Feat: exam creation page

recopytex/dashboard/create_exam/app.py

@@ -5,13 +5,28 @@ import dash
 import dash_html_components as html
 import dash_core_components as dcc
 import dash_table
-from datetime import date
+from datetime import date, datetime
 import uuid
 import pandas as pd
+import yaml
 
 from ...scripts.getconfig import config
 from ...config import NO_ST_COLUMNS
 from ..app import app
+from ...scripts.exam import Exam
+
+QUESTION_COLUMNS = [
+    {"id": "id", "name": "Question"},
+    {
+        "id": "competence",
+        "name": "Competence",
+        "presentation": "dropdown",
+    },
+    {"id": "theme", "name": "Domaine"},
+    {"id": "comment", "name": "Commentaire"},
+    {"id": "score_rate", "name": "Bareme"},
+    {"id": "is_leveled", "name": "Est_nivele"},
+]
 
 
 def get_current_year_limit():
@@ -35,7 +50,8 @@ layout = html.Div(
         html.Header(
             children=[
                 html.H1("Création d'une évaluation"),
-                html.P("Dernière sauvegarde", id="lastsave"),
+                html.P("Pas encore de sauvegarde", id="is-saved"),
+                html.Button("Enregistrer dans csv", id="save-csv"),
             ],
         ),
         html.Main(
@@ -118,7 +134,7 @@ layout = html.Div(
 def add_exercise(n_clicks, children):
     if n_clicks is None:
         return children
-    element_table = pd.DataFrame(columns=NO_ST_COLUMNS)
+    element_table = pd.DataFrame(columns=[c["id"] for c in QUESTION_COLUMNS])
     element_table = element_table.append(pd.Series(name=0))
     new_exercise = html.Div(
         children=[
@@ -127,12 +143,13 @@ def add_exercise(n_clicks, children):
                     dcc.Input(
                         id={"type": "exercice", "index": str(n_clicks)},
                         type="text",
+                        value=f"Exercice {len(children)+1}",
                         placeholder="Nom de l'exercice",
                         className="exercise-name",
                     ),
                     html.Button(
                         "X",
-                        id={"type": "exercice", "index": str(n_clicks)},
+                        id={"type": "rm_exercice", "index": str(n_clicks)},
                         className="delete-exercise",
                     ),
                 ],
@@ -140,18 +157,7 @@ def add_exercise(n_clicks, children):
             ),
             dash_table.DataTable(
                 id={"type": "elements", "index": str(n_clicks)},
-                columns=[
+                columns=QUESTION_COLUMNS,
-                    {"id": "Question", "name": "Question"},
-                    {
-                        "id": "Competence",
-                        "name": "Competence",
-                        "presentation": "dropdown",
-                    },
-                    {"id": "Domaine", "name": "Domaine"},
-                    {"id": "Commentaire", "name": "Commentaire"},
-                    {"id": "Bareme", "name": "Bareme"},
-                    {"id": "Est_nivele", "name": "Est_nivele"},
-                ],
                 data=element_table.to_dict("records"),
                 editable=True,
                 row_deletable=True,
@@ -192,6 +198,7 @@ def add_exercise(n_clicks, children):
             {"type": "elements", "index": dash.dependencies.MATCH}, "data"
         ),
     ],
+    prevent_initial_call=True,
 )
 def add_element(n_clicks, elements):
     if n_clicks is None or n_clicks < len(elements):
@@ -202,8 +209,27 @@ def add_element(n_clicks, elements):
     return df.to_dict("records")
 
