replace_cartere(str(diction['filter_nom_prenom_mail_inscrit'])) , "$options": 'i'}, + 'valide': '1', + 'locked': '0', + 'partner_owner_recid': str(my_partner['recid']) + } + + tmp_filt_inscrit_prenom = { + 'prenom': {'$regex': mycommon.regex_replace_cartere(str(diction['filter_nom_prenom_mail_inscrit'])), + "$options": 'i'}, + 'valide': '1', + 'locked': '0', + 'partner_owner_recid': str(my_partner['recid']) + } + + tmp_filt_inscrit_email = { + 'email': {'$regex': mycommon.regex_replace_cartere(str(diction['filter_nom_prenom_mail_inscrit'])), + "$options": 'i',}, + 'valide': '1', + 'locked': '0', + 'partner_owner_recid': str(my_partner['recid']) + } + qry_inscrit = {"$or": [ + tmp_filt_inscrit_nom, + tmp_filt_inscrit_prenom, + tmp_filt_inscrit_email]} + + + for inscrit_data in MYSY_GV.dbname['inscription'].find(qry_inscrit, {'_id':1}): + tab_inscrit.append(str(inscrit_data['_id'])) + + if(len(tab_inscrit) > 0 ): + filt_nom_prenom_mail_inscrit = {'tab_related_collection.related_collection':'inscription', + 'tab_related_collection.related_collection_id':{'$in': tab_inscrit }} + + print(" QEYYY = ", filt_nom_prenom_mail_inscrit) + + else: + # Aucun inscrit trouvé avec ce filtre de nom/prenom/mail, don on retourne vide + return True, [] + filt_object_owner_collection = {} @@ -1137,14 +1335,22 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): filt_session_code = {} Lists_session_id = [] if ("filter_session_code" in diction.keys() and diction['filter_session_code']): - sub_filt_session_code = {'code_session': {'$regex': str(diction['filter_session_code']), "$options": "i"}, + sub_filt_session_code = {'code_session': {'$regex': mycommon.regex_replace_cartere(str(diction['filter_session_code'])), "$options": "i"}, 'partner_owner_recid': str(my_partner['recid']), 'valide': '1'} # Recuperation des '_id' des session dont le nom match en regexp for List_session_Data in MYSY_GV.dbname['session_formation'].find(sub_filt_session_code, {'_id': 1}): Lists_session_id.append(str(List_session_Data['_id'])) - filt_session_code = {'object_owner_id': {'$in': Lists_session_id, }} + if (len(Lists_session_id) <= 0): + # Aucun inscrit trouvé avec ce filtre, donc on retourne vide + return True, [] + + filt_session_code = {"$or": [{'object_owner_id': {'$in': Lists_session_id, }}, + {'tab_related_collection.related_collection':'session_formation', + 'tab_related_collection.related_collection_id':{'$in': Lists_session_id }} + ]} + """ @@ -1157,15 +1363,26 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): """ filt_class_external_code = {} Lists_class_id = [] - if ("filter_class_external_code" in diction.keys() and diction['filter_class_external_code']): - sub_filt_class_external_code = {'external_code': {'$regex': str(diction['filter_class_external_code']), "$options": "i"}, + if ("filter_formation_external_code" in diction.keys() and diction['filter_formation_external_code']): + sub_filt_class_external_code = {'external_code': {'$regex': mycommon.regex_replace_cartere(str(diction['filter_formation_external_code'])), "$options": "i"}, 'partner_owner_recid': str(my_partner['recid']), 'valide': '1', 'locked':'0'} # Recuperation des '_id' des session dont le nom match en regexp + for List_class_Data in MYSY_GV.dbname['myclass'].find(sub_filt_class_external_code, {'_id': 1}): Lists_class_id.append(str(List_class_Data['_id'])) - filt_class_external_code = {'object_owner_id': {'$in': Lists_class_id, }} + if( len(Lists_class_id) <= 0 ): + # Aucun inscrit trouvé avec ce filtre, donc on retourne vide + return True, [] + + + filt_class_external_code = {"$or": [{'object_owner_id': {'$in': Lists_class_id, }}, + {'tab_related_collection.related_collection': 'myclass', + 'tab_related_collection.related_collection_id': {'$in': Lists_class_id}} + ]} + + print(" ## filt_class_external_code = ", filt_class_external_code) """ Gestion du filtre nom client. @@ -1174,7 +1391,7 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): Lists_partner_client_id = [] if ("filter_nom_client" in diction.keys() and diction['filter_nom_client']): sub_filt_partner_client_nom = { - 'nom': {'$regex': str(diction['filter_nom_client']), "$options": "i"}, + 'nom': {'$regex': mycommon.regex_replace_cartere(str(diction['filter_nom_client'])), "$options": "i"}, 'partner_owner_recid': str(my_partner['recid']), 'valide': '1', 'locked': '0'} # Recuperation des '_id' des session dont le nom match en regexp @@ -1183,7 +1400,16 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): for List_partner_client_Data in MYSY_GV.dbname['partner_client'].find(sub_filt_partner_client_nom, {'_id': 1}): Lists_partner_client_id.append(str(List_partner_client_Data['_id'])) - filt_partner_client_nom = {'object_owner_id': {'$in': Lists_partner_client_id, }} + if (len(Lists_partner_client_id) <= 0): + # Aucun inscrit trouvé avec ce filtre, donc on retourne vide + return True, [] + + filt_partner_client_nom = {"$or": [{'object_owner_id': {'$in': Lists_partner_client_id, }}, + {'tab_related_collection.related_collection': 'partner_client', + 'tab_related_collection.related_collection_id': { + '$in': Lists_partner_client_id}} + ]} + """ @@ -1217,7 +1443,7 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): my_query = {'$and': [ filt_object_owner_collection, filt_filter_object_owner_id, filt_date_creation, filt_type_document, filt_session_code,filt_partner_client_nom, filt_file_business_object, - filt_class_external_code, {'partner_owner_recid': str(my_partner['recid']), + filt_class_external_code, filt_nom_prenom_mail_inscrit, {'partner_owner_recid': str(my_partner['recid']), 'valide':'1'}]} new_query = ([ {"$addFields": { @@ -1292,6 +1518,11 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): else: ret_file['file_extention'] = "file_extention" + if ("tab_key_word" in retval.keys()): + ret_file['tab_key_word'] = retval['tab_key_word'] + else: + ret_file['tab_key_word'] = [] + """ Recuperation du nom du client """ @@ -1311,6 +1542,88 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter(diction): ret_file['client_raison_sociale'] = client_raison_sociale ret_file['client_nom'] = client_nom + tab_related_collection = [] + """ + 09/11/2025 - Traitement du contenu de la 'tab_related_collection' + - aller y chercher si on a un apprenant ou client ou un RH (les tuteurs par exemple) + """ + if( "tab_related_collection" in retval.keys() and retval['tab_related_collection']): + for tmp_data in retval['tab_related_collection']: + if( 'related_collection' in tmp_data.keys() and tmp_data['related_collection'] and + 'related_collection_id' in tmp_data.keys() and tmp_data['related_collection_id']): + + if( tmp_data['related_collection'] == "partner_client" and