specify columns in notstudent

notes_tools/tools/extract.py

@@ -9,7 +9,16 @@ from path import Path
 
 notes_path = Path("./")
 
-notStudent = ["Trimestre", "Nom", "Date", "Exercice", "Question", "Competence", "Domaine", "Commentaire", "Bareme", "Niveau"]
+no_student_columns = ["Trimestre",
+        "Nom",
+        "Date",
+        "Exercice",
+        "Question",
+        "Competence",
+        "Domaine",
+        "Commentaire",
+        "Bareme",
+        "Niveau"]
 
 pd.set_option("Precision",2)
 
@@ -41,12 +50,12 @@ def get_class_ws(classe, path = notes_path):
     else:
         raise ValueError("This class is not disponible in {p}. You have to choose in {c}".format(p = p, c = list_classes(p)))
 
-def extract_students(df, notStudent = notStudent):
+def extract_students(df, no_student_columns = no_student_columns):
     """ Extract the list of students from df """
-    students = df.columns.difference(notStudent)
+    students = df.columns.difference(no_student_columns)
     return students
 
-def check_students(dfs, notStudent = notStudent):
+def check_students(dfs, no_student_columns = no_student_columns):
     """ Build students list """
     dfs_students = [extract_students(df) for df in dfs]
 
@@ -81,7 +90,7 @@ def flat_df_students(df, students):
     flat_data = []
     dfT = df.T
     for n in dfT:
-        pre_di = dfT[n][notStudent].to_dict()
+        pre_di = dfT[n][no_student_columns].to_dict()
         for e in students:
             data = pre_di.copy()
             data["Eleve"] = e