diff --git a/Data_Base.xlsx b/Data_Base.xlsx
index 1f39cc98688a95fbd37c3b9973f49706d96e2f3b..ff3609863d3bf4498232613c4b243f066019e719 100644
Binary files a/Data_Base.xlsx and b/Data_Base.xlsx differ
diff --git a/projet_personnel/algorithme_gestion_etudiants.py b/projet_personnel/algorithme_gestion_etudiants.py
index b2d39ed30c403cdc3e4a8efc4a8f93ce023ef863..bba2dfb4ebc96ebfea2b54dc684fd43a70222696 100644
--- a/projet_personnel/algorithme_gestion_etudiants.py
+++ b/projet_personnel/algorithme_gestion_etudiants.py
@@ -32,7 +32,7 @@ name_pattern = re.compile(r'^[A-Za-zéèêëà âäôöûüçÉÈÊËÀÂÄÔÖÛ
date_pattern = re.compile(r'^(0[1-9]|[12][0-9]|3[01])/(0[1-9]|1[0-2])/\d{4}$')
place_of_birth_pattern = re.compile(r'^[A-Za-zÀ-ÖØ-öø-ÿ\s]+$')
address_pattern = re.compile(r'^[A-Za-z\s]+ \d+, [A-Za-z\s]+$')
-telephone_pattern = re.compile(r'^\d{3}/\d{2}\.\d{2}\.\d{2}$')
+telephone_pattern = re.compile(r'^\d{4}/\d{2}\.\d{2}\.\d{2}$')
email_pattern = re.compile(r'^[a-zA-Z0-9._%+-]+@student\.uclouvain\.be$')
gender_pattern = re.compile(r'^[MFO]$')
academic_year_pattern = re.compile(r'^(BAC[123]|MA[12])$')
@@ -84,20 +84,17 @@ def register_student(data):
print("The address is not valid. Make sure to follow the format 'street number, city'.")
while True:
- Telephone = input("What is the telephone number? (in the format 000/00.00.00) ")
+ Telephone = input("What is the telephone number? (in the format 0000/00.00.00) ")
if telephone_pattern.match(Telephone):
print(f"The telephone number is valid : {Telephone}")
break # Exit the loop if the telephone number is valid
else:
print("The telephone number is not valid. Make sure to follow the requested format.")
- while True:
- Email = input("Enter the university email (@student.uclouvain.be): ")
- if email_pattern.match(Email):
- print(f"The email is valid : {Email}")
- break # Exit the loop if the email is valid
- else:
- print("The email is not valid. Make sure to follow the requested format.")
+ print("The email address was completed automatically. If it is not suitable you can modify it later : ")
+ email_of_student = f"{Firstname}{'.'}{Lastname}{'@student.uclouvain.be'}"
+ Email = email_of_student.lower()
+ print(Email)
while True:
Gender = input("What is your gender? (For Male enter M, for Female enter F, and for another type enter O): ")
@@ -164,8 +161,10 @@ def register_student(data):
break # Exit the loop if the campus choice is valid
else:
print("The campus choice is not valid. Make sure to follow the requested format.")
+
+ matricule = generate_matricule(Firstname, Lastname, Date_of_birth)
- register(data, Firstname, Lastname, Curriculum, Date_of_birth, Place_of_birth, Address, Telephone, Email, Gender, Academic_year, Courses_and_grade, Campus)
+ register(data, Firstname, Lastname, Curriculum, Date_of_birth, Place_of_birth, Address, Telephone, Email, Gender, Academic_year, Courses_and_grade, Campus, matricule)
# Display the entered information
print("\nEntered Information:")
@@ -181,6 +180,7 @@ def register_student(data):
print(f"Curriculum: {Curriculum}")
print(f"Courses and Grades: {Courses_and_grade}")
print(f"Campus: {Campus}")
+ print(f"Matricule: {matricule}")
while True:
# Ask the user if they want to modify any information before registration
@@ -195,14 +195,22 @@ def register_student(data):
return
+"""
+def reload_data(file_path):
+ pd.read_excel(file_path)
+ return"""
+
+# faire la fonction qui permet de faire un reload des données !!!!