tmp_data['related_collection_id']): + # Aller chercher les données du client + local_client_data = MYSY_GV.dbname['partner_client'].find_one({'_id':ObjectId(str(tmp_data['related_collection_id'])), + 'valide':'1', 'locked':'0', + 'partner_owner_recid':str(my_partner['recid'])}, + {'raison_sociale':1, 'nom':1, 'email':1, '_id':1}) + + + local_node = {} + local_node['related_collection'] = 'partner_client' + local_node['related_collection_data'] = local_client_data + tab_related_collection.append(local_node) + + ret_file['related_client_nom'] = client_raison_sociale + + + elif( tmp_data['related_collection'] == "inscription" and tmp_data['related_collection_id']): + + local_id = "" + + if type(tmp_data['related_collection_id']) == list: + local_id = tmp_data['related_collection_id'][0] + else: + local_id = tmp_data['related_collection_id'] + + # Aller chercher les données de l'inscrit + local_inscrit_data = MYSY_GV.dbname['inscription'].find_one( + {'_id': ObjectId(str(local_id)), + 'valide': '1', 'locked': '0', + 'partner_owner_recid': str(my_partner['recid'])}, + {'prenom': 1, 'nom': 1, 'email': 1, '_id':1}) + + local_node = {} + local_node['related_collection'] = 'inscription' + local_node['related_collection_data'] = local_inscrit_data + tab_related_collection.append(local_node) + + ret_file['related_inscrit_email'] = local_inscrit_data['email'] + + + elif (tmp_data['related_collection'] == "session_formation" and tmp_data['related_collection_id']): + # Aller chercher les données de la session + local_session_data = MYSY_GV.dbname['session_formation'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', + 'partner_owner_recid': str(my_partner['recid'])}, + {'_id': 1, 'titre': 1, 'code_session': 1}) + + local_node = {} + local_node['related_collection'] = 'session_formation' + local_node['related_collection_data'] = local_session_data + tab_related_collection.append(local_node) + + ret_file['related_code_session'] = local_session_data['code_session'] + + elif (tmp_data['related_collection'] == "myclass" and tmp_data['related_collection_id']): + # Aller chercher les données de la formation + local_myclass_data = MYSY_GV.dbname['myclass'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', 'locked':'0', + 'partner_owner_recid': str(my_partner['recid'])}, + {'_id': 1, 'external_code': 1, 'title': 1}) + + local_node = {} + local_node['related_collection'] = 'myclass' + local_node['related_collection_data'] = local_myclass_data + tab_related_collection.append(local_node) + + ret_file['related_ftion_external_code'] = local_myclass_data['external_code'] + + ret_file['tab_related_collection'] = tab_related_collection + RetObject.append(mycommon.JSONEncoder().encode(ret_file)) nb_val = nb_val + 1 @@ -1329,7 +1642,6 @@ Cette fonction permet de recuperer une liste de documents avec plusieurs filtre """ - def Get_List_object_owner_collection_Stored_Files_With_Filter_No_Token(diction): try: @@ -1464,6 +1776,12 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter_No_Token(diction): else: ret_file['file_extention'] = "file_extention" + if ("tab_key_word" in retval.keys()): + ret_file['tab_key_word'] = retval['tab_key_word'] + else: + ret_file['tab_key_word'] = [] + + """ Recuperation du nom du client """ @@ -1483,6 +1801,88 @@ def Get_List_object_owner_collection_Stored_Files_With_Filter_No_Token(diction): ret_file['client_raison_sociale'] = client_raison_sociale ret_file['client_nom'] = client_nom + tab_related_collection = [] + """ + 09/11/2025 - Traitement du contenu de la 'tab_related_collection' + - aller y chercher si on a un apprenant ou client ou un RH (les tuteurs par exemple) + """ + if ("tab_related_collection" in retval.keys() and retval['tab_related_collection']): + for tmp_data in retval['tab_related_collection']: + if ('related_collection' in tmp_data.keys() and tmp_data['related_collection'] and + 'related_collection_id' in tmp_data.keys() and tmp_data['related_collection_id']): + + if (tmp_data['related_collection'] == "partner_client" and tmp_data['related_collection_id']): + # Aller chercher les données du client + local_client_data = MYSY_GV.dbname['partner_client'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', 'locked': '0', + 'partner_owner_recid': str(ret_file['partner_owner_recid'])}, + {'raison_sociale': 1, 'nom': 1, 'email': 1, '_id': 1}) + + local_node = {} + local_node['related_collection'] = 'partner_client' + local_node['related_collection_data'] = local_client_data + tab_related_collection.append(local_node) + + ret_file['related_client_nom'] = client_raison_sociale + + + elif (tmp_data['related_collection'] == "inscription" and tmp_data['related_collection_id']): + # Aller chercher les données de l'inscrit + + local_id = "" + + if type(tmp_data['related_collection_id']) == list: + local_id = tmp_data['related_collection_id'][0] + else: + local_id = tmp_data['related_collection_id'] + + local_inscrit_data = MYSY_GV.dbname['inscription'].find_one( + {'_id': ObjectId(str(local_id)), + 'valide': '1', 'locked': '0', + 'partner_owner_recid': str(ret_file['partner_owner_recid'])}, + {'prenom': 1, 'nom': 1, 'email': 1, '_id': 1}) + + local_node = {} + local_node['related_collection'] = 'inscription' + local_node['related_collection_data'] = local_inscrit_data + tab_related_collection.append(local_node) + + ret_file['related_inscrit_email'] = local_inscrit_data['email'] + + + elif (tmp_data['related_collection'] == "session_formation" and tmp_data['related_collection_id']): + # Aller chercher les données de la session + local_session_data = MYSY_GV.dbname['session_formation'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', + 'partner_owner_recid': str(ret_file['partner_owner_recid'])}, + {'_id': 1, 'titre': 1, 'code_session': 1}) + + local_node = {} + local_node['related_collection'] = 'session_formation' + local_node['related_collection_data'] = local_session_data + tab_related_collection.append(local_node) + + ret_file['related_code_session'] = local_session_data['code_session'] + + elif (tmp_data['related_collection'] == "myclass" and tmp_data['related_collection_id']): + # Aller chercher les données de la formation + local_myclass_data = MYSY_GV.dbname['myclass'].find_one( + {'_id': ObjectId(str(tmp_data['related_collection_id'])), + 'valide': '1', 'locked': '0', + 'partner_owner_recid': str(ret_file['partner_owner_recid'])}, + {'_id': 1, 'external_code': 1, 'title': 1}) + + local_node = {} + local_node['related_collection'] = 'myclass' + local_node['related_collection_data'] = local_myclass_data + tab_related_collection.append(local_node) + + ret_file['related_ftion_external_code'] = local_myclass_data['external_code'] + + ret_file['tab_related_collection'] = tab_related_collection + RetObject.append(mycommon.JSONEncoder().encode(ret_file)) nb_val = nb_val + 1 diff --git a/base_class_calcul_note.py b/base_class_calcul_note.py index 7601f62..6c0fe9e 100644 --- a/base_class_calcul_note.py +++ b/base_class_calcul_note.py @@ -431,6 +431,7 @@ def Cacul_UE_Note_By_Evaluation_Type(diction): print(" QRYY = ", {'partner_owner_recid': str(my_partner['recid']), 'valide': '1', 'locked': '0', + 'session_id': str(diction['session_id']), 'class_id': str(diction['class_id']), 'class_eu_id': str(diction['ue_id']), 'type_eval_id': str(evaluation_type_id)} ) @@ -439,6 +440,7 @@ def Cacul_UE_Note_By_Evaluation_Type(diction): for val in MYSY_GV.dbname['note_evaluation'].find({'partner_owner_recid': str(my_partner['recid']), 'valide': '1', 'locked': '0', + 'session_id': str(diction['session_id']), 'class_id': str(diction['class_id']), 'class_eu_id': str(diction['ue_id']), 'type_eval_id': str(evaluation_type_id)}): @@ -492,8 +494,6 @@ def Cacul_UE_Note_By_Evaluation_Type(diction): moyenne_note = round(somme_note / nb_eval, 2) - - else : moyenne_note = "-" somme_note = "-" @@ -806,14 +806,14 @@ def Cacul_UE_Note_Finale_For_calcul_mode_1(diction): classement = 0 note_precedente = "" - for sorted_data in MYSY_GV.dbname['session_formation_final_note_classement'].find(basic_qry).sort([("note_finale", pymongo.DESCENDING), ]): + for sorted_data in MYSY_GV.dbname['session_formation_final_note_classement'].find(basic_qry).sort([("note_finale", pymongo.DESCENDING), ]).collation({'locale': "fr", 'numericOrdering': True}): # Gestion des Execo if( str(note_precedente) != str(sorted_data['note_finale'])): classement = classement + 1 note_precedente = str(sorted_data['note_finale']) #MAJ du rang - #print(" MAJJ classement = ", classement) + #print(" MAJJ classement 0222 = ", classement) MYSY_GV.dbname['session_formation_final_note_classement'].find_one_and_update( {'_id':ObjectId(str(sorted_data['_id'])), 'partner_owner_recid':str(sorted_data['partner_owner_recid']), @@ -1258,9 +1258,9 @@ def Get_List_Evaluation_Inscriptio_Note_Classement_With_Filter(diction): """ -Cette fonction va calculer moyenne par session (formation) +Cette fonction va calculer la moyenne par session (formation) -Précedemment les calculs se faisaient pas UE, a présent nous allons faire le calcul par formation. +Précedemment les calculs se faisaient par UE, a présent nous allons faire le calcul par formation. Calcul selon la règle : - [ UE * Coef (UE) ] / nb_coef @@ -1343,16 +1343,31 @@ def Cacul_Session_Note_Finale_For_calcul_mode_1(diction): 'partner_owner_recid': str(my_partner['recid'])}) """ - Recuperer la liste des UE de la formation, avec leur credit et coeff.* + Recuperer la liste des UE qui sont sur la session / promotion, avec leur credit et coeff.* """ tab_class_ue = [] - if( "list_unite_enseignement" in is_myclass_valide_data.keys() ): - tab_class_ue = is_myclass_valide_data['list_unite_enseignement'] + if( "list_unite_enseignement" in is_session_valide_data.keys() ): + for tmp_tab_session_ue in is_session_valide_data['list_unite_enseignement']: + + if( tmp_tab_session_ue and '_id' in tmp_tab_session_ue.keys() ): + local_class_eu = MYSY_GV.dbname['myclass'].find_one( + {'_id': ObjectId(str(diction['class_id'])), + 'valide': '1', + 'locked': '0', + 'partner_owner_recid': str(my_partner['recid']), + 'list_unite_enseignement._id': str(tmp_tab_session_ue['_id'])}, + { 'list_unite_enseignement.$': 1}) + + + + tab_class_ue.append(local_class_eu['list_unite_enseignement'][0]) + if(len(tab_class_ue) <= 0 ): mycommon.myprint( - str(inspect.stack()[0][3]) + " Aucune unité d'enseignement pour cette formation ") - return False, " Aucune unité d'enseignement pour cette formation " + str(inspect.stack()[0][3]) + " Aucune unité d'enseignement pour cette promotion / session ") + return False, " Aucune unité d'enseignement pour cette promotion / session " + # Verifier la validité de la liste des inscrits fournie @@ -1393,6 +1408,7 @@ def Cacul_Session_Note_Finale_For_calcul_mode_1(diction): session_somme_credit_acquis = 0 for class_ue in tab_class_ue : + for tmps_data in MYSY_GV.dbname['session_formation_final_note_classement'].find({'partner_owner_recid':str(my_partner['recid']), 'ue_id':str(class_ue['_id']), 'inscription_id':str(my_inscription), @@ -1450,7 +1466,7 @@ def Cacul_Session_Note_Finale_For_calcul_mode_1(diction): 'session_id':str(is_session_valide_data['_id']), 'valide': '1', 'locked': '0' }).sort( - [("note_finale", pymongo.DESCENDING), ]): + [("note_finale", pymongo.DESCENDING), ]).collation({'locale': "fr", 'numericOrdering': True}): if( sorted_data and "note_finale" in sorted_data.keys() ): # Gestion des Execo @@ -1624,7 +1640,6 @@ def Calcul_Note_Classement_Session(diction): 'session_id':str(is_session_valide_data['_id'])}): tab_inscrit_id.append(str(inscrit['_id'])) - print(" ### str(is_session_valide_data['class_internal_url']) = ", str(is_session_valide_data['class_internal_url'])) is_class_data = MYSY_GV.dbname['myclass'].find_one({'internal_url':str(is_session_valide_data['class_internal_url']), 'valide':'1', @@ -1635,12 +1650,15 @@ def Calcul_Note_Classement_Session(diction): Preparation des calculs """ - # On recupere la liste des ue_id de la formation + # On recupere la liste des ue_id de la promotion tab_ue_id = [] - for class_class_ue_data in is_class_data['list_unite_enseignement'] : + for class_class_ue_data in is_session_valide_data['list_unite_enseignement'] : tab_ue_id.append( str(class_class_ue_data['_id'])) + print(" ### ooooo tab_ue_id = ", tab_ue_id) + + local_diction = {} local_diction['token'] = str(diction['token']) local_diction['class_id'] = str(is_class_data['_id']) @@ -1668,75 +1686,88 @@ def Calcul_Note_Classement_Session(diction): """ for class_class_ue_data in is_class_data['list_unite_enseignement'] : - unite_enseignement_data = MYSY_GV.dbname['unite_enseignement'].find_one( - {'_id': ObjectId(str(class_class_ue_data['_id'])), - 'valide': '1', - 'locked': '0', - }) + """ + Verifier si cette UE est sur la session / promotion + """ + is_ue_in_session_count = MYSY_GV.dbname['session_formation'].count_documents({'_id':ObjectId(str(diction['session_id'])), + 'valide':'1', + 'partner_owner_recid':str(my_partner['recid']), + 'list_unite_enseignement._id':str(class_class_ue_data['_id'])}) - note_ue_calculation_rule_id = "" - if( "note_ue_calculation_rule_id" in unite_enseignement_data.keys() and unite_enseignement_data['note_ue_calculation_rule_id']): - - note_ue_calculation_rule_id = unite_enseignement_data['note_ue_calculation_rule_id'] - - if( note_ue_calculation_rule_id == ""): - mycommon.myprint( - str(inspect.stack()[0][3]) + " L'unité d'enseignement "+str(unite_enseignement_data['code'])+" n'a pas de règle de calcul de la note") - return False, " L'unité d'enseignement "+str(unite_enseignement_data['code'])+" n'a pas de règle de calcul de la note" - - base_calcul_note_class_and_ue_data = MYSY_GV.dbname['base_calcul_note_class_and_ue'].find_one({'_id':ObjectId(str(unite_enseignement_data['note_ue_calculation_rule_id'])), - 'valide':'1', - 'locked':'0', - 'related_collection':'unite_enseignement'}) - - ue_calcul_fonction_name = "" - if ("fonction_name" in base_calcul_note_class_and_ue_data.keys() and base_calcul_note_class_and_ue_data['fonction_name']): - ue_calcul_fonction_name = base_calcul_note_class_and_ue_data['fonction_name'] - - if (ue_calcul_fonction_name == ""): - mycommon.myprint( - str(inspect.stack()[0][3]) + " L'unité d'enseignement " + str( - unite_enseignement_data['code']) + " n'a pas de règle de calcul de la note (2) ") - return False, " L'unité d'enseignement " + str( - unite_enseignement_data['code']) + " n'a pas de règle de calcul de la note (2) " - - local_coef = "1" - if( "coefficient" in class_class_ue_data.keys() and class_class_ue_data['coefficient'] ): - local_coef = class_class_ue_data['coefficient'] - - local_seuil_validation = "10" - if ("seuil_validation" in class_class_ue_data.keys() and class_class_ue_data['seuil_validation']): - local_seuil_validation = class_class_ue_data['seuil_validation'] - print(" ### Pour l'UE : ",str(unite_enseignement_data['code']), - " Coef : ", local_coef, - " seuil validation : ", local_seuil_validation) - print(" ### la formule de calcul est : ", base_calcul_note_class_and_ue_data['fonction_name']) - - #field_list = ['token', 'class_id', 'session_id', 'ue_id', 'tab_inscriptions_ids',] - local_node = {} - local_node['token'] = str(diction['token']) - local_node['class_id'] = str(is_class_data['_id']) - local_node['session_id'] = str(diction['session_id']) - local_node['tab_ue_ids'] = str(unite_enseignement_data['_id']) - - list_inscrit_id = ",".join(tab_inscrit_id) - local_node['tab_inscriptions_ids'] = str(list_inscrit_id) + if( is_ue_in_session_count > 0 ): + unite_enseignement_data = MYSY_GV.dbname['unite_enseignement'].find_one( + {'_id': ObjectId(str(class_class_ue_data['_id'])), + 'valide': '1', + 'locked': '0', + }) - possibles = globals().copy() - possibles.update(locals()) - cron_function = possibles.get(base_calcul_note_class_and_ue_data['fonction_name']) + note_ue_calculation_rule_id = "" + if( "note_ue_calculation_rule_id" in unite_enseignement_data.keys() and unite_enseignement_data['note_ue_calculation_rule_id']): - if not cron_function: - mycommon.myprint(str( - inspect.stack()[0][3]) + " Fonction '" + str(base_calcul_note_class_and_ue_data['fonction_name']) + "' est introuvable") + note_ue_calculation_rule_id = unite_enseignement_data['note_ue_calculation_rule_id'] - print(" Exécution de la fonction : UE de Session = ", base_calcul_note_class_and_ue_data['fonction_name']) - local_status, local_retval = cron_function(local_node) + if( note_ue_calculation_rule_id == ""): + mycommon.myprint( + str(inspect.stack()[0][3]) + " L'unité d'enseignement "+str(unite_enseignement_data['code'])+" n'a pas de règle de calcul de la note") + return False, " L'unité d'enseignement "+str(unite_enseignement_data['code'])+" n'a pas de règle de calcul de la note" + + base_calcul_note_class_and_ue_data = MYSY_GV.dbname['base_calcul_note_class_and_ue'].find_one({'_id':ObjectId(str(unite_enseignement_data['note_ue_calculation_rule_id'])), + 'valide':'1', + 'locked':'0', + 'related_collection':'unite_enseignement'}) + + ue_calcul_fonction_name = "" + if ("fonction_name" in base_calcul_note_class_and_ue_data.keys() and base_calcul_note_class_and_ue_data['fonction_name']): + ue_calcul_fonction_name = base_calcul_note_class_and_ue_data['fonction_name'] + + if (ue_calcul_fonction_name == ""): + mycommon.myprint( + str(inspect.stack()[0][3]) + " L'unité d'enseignement " + str( + unite_enseignement_data['code']) + " n'a pas de règle de calcul de la note (2) ") + return False, " L'unité d'enseignement " + str( + unite_enseignement_data['code']) + " n'a pas de règle de calcul de la note (2) " + + local_coef = "1" + if( "coefficient" in class_class_ue_data.keys() and class_class_ue_data['coefficient'] ): + local_coef = class_class_ue_data['coefficient'] + + local_seuil_validation = "10" + if ("seuil_validation" in class_class_ue_data.keys() and class_class_ue_data['seuil_validation']): + local_seuil_validation = class_class_ue_data['seuil_validation'] + + + print(" ### Pour l'UE : ",str(unite_enseignement_data['code']), + " Coef : ", local_coef, + " seuil validation : ", local_seuil_validation) + + print(" ### la formule de calcul est : ", base_calcul_note_class_and_ue_data['fonction_name']) + + #field_list = ['token', 'class_id', 'session_id', 'ue_id', 'tab_inscriptions_ids',] + local_node = {} + local_node['token'] = str(diction['token']) + local_node['class_id'] = str(is_class_data['_id']) + local_node['session_id'] = str(diction['session_id']) + local_node['tab_ue_ids'] = str(unite_enseignement_data['_id']) + + list_inscrit_id = ",".join(tab_inscrit_id) + local_node['tab_inscriptions_ids'] = str(list_inscrit_id) + + + possibles = globals().copy() + possibles.update(locals()) + cron_function = possibles.get(base_calcul_note_class_and_ue_data['fonction_name']) + + if not cron_function: + mycommon.myprint(str( + inspect.stack()[0][3]) + " Fonction '" + str(base_calcul_note_class_and_ue_data['fonction_name']) + "' est introuvable") + + print(" Exécution de la fonction : UE de Session = ", base_calcul_note_class_and_ue_data['fonction_name']) + local_status, local_retval = cron_function(local_node) class_function_note_calcul_rule = "" @@ -1823,6 +1854,8 @@ def Cacul_UE_Note_Finale_Standard(diction): str(inspect.stack()[0][3]) + " - La valeur '" + val + "' n'est pas presente dans la liste des arguments ") return False, " Les informations fournies sont incorrectes" + + print(" ## diction ) diction = ", diction) """ Verification de l'identité et autorisation de l'entité qui appelle cette API @@ -2145,7 +2178,7 @@ def Cacul_UE_Note_Finale_Standard(diction): note_precedente = "" for sorted_data in MYSY_GV.dbname['session_formation_final_note_classement'].find(basic_qry).sort( - [("note_finale", pymongo.DESCENDING), ]): + [("note_finale", pymongo.DESCENDING), ]).collation({'locale': "fr", 'numericOrdering': True}): #print(" ### sorted_data = ", sorted_data) # Gestion des Execo @@ -2230,7 +2263,6 @@ def Cacul_UE_Note_Finale_Standard(diction): node_note_categorie_session_ue['note_categorie_code'] = val['code'] node_note_categorie_session_ue['pourcentage'] = "0" - print(" ### node_note_categorie_session_ue = ", node_note_categorie_session_ue) data_key = {} data_key['ue_id'] = str(local_ue) @@ -2252,13 +2284,12 @@ def Cacul_UE_Note_Finale_Standard(diction): tab_data = [] for retval in MYSY_GV.dbname['session_formation_final_note_classement'].aggregate(pipe_qry): - print(" ### retval ici pipe_qry = ", retval) + ## Calcul du nombre total d'inscrit pour cette UE total_personne = MYSY_GV.dbname['session_formation_final_note_classement'].count_documents({'partner_owner_recid':str(my_partner['recid']), 'session_id':str(retval['_id']['session_id']), 'ue_id':str(retval['_id']['ue_id'])}) - print(" ### total_personne pour UE ("+str(str(retval['_id']['ue_id']))+") = ", total_personne) node_note_categorie_session_ue = {} node_note_categorie_session_ue['partner_owner_recid'] = str(my_partner['recid']) @@ -2446,21 +2477,55 @@ def run_ue_pre_calcul_moyenne_somme_v2(diction): for my_ue_id in tab_ue_ids_splited: my_ue_id = str(my_ue_id).strip() + print(" ## TGGT my_ue_id = ", my_ue_id) + my_ue_id_data = MYSY_GV.dbname['unite_enseignement'].find_one( {'_id': ObjectId(str(my_ue_id)), 'valide': '1', 'locked': '0', 'partner_owner_recid': str(my_partner['recid'])}) + + + """ + 08/11/2025 + Enveler de cette liste, les type d'evaluation qui sont pas configurée sur la formation. + """ + Class_UE_type_eval = MYSY_GV.dbname['class_unite_enseignement_type_evaluation'].distinct( + "type_evaluation_id", + {'class_ue_id': str(my_ue_id), + 'valide': '1', + 'locked': '0', + 'class_id': str( + diction['class_id']), + 'partner_owner_recid': str( + my_partner['recid']) + } + ) + + print(" ### la liste Class_UE_type_eval = ", Class_UE_type_eval) + + print(" ### QRYYY = ", {'class_eu_id': str(my_ue_id), + 'valide': '1', + 'locked': '0', + 'session_id':str(diction['session_id']), + 'partner_owner_recid': str(my_partner['recid']), + 'type_eval_id':{'$in':Class_UE_type_eval} + }) + evaluation_distinc_type_eval = MYSY_GV.dbname['note_evaluation'].distinct("type_eval_id", {'class_eu_id': str(my_ue_id), 'valide': '1', 'locked': '0', - 'partner_owner_recid': str(my_partner['recid']) + 'session_id':str(diction['session_id']), + 'partner_owner_recid': str(my_partner['recid']), + 'type_eval_id':{'$in':Class_UE_type_eval} } ) - #print(" ### la liste evaluation_distinc_type_eval = ", evaluation_distinc_type_eval) + + + print(" ### la liste evaluation_distinc_type_eval = ", evaluation_distinc_type_eval) @@ -2488,7 +2553,7 @@ def run_ue_pre_calcul_moyenne_somme_v2(diction): ############ """ - Traitement des Types d'evaluation + Traitement des Types d'évaluation """ for eval_type_id in evaluation_distinc_type_eval : @@ -2529,6 +2594,11 @@ def run_ue_pre_calcul_moyenne_somme_v2(diction): new_node['nb_evaluation'] = str(local_retval_nb_eval_TD) # Recuperer la ponderation associé à ce type d'evaluation + print(" ## QRY class_unite_enseignement_type_evaluation_data = ", {'class_id':str(diction['class_id']), + 'type_evaluation_id': str(eval_type_id_data["_id"]), + 'class_ue_id': str(my_ue_id), + }) + class_unite_enseignement_type_evaluation_data = MYSY_GV.dbname['class_unite_enseignement_type_evaluation'].find_one({'class_id':str(diction['class_id']), 'type_evaluation_id': str(eval_type_id_data["_id"]), 'class_ue_id': str(my_ue_id), @@ -2671,16 +2741,29 @@ def Cacul_Session_Note_Finale_For_calcul_Stanard(diction): 'partner_owner_recid': str(my_partner['recid'])}) """ - Recuperer la liste des UE de la formation, avec leur credit et coeff.* + Recuperer la liste des UE qui sont sur la session / promotion, avec leur credit et coeff.* """ tab_class_ue = [] - if( "list_unite_enseignement" in is_myclass_valide_data.keys() ): - tab_class_ue = is_myclass_valide_data['list_unite_enseignement'] + if( "list_unite_enseignement" in is_session_valide_data.keys() ): + for tmp_tab_session_ue in is_session_valide_data['list_unite_enseignement']: + print(" ## tmp_tab_session_ue = ", tmp_tab_session_ue) + + if (tmp_tab_session_ue and '_id' in tmp_tab_session_ue.keys()): + local_class_eu = MYSY_GV.dbname['myclass'].find_one( + {'_id': ObjectId(str(diction['class_id'])), + 'valide': '1', + 'locked': '0', + 'partner_owner_recid': str(my_partner['recid']), + 'list_unite_enseignement._id': str(tmp_tab_session_ue['_id'])}, + {'list_unite_enseignement.$': 1}) + + tab_class_ue.append(local_class_eu['list_unite_enseignement'][0]) + if(len(tab_class_ue) <= 0 ): mycommon.myprint( - str(inspect.stack()[0][3]) + " Aucune unité d'enseignement pour cette formation ") - return False, " Aucune unité d'enseignement pour cette formation " + str(inspect.stack()[0][3]) + " Aucune unité d'enseignement pour cette promotion / session formation ") + return False, " Aucune unité d'enseignement pour cette promotion / session formation " # Verifier la validité de la liste des inscrits fournie @@ -2767,7 +2850,6 @@ def Cacul_Session_Note_Finale_For_calcul_Stanard(diction): upsert=False, ) - """ Apres avoir saisi la note finale sur l'inscription, on va mettre à jour le rang """ @@ -2778,16 +2860,17 @@ def Cacul_Session_Note_Finale_For_calcul_Stanard(diction): 'session_id':str(is_session_valide_data['_id']), 'valide': '1', 'locked': '0' }).sort( - [("note_finale", pymongo.DESCENDING), ]): + [("note_finale", pymongo.DESCENDING), ]).collation({'locale': "fr", 'numericOrdering': True}): if( sorted_data and "note_finale" in sorted_data.keys() ): + # Gestion des Execo if (str(note_precedente) != str(sorted_data['note_finale'])): classement = classement + 1 note_precedente = str(sorted_data['note_finale']) # MAJ du rang - #print(" MAJJ classement = ", classement) + MYSY_GV.dbname['inscription'].find_one_and_update( {'_id': ObjectId(str(sorted_data['_id'])), 'partner_owner_recid': str(sorted_data['partner_owner_recid']), @@ -2795,7 +2878,7 @@ def Cacul_Session_Note_Finale_For_calcul_Stanard(diction): 'locked': '0' }, - {"$set": {'rang': str(classement), 'rang_calculation_date':str(datetime.now())}}, + {"$set": {'rang': str("classement"), 'rang_calculation_date':str(datetime.now())}}, return_document=ReturnDocument.AFTER, upsert=False, ) @@ -3103,7 +3186,28 @@ def Create_Bulletin_By_Inscrit_PDF(diction): """ Creation du ficier PDF """ - contenu_doc_Template = jinja2.Template(str(template_courrier_data['contenu_doc'])) + header_html = """ + + + + + + """ + content_with_header = str(header_html)+str(template_courrier_data['contenu_doc'])+str(" ") + #print(" ### content_with_header = ", content_with_header) + contenu_doc_Template = jinja2.Template(str(content_with_header)) sourceHtml = contenu_doc_Template.render(params=body["params"]) @@ -3125,36 +3229,15 @@ def Create_Bulletin_By_Inscrit_PDF(diction): # close output file resultFile.close() - """ - # Create a PdfDocument object - doc = PdfDocument() - - # Load a PDF file - doc.LoadFromFile(outputFilename) - - # Create font and brush - font = PdfTrueTypeFont("DM Sans", 24.0, PdfFontStyle.Bold, True) - brush = PdfBrushes.get_DarkBlue() - - # Specify text to add to header - headerText = "ABC INC." - - # Iterate through the pages in the document - for i in range(doc.Pages.Count): - # Get a specific page - page = doc.Pages[i] - - # Draw a string at the specified position - page.Canvas.DrawString(headerText, font, brush, 54.0, 25.0) - print(" iiii ") - - # Save the changes to a different PDF file - doc.SaveToFile(str(MYSY_GV.TEMPORARY_DIRECTORY) + "/iiiiiii.pdf") - - # Dispose resources - doc.Dispose() - """ - #### + pied_page = "" + if( "company_data" in convention_dictionnary_data.keys()): + if("societe_nom" in convention_dictionnary_data['company_data'].keys() ): + pied_page = convention_dictionnary_data['company_data']['societe_nom']+ ", Num NDA "+convention_dictionnary_data['company_data']['societe_num_nda'] + pied_page = pied_page + ", Siret : " + convention_dictionnary_data['company_data']['societe_siret'] + pied_page = pied_page + ", Adresse "+ convention_dictionnary_data['company_data']['societe_adr_street'] + " "+convention_dictionnary_data['company_data']['societe_adr_zip'] + pied_page = pied_page + " " + convention_dictionnary_data['company_data']['societe_adr_city'] + pied_page = pied_page + " Tel : " + convention_dictionnary_data['company_data']['societe_telephone'] + pied_page = pied_page + " Email : " + convention_dictionnary_data['company_data']['societe_email'] input_file = outputFilename @@ -3171,21 +3254,20 @@ def Create_Bulletin_By_Inscrit_PDF(diction): canvas.doForm(makerl(canvas, page)) # Dessiner le pied de page - pied_page_html = """ - Votre société bla bla bla bla - Page %s sur %s

- """% (page_num, len(pages)) - print(" ## pied_page_html = ", pied_page_html) + pied_page_html = pied_page + pied_page_num_page_html = """%s/%s """ % (page_num, len(pages)) - footer_text = "Page %s sur %s" % (page_num, len(pages)) - x = 128 + x = 500 canvas.saveState() canvas.setStrokeColorRGB(0, 0, 0) canvas.setLineWidth(0.5) - canvas.line(66, 78, page.BBox[2] - 66, 78) - canvas.setFont('Times-Roman', 10) - canvas.drawString(page.BBox[2] - x, 65, pied_page_html) + + canvas.line(0, 50, 700, 50) + canvas.setFont('Times-Roman', 8) + + canvas.drawString(50, 35, pied_page_html) + canvas.drawString(550, 20, pied_page_num_page_html) canvas.restoreState() canvas.showPage() @@ -3260,10 +3342,10 @@ def Create_Bar_Chart_And_Save_Ok(diction): padding=4)""" labels = ax.bar_label(ax.containers[0], color='black', fontsize=10) - print(ax.legend()) + for label in labels: label.set_ha('right') - print(" ### label.get_text() = ", label.get_text()) + if label.get_text() == '40': label.set_color('b') label.set_text("Eleve") diff --git a/email_mgt.py b/email_mgt.py index 4e6a80b..21f4bb8 100644 --- a/email_mgt.py +++ b/email_mgt.py @@ -2706,9 +2706,9 @@ def ManualSendInvoiceEmailRIB_CIC_BureauVallee(diction): "params": {"order_id": "N/A", "date_order": ": 12/08/2025", "periode":"01/10/2025 au 31/10/2025", - "total_ht": "12 650", - "tva": "2 530", - "total_ttc": "15 279", + "total_ht": "12 749", + "tva": "2 549,8", + "total_ttc": "15 298,8", "client_name": "BVD Fr (Bureau Vallée)", "client_address": "25 rue du Gros Caillou", "client_zip_ville": "78340 – Les Clayes-sous-Bois", diff --git a/ent_student_common.py b/ent_student_common.py index 44890d1..289e05f 100644 --- a/ent_student_common.py +++ b/ent_student_common.py @@ -1073,6 +1073,7 @@ def Get_Ent_Student_Participant_Notes(diction): nb_val = 0 query = [{'$match': {'inscription_id': {'$in':tab_my_inscription_ids}, 'partner_owner_recid': str(apprenant_data['partner_owner_recid']), + 'publish':'1' }}, {'$sort': {'_id': -1}}, {'$lookup': diff --git a/jury_mgt.py b/jury_mgt.py index 8b37a2a..bce9816 100644 --- a/jury_mgt.py +++ b/jury_mgt.py @@ -5047,13 +5047,13 @@ def Send_Jury_Apprenant_Soutenance_Convocation_By_Email(tab_files, Folder, dicti - return True, " Les convocations au jury ont été correctement envoyées par emails" + return True, " Les convocations au jury ont été correctement envoyées par email" except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() mycommon.myprint(str(inspect.stack()[0][3]) + " -" + str(e) + " - Line : " + str(exc_tb.tb_lineno)) - return False, " Impossible d'envoyer les convocations au jury par emails" + return False, " Impossible d'envoyer les convocations au jury par email" diff --git a/main.py b/main.py index 255f4b2..4551fc2 100644 --- a/main.py +++ b/main.py @@ -3165,10 +3165,6 @@ def ManualSendInvoiceEmailRIB_CIC_BureauVallee(): - - - - """ API de recuperation au formation CSV de la liste des inscrits à une formation avec les statuts (validé ou pas) @@ -7404,7 +7400,7 @@ avec plusieurs filtres def Get_List_object_owner_collection_Stored_Files_With_Filter(): # On recupere le corps (payload) de la requete payload = mycommon.strip_dictionary (request.form.to_dict()) - print(" ### Get_List_object_owner_collection_Stored_Files_With_Filter : payload = ",) + print(" ### Get_List_object_owner_collection_Stored_Files_With_Filter : payload = ",payload) status, retval = attached_file_mgt.Get_List_object_owner_collection_Stored_Files_With_Filter(payload) return jsonify(status=status, message=retval) @@ -11276,6 +11272,23 @@ def Update_Participant_Evaluation_Note(): return jsonify(status=status, message=retval) + +""" +API pour publier ou dépublieres note evaluation +à une évaluation +""" +@app.route('/myclass/api/Publish_Unpublish_Participant_Evaluation_Note/', methods=['POST','GET']) +@crossdomain(origin='*') +def Publish_Unpublish_Participant_Evaluation_Note(): + # On recupere le corps (payload) de la requete + payload = mycommon.strip_dictionary (request.form.to_dict()) + print(" ### Publish_Unpublish_Participant_Evaluation_Note payload = ",payload) + status, retval = note_evaluation_mgt.Publish_Unpublish_Participant_Evaluation_Note(payload) + return jsonify(status=status, message=retval) + + + + """ API pour Recuperer la liste des inscrits et groupe inscrit à une evaluation @@ -14702,6 +14715,7 @@ if __name__ == '__main__': mycommon.myprint("++ FLASK PORT " + str(MYSY_GV.MYSY_PORT_REC) + " ++") mycommon.myprint("++ LMS_BAS_URL " + str(MYSY_GV.LMS_BAS_URL) + " ++") + """ scheduler = BackgroundScheduler() scheduler.start() @@ -14715,7 +14729,7 @@ if __name__ == '__main__': # WARNING IMPORTANT WARNING : Shut down the scheduler when exiting the app atexit.register(lambda: scheduler.shutdown()) - + """ app.run(host='localhost', port=MYSY_GV.MYSY_PORT_REC, debug=True, threaded=True) diff --git a/note_evaluation_mgt.py b/note_evaluation_mgt.py index