 
+def exam_generalities(tribe, exam_name, date, term, exercices=[], elements=[]):
+    return [
+        html.H1(f"{exam_name} pour les {tribe}"),
+        html.P(f"Fait le {date} (Trimestre {term})"),
+    ]
+
+
+def exercise_summary(identifier, name, elements=[]):
+    df = pd.DataFrame.from_records(elements)
+    return html.Div(
+        [
+            html.H2(name),
+            dash_table.DataTable(
+                columns=[{"id": c, "name": c} for c in df], data=elements
+            ),
+        ]
+    )
+
+
 @app.callback(
-    dash.dependencies.Output("summary", "children"),
+    dash.dependencies.Output("exam_store", "data"),
     [
         dash.dependencies.Input("tribe", "value"),
         dash.dependencies.Input("exam_name", "value"),
@@ -212,13 +238,32 @@ def add_element(n_clicks, elements):
         dash.dependencies.Input(
             {"type": "exercice", "index": dash.dependencies.ALL}, "value"
         ),
+        dash.dependencies.Input(
+            {"type": "elements", "index": dash.dependencies.ALL}, "data"
+        ),
     ],
+    dash.dependencies.State({"type": "elements", "index": dash.dependencies.ALL}, "id"),
 )
-def display_summary(tribe, exam_name, date, term, exercices):
+def store_exam(tribe, exam_name, date, term, exercices, elements, elements_id):
-    return html.Section(
+    exam = Exam(exam_name, tribe, date, term)
-        children=[
+    for (i, name) in enumerate(exercices):
-            html.H1(f"{exam_name} pour les {tribe}"),
+        ex_elements_id = [el for el in elements_id if el["index"] == str(i + 1)][0]
-            html.P(f"Fait le {date} (Trimestre {term})"),
+        index = elements_id.index(ex_elements_id)
-        ]
+        ex_elements = elements[index]
-        + [html.P(f"{value}") for (i, value) in enumerate(exercices)]
+        exam.add_exercise(name, ex_elements)
-    )
+
+    print(yaml.dump(exam.to_dict()))
+    return exam.to_dict()
+
+
+@app.callback(
+    dash.dependencies.Output("is-saved", "children"),
+    dash.dependencies.Input("save-csv", "n_clicks"),
+    dash.dependencies.State("exam_store", "data"),
+    prevent_initial_call=True,
+)
+def save_to_csv(n_clicks, data):
+    exam = Exam(**data)
+    csv = exam.path(".csv")
+    exam.write_csv()
+    return [f"Dernière sauvegarde {datetime.today()} dans {csv}"]

recopytex/scripts/exam.py

@@ -4,22 +4,36 @@
 from datetime import datetime
 from pathlib import Path
 from prompt_toolkit import HTML
+from ..config import NO_ST_COLUMNS
+import pandas as pd
 import yaml
 from .getconfig import config
 
 
+def try_parsing_date(text, formats=["%Y-%m-%d", "%Y.%m.%d", "%Y/%m/%d"]):
+    for fmt in formats:
+        try:
+            return datetime.strptime(text[:10], fmt)
+        except ValueError:
+            pass
+    raise ValueError("no valid date format found")
+
+
 class Exam:
     def __init__(self, name, tribename, date, term, **kwrds):
         self._name = name
         self._tribename = tribename
-        try:
+
-            self._date = datetime.strptime(date, "%y%m%d")
+        self._date = try_parsing_date(date)
-        except:
-            self._date = date
 
         self._term = term
 
-        self._exercises = {}
+        try:
+            kwrds["exercices"]
+        except KeyError:
+            self._exercises = {}
+        else:
+            self._exercises = kwrds["exercices"]
 
     @property
     def name(self):
@@ -125,8 +139,21 @@ class Exam:
     def display(self, name):
         pass
 
-    def write(self):
+    def write_yaml(self):
         print(f"Sauvegarde temporaire dans {self.path('.yml')}")
         self.tribe_path.mkdir(exist_ok=True)
         with open(self.path(".yml"), "w") as f:
             f.write(yaml.dump(self.to_dict()))
+
+    def write_csv(self):
+        rows = self.to_row()
+
+        base_df = pd.DataFrame.from_dict(rows)[NO_ST_COLUMNS.keys()]
+        base_df.rename(columns=NO_ST_COLUMNS, inplace=True)
+
+        students = pd.read_csv(self.tribe_student_path)["Nom"]
+        for student in students:
+            base_df[student] = ""
+
+        self.tribe_path.mkdir(exist_ok=True)
+        base_df.to_csv(self.path(".csv"), index=False)