-def register(data, firstname, lastname,Curriculum, date_of_birth, place_of_birth, address, telephone, email, gender, academic_year, courses_and_grade, campus):
- matricule = generate_matricule(firstname, lastname, date_of_birth)
+
+
+
+def register(data, firstname, lastname, Curriculum, date_of_birth, place_of_birth, address, telephone, email, gender, academic_year, courses_and_grade, campus, matricule):
student = {
- "Name": firstname,
- "Surname": lastname,
+ "Firstname": firstname,
+ "Lastname": lastname,
"Curriculum":Curriculum,
"Date of Birth": date_of_birth,
"Place of Birth": place_of_birth,
@@ -218,7 +226,9 @@ def register(data, firstname, lastname,Curriculum, date_of_birth, place_of_birth
for course, grade in courses_and_grade.items():
student[course] = grade
- data = pd.concat([data, student], ignore_index=True)
+ student_df = pd.DataFrame([student])
+ data = pd.concat([data, student_df], ignore_index=True)
+
data.to_excel(file_path, index=False)
print('The person has been registered.\n')
@@ -442,8 +452,8 @@ def modify(data):
# Mapping for field names to DataFrame column names
field_mapping = {
- 1: 'Name',
- 2: 'Surname',
+ 1: 'Firstname',
+ 2: 'Lastname',
3: 'Date of Birth',
4: 'Place of Birth',
5: 'Address',
diff --git a/projet_personnel/algorithme_student_generate.py b/projet_personnel/algorithme_student_generate.py
index 9e24be519bbf3e62816697c233564c31e6c2a676..d20cc8a1e802c647e8a537716c44ee1b6cead33c 100644
--- a/projet_personnel/algorithme_student_generate.py
+++ b/projet_personnel/algorithme_student_generate.py
@@ -114,16 +114,16 @@ for each in range(number_of_students): # générer des données
# attribuer un numero de téléphone à la personne
phone_number = []
- n = f"{random.randint(10000000, 99999999):08d}"
+ n = f"{random.randint(100000000, 999999999):08d}"
if n not in phone_number :
phone_number.append(n)
- phone = f"0{n[:2]}/{n[2:4]}.{n[4:6]}.{n[6:]}"
+ phone = f"0{n[:3]}/{n[3:5]}.{n[5:7]}.{n[7:]}"
# endroit où habite la personne
student_city = random.choice(place_of_birth)
student_street = random.choice(streets)
student_number_of_house = random.randint(1, 200)
- adress_of_student = f"{student_number_of_house} {student_street}, {student_city}"
+ adress_of_student = f"{student_street} {student_number_of_house}, {student_city}"
#attribution du sexe d'une personne
gender_of_student = random.choice(gender)
@@ -190,7 +190,7 @@ for each in range(number_of_students): # générer des données
grades[courses] = random.randint(0, 20)
- data_generated.append({"Firstname": last_name, "Lastname": first_name, "Academic Year" : academic_year, "Curriculum" : curriculum, "Place of Birth" : city_of_birth , "Telephone": phone, "Address": adress_of_student, "Genre" : gender_of_student, "Email" : email_formated, "Campus" : campus, "Date of Birth" : complete_date_of_birth, "Matricule" : matricule, **grades})
+ data_generated.append({"Firstname": last_name, "Lastname": first_name, "Academic Year" : academic_year, "Curriculum" : curriculum, "Place of Birth" : city_of_birth , "Telephone": phone, "Address": adress_of_student, "Gender" : gender_of_student, "Email" : email_formated, "Campus" : campus, "Date of Birth" : complete_date_of_birth, "Matricule" : matricule, **grades})
# génération de données qui ne peuvent pas se ressembler