ffd90ad..399ff0e 100644 --- a/note_evaluation_mgt.py +++ b/note_evaluation_mgt.py @@ -198,9 +198,8 @@ def Add_Evaluation_Planification(diction): local_mode_animation = diction['mode_animation'] - - new_data = diction + mytoken = diction['token'] del diction['token'] if( "mode_animation" in diction.keys() ): @@ -226,6 +225,25 @@ def Add_Evaluation_Planification(diction): " Impossible de créer l'évaluation (2) ") return False, " Impossible de créer l'évaluation (2) " + """ + # Ajout de l'evenement dans l'historique + """ + now = str(datetime.now().strftime("%d/%m/%Y %H:%M:%S")) + # print(" ####### laaaa diction = ", diction) + + history_event_dict = {} + history_event_dict['token'] = mytoken + history_event_dict['related_collection'] = "note_evaluation" + history_event_dict['related_collection_recid'] = str(inserted_id) + history_event_dict['action_date'] = str(now) + + history_event_dict['action_description'] = "Planification de l'évaluation " + local_status, local_retval = mycommon.Collection_Historique.Add_Historique_Event(history_event_dict) + if (local_status is False): + mycommon.myprint( + " WARNING : Impossible de logguer l'historique pour l'évènement : " + str(history_event_dict)) + + return True, " L'évaluation a été correctement ajoutée" @@ -398,6 +416,9 @@ def Update_Evaluation_Planification(diction): local_evaluation_id = diction['evaluation_id'] new_data = diction + mytoken = diction['token'] + myevaluation_id = diction['evaluation_id'] + del diction['token'] del diction['evaluation_id'] @@ -428,7 +449,23 @@ def Update_Evaluation_Planification(diction): " Impossible de mettre à jour l'évaluation (2) ") return False, " Impossible de mettre à jour l'évaluation (2) " + """ + # Ajout de l'evenement dans l'historique + """ + now = str(datetime.now().strftime("%d/%m/%Y %H:%M:%S")) + # print(" ####### laaaa diction = ", diction) + history_event_dict = {} + history_event_dict['token'] = mytoken + history_event_dict['related_collection'] = "note_evaluation" + history_event_dict['related_collection_recid'] = str(myevaluation_id) + history_event_dict['action_date'] = str(now) + + history_event_dict['action_description'] = "Mise à jour " + local_status, local_retval = mycommon.Collection_Historique.Add_Historique_Event(history_event_dict) + if (local_status is False): + mycommon.myprint( + " WARNING : Impossible de logguer l'historique pour l'évènement : " + str(history_event_dict)) return True, " L'évaluation a été correctement mise à jour" @@ -565,7 +602,7 @@ def Duplicate_Evaluation_Planification(diction): new_data = evaluation_id_data del new_data['_id'] - new_data['code'] = "Dup_"+str(evaluation_id_data['code']) + new_data['code'] = str(evaluation_id_data['code'])+"_dup" new_data['valide'] = "1" new_data['locked'] = "0" @@ -574,18 +611,30 @@ def Duplicate_Evaluation_Planification(diction): new_data['creation_by'] = str(my_partner['_id']) new_data['partner_owner_recid'] = str(my_partner['recid']) - result = MYSY_GV.dbname['note_evaluation'].insert_one(new_data).inserted_id - - if (result is None ): mycommon.myprint( " Impossible de dupliquer l'évaluation (2) ") return False, " Impossible de mettre à jour l'évaluation (2) " + """ + # Ajout de l'evenement dans l'historique + """ + now = str(datetime.now().strftime("%d/%m/%Y %H:%M:%S")) + # print(" ####### laaaa diction = ", diction) + history_event_dict = {} + history_event_dict['token'] = token + history_event_dict['related_collection'] = "note_evaluation" + history_event_dict['related_collection_recid'] = str(result) + history_event_dict['action_date'] = str(now) + history_event_dict['action_description'] = "Planification par duplication de "+str(evaluation_id_data['code']) + local_status, local_retval = mycommon.Collection_Historique.Add_Historique_Event(history_event_dict) + if (local_status is False): + mycommon.myprint( + " WARNING : Impossible de logguer l'historique pour l'évènement : " + str(history_event_dict)) return True, " L'évaluation a été correctement dupliquée" @@ -990,6 +1039,21 @@ def Delete_Evaluation_Planification(diction): str(inspect.stack()[0][3]) + " Il y a "+str(note_evaluation_participant_count)+" inscription(s) pour cette evaluation. Suppression annulée ") return False, " Il y a "+str(note_evaluation_participant_count)+" inscription(s) pour cette evaluation. Suppression annulée " + eval_data = MYSY_GV.dbname['note_evaluation'].find_one({'_id': ObjectId(str(diction['evaluation_id'])), + 'partner_owner_recid': my_partner['recid'], + 'valide': '1', + 'locked': '0' + }, {'_id':1, 'code':1, 'titre':1}) + + deleted_id = "" + deleted_code = "" + deleted_titre = "" + if( eval_data and 'code' in eval_data.keys()): + deleted_id = str(eval_data['_id']) + deleted_code = str(eval_data['code']) + + if (eval_data and 'titre' in eval_data.keys()): + deleted_titre = str(eval_data['titre']) delete = MYSY_GV.dbname['note_evaluation'].delete_one({ '_id':ObjectId(str(diction['evaluation_id'])), 'partner_owner_recid':my_partner['recid'], @@ -997,7 +1061,23 @@ def Delete_Evaluation_Planification(diction): 'locked': '0' } ) + """ + # Ajout de l'evenement dans l'historique + """ + now = str(datetime.now().strftime("%d/%m/%Y %H:%M:%S")) + # print(" ####### laaaa diction = ", diction) + history_event_dict = {} + history_event_dict['token'] = token + history_event_dict['related_collection'] = "note_evaluation" + history_event_dict['related_collection_recid'] = str(deleted_id) + history_event_dict['action_date'] = str(now) + + history_event_dict['action_description'] = "Suppresion de l'évaluation " + str(deleted_id)+ " code:"+str(deleted_code)+" titre:"+str(deleted_titre) + local_status, local_retval = mycommon.Collection_Historique.Add_Historique_Event(history_event_dict) + if (local_status is False): + mycommon.myprint( + " WARNING : Impossible de logguer l'historique pour l'évènement : " + str(history_event_dict)) return True, " La évaluation a été correctement supprimée" @@ -1921,8 +2001,8 @@ Mise à jour note evaluation Cette fonction met à jour la note d'un inscrit ou groupe d'inscrit. {note_evaluation_participant_id:'kjdskjkdj', tab_participant_note [ - {note_evaluation_participant_id:'4444', note:'33'}, - {note_evaluation_participant_id:'4444', note:'33'} + {note_evaluation_participant_id:'4444', note:'10', publish:'0'}, + {note_evaluation_participant_id:'4444', note:'17', publish:'1'} ] } """ @@ -1992,6 +2072,12 @@ def Update_Participant_Evaluation_Note(diction): else: new_data['note'] = "-1" + if ("publish" in val.keys()): + new_data['publish'] = str(val['publish']) + else: + new_data['publish'] = "0" + + new_data['valide'] = "1" new_data['locked'] = "0" new_data['date_update'] = str(datetime.now()) @@ -2015,6 +2101,123 @@ def Update_Participant_Evaluation_Note(diction): return False, "Impossible de mettre à jour les notes " +""" +Cette fonction permet de publier et dépublier des notes +""" +def Publish_Unpublish_Participant_Evaluation_Note(diction): + try: + diction = mycommon.strip_dictionary(diction) + + """ + Verification des input acceptés + """ + field_list = ['token', 'evaluation_id', 'tab_inscription_id', 'publish_status'] + + incom_keys = diction.keys() + for val in incom_keys: + if val not in field_list and val.startswith('my_') is False: + mycommon.myprint(str( + inspect.stack()[0][3]) + " Le champ '" + val + "' n'est pas autorisé") + return False, " Les informations fournies sont incorrectes" + + """ + Verification des champs obligatoires + """ + field_list_obligatoire = ['token', 'evaluation_id', 'tab_inscription_id', 'publish_status'] + + for val in field_list_obligatoire: + if val not in diction: + mycommon.myprint( + str(inspect.stack()[0][3]) + " - La valeur '" + val + "' n'est pas presente dans la liste des arguments ") + return False, " Les informations fournies sont incorrectes" + + """ + Verification de l'identité et autorisation de l'entité qui + appelle cette API + """ + token = "" + if ("token" in diction.keys()): + if diction['token']: + token = diction['token'] + + + if( diction['publish_status'] not in ['0', '1']): + mycommon.myprint( + str(inspect.stack()[0][ + 3]) + "Le statut de publication est invalide ") + return False, "Le statut de publication est invalide" + + local_status, my_partner = mycommon.Check_Connexion_And_Return_Partner_Data(diction) + if (local_status is not True): + return local_status, my_partner + + """ + Verifier que l'evaluation est valide + """ + is_evaluation_valide = MYSY_GV.dbname['note_evaluation'].count_documents( + {"_id": ObjectId(str(diction['evaluation_id'])), + 'valide': '1', + 'locked': '0', + 'partner_owner_recid': str(my_partner['recid'])}) + + if (is_evaluation_valide != 1): + mycommon.myprint( + str(inspect.stack()[0][3]) + " L'identifiant de l'évaluation n'est pas valide ") + return False, " L'identifiant de l'évaluation n'est pas valide " + + tab_id_to_update = [] + + tab_inscription_id = str(diction['tab_inscription_id']).split(",") + for inscription_id in tab_inscription_id: + if( inscription_id ): + # Verifier que le stagiaire est bien inscrit. Le statut de l'inscription doit etre "1" + + is_inscription_valide = MYSY_GV.dbname['note_evaluation_participant'].count_documents( + {'_id': ObjectId(str(inscription_id)), + 'partner_owner_recid': str(my_partner['recid'])}) + + if (is_inscription_valide != 1): + mycommon.myprint( + str(inspect.stack()[0][ + 3]) + " L'identifiant de l'inscription " + str(inscription_id) + " est invalide ") + return False, " L'identifiant de l'inscription " + str(inscription_id) + " est invalide " + + tab_id_to_update.append(ObjectId(str(inscription_id))) + + + warning_msg = "" + is_warning = "" + + new_data = {} + new_data['date_update'] = str(datetime.now()) + new_data['update_by'] = str(my_partner['_id']) + new_data['publish'] = str(diction['publish_status']) + + # Suppression des inscription + if( len(tab_id_to_update) > 0 and tab_id_to_update[0]): + qry_update_inscription = {'partner_owner_recid': str(my_partner['recid']), + "_id": {"$in": tab_id_to_update}, + } + + print(" ### qry_update_inscription = ", qry_update_inscription ) + + MYSY_GV.dbname['note_evaluation_participant'].update_many( + qry_update_inscription, + {'$set': new_data} + ) + + + + return True, " La mise à jour correctement faite" + + except Exception as e: + exc_type, exc_obj, exc_tb = sys.exc_info() + mycommon.myprint(str(inspect.stack()[0][3]) + " -" + str(e) + " - Line : " + str(exc_tb.tb_lineno)) + return False, "Impossible de mettre à jour les données" + + + + """ Recuperer la liste des inscrits et groupe inscrit à une evaluation @@ -2109,6 +2312,15 @@ def Get_List_Participant_To_Evaluation(diction): if( "note" not in retval.keys() ): user['note'] = "-1" + if ("publish" not in retval.keys()): + user['publish'] = False + + + if ("publish" in retval.keys() and retval['publish'] == "1"): + user['publish'] = True + elif ("publish" in retval.keys() and retval['publish'] != "1"): + user['publish'] = False + if( "convocation_send_date" not in user.keys() ): user['convocation_send_date'] = "" @@ -2273,6 +2485,14 @@ def Get_List_Participant_Notes(diction): user['inscription_id'] = str(retval['inscription_id']) user['note'] = str(retval['note']) + if ("publish" not in retval.keys()): + user['publish'] = False + + if ("publish" in retval.keys() and retval['publish'] == "1"): + user['publish'] = True + elif ("publish" in retval.keys() and retval['publish'] != "1"): + user['publish'] = False + user['note_evaluation_id'] = str(retval['note_evaluation_collection'][0]['_id']) user['note_evaluation_code'] = str(retval['note_evaluation_collection'][0]['code']) @@ -2452,7 +2672,7 @@ def Export_Excel_List_Participant_Notes(diction): outputFilename = str(MYSY_GV.TEMPORARY_DIRECTORY) + "/" + str(orig_file_name) tab_exported_fields_header = ["Formation", "Classe", "Nom", "Prenom", "Email", "UE Code", "UE Titre", - "Evaluation", "Début Evaluation", "Fin Evaluation", "Note" + "Evaluation", "Début Evaluation", "Fin Evaluation", "Note", "Publié" ] # Create a workbook and add a worksheet. @@ -2495,6 +2715,8 @@ def Export_Excel_List_Participant_Notes(diction): user['inscription_id'] = str(retval['inscription_id']) user['note'] = str(retval['note']) + + user['note_evaluation_id'] = str(retval['note_evaluation_collection'][0]['_id']) user['note_evaluation_code'] = str(retval['note_evaluation_collection'][0]['code']) @@ -2538,6 +2760,9 @@ def Export_Excel_List_Participant_Notes(diction): if( "note" not in retval.keys() ): user['note'] = "-1" + if ("publish" not in retval.keys()): + user['publish'] = "0" + user['class_id'] = str(retval['note_evaluation_collection'][0]['class_id']) myclass_data = MYSY_GV.dbname['myclass'].find_one({'_id':ObjectId(str(user['class_id'])), 'valide':'1', @@ -2607,6 +2832,10 @@ def Export_Excel_List_Participant_Notes(diction): worksheet.write(row, column, user['note']) column += 1 + # Champ : user['publish'] + worksheet.write(row, column, user['publish']) + column += 1 + nb_val = nb_val + 1 diff --git a/prj_common.py b/prj_common.py index cfe405c..ae9c703 100644 --- a/prj_common.py +++ b/prj_common.py @@ -8044,9 +8044,6 @@ def Get_total_Ponderation_Class_UE_Type_Eval( class_id, ue_id): somme_ponderation = 0 - print(" ### QRY Get_total_Ponderation_Class_UE_Type_Eval = ", {'class_id':class_id, - 'class_ue_id':ue_id, - }) for tmp in MYSY_GV.dbname['class_unite_enseignement_type_evaluation'].find({'class_id':class_id, 'class_ue_id':ue_id,