Feat: basic score_table

recopytex/dashboard/pages/exams_scores/app.py

@@ -15,6 +15,7 @@ layout = html.Div(
                     ],
                 ),
             html.Main(
+                children=[
                     html.Section(
                         children=[
                             html.Div(
@@ -39,19 +40,28 @@ layout = html.Div(
                             ],
                         id="selects",
                         ),
-                # html.Section(
+                    html.Section(
-                #     children=[
+                        children=[
-                #         html.Div(
+                            html.Div(
-                #             children=[],
+                                children=[],
-                #             id="final_score_table_container",
+                                id="final_score_table_container",
-                #             ),
+                                ),
-                #         ],
+                            ],
-                #     id="analysis",
+                        id="analysis",
-                #     ),
+                        ),
-                # html.Section(
+                    html.Section(
-                #     children=[],
+                        children=[
-                #     id="scores_table",  
+                            dash_table.DataTable(
-                #     ),
+                                id="scores_table",
+                                columns=[],
+                                style_data_conditional=[],
+                                fixed_columns={},
+                                editable=True,
+                                )
+                            ],
+                        id="edit",
+                        ),
+                    ],
                 ),
             dcc.Store(id="scores"),
             ],

recopytex/dashboard/pages/exams_scores/callbacks.py

@@ -1,14 +1,15 @@
 #!/usr/bin/env python
 # encoding: utf-8
 
-from dash.dependencies import Input, Output
+from dash.dependencies import Input, Output, State
+import dash
 from dash.exceptions import PreventUpdate
 import dash_table
 import json
 import pandas as pd
 
 from ...app import app
-from .models import get_tribes, get_exams, get_scores
+from .models import get_tribes, get_exams, get_unstack_scores, get_students_from_exam
 
 
 @app.callback(
@@ -18,10 +19,10 @@ from .models import get_tribes, get_exams, get_scores
     ],
     [Input("tribe", "value")],
 )
-def update_exams_choices(value):
+def update_exams_choices(tribe):
-    if not value:
+    if not tribe:
         raise PreventUpdate
-    exams = get_exams(value)
+    exams = get_exams(tribe)
     exams.reset_index(inplace=True)
     if not exams.empty:
         return [
@@ -29,39 +30,38 @@ def update_exams_choices(value):
         ], exams.loc[0].to_json()
     return [], None
 
+
 @app.callback(
-        [Output("scores", "data")],
+    [
-        [Input("exam_select", "value")]
+        Output("scores_table", "columns"),
+        Output("scores_table", "data"),
+        Output("scores_table", "style_data_conditional"),
+        Output("scores_table", "fixed_columns"),
+    ],
+    [
+        Input("exam_select", "value"),
+    ],
 )
-def update_scores_store(value):
+def update_scores_store(exam):
-    if not value:
+    ctx = dash.callback_context
-        return [[]]
+    if not exam:
-    exam = pd.DataFrame.from_dict([json.loads(value)])
+        return [[], [], [], {}]
-    return [get_scores(exam)]
+    exam = pd.DataFrame.from_dict([json.loads(exam)])
+    scores = get_unstack_scores(exam, "score", "student_name")
+    fixed_columns = [
+        "exercise",
+        "question",
+        "competence",
+        "theme",
+        "comment",
+        "score_rate",
+        "is_leveled",
+    ]
+    columns = fixed_columns + list(get_students_from_exam(exam))
 
-
+    return [
-
+        [{"id": c, "name": c} for c in columns],
-
+        scores.to_dict("records"),
-# @app.callback(
+        [],
-#     [
+        {"headers": True, "data": len(fixed_columns)},
-#         Output("final_score", "data"),
+    ]
-#     ],
-#     [Input("scores_table", "data")],
-# )
-# def update_final_scores(data):
-#     if not data:
-#         raise PreventUpdate
-# 
-#     scores = pd.DataFrame.from_records(data)
-#     try:
-#         if scores.iloc[0]["Commentaire"] == "commentaire":
-#             scores.drop([0], inplace=True)
-#     except KeyError:
-#         pass
-#     scores = flat_df_students(scores).dropna(subset=["Score"])
-#     if scores.empty:
-#         return [{}]
-# 
-#     scores = pp_q_scores(scores)
-#     assessment_scores = scores.groupby(["Eleve"]).agg({"Note": "sum", "Bareme": "sum"})
-#     return [assessment_scores.reset_index().to_dict("records")]

recopytex/dashboard/pages/exams_scores/models.py

@@ -14,5 +14,21 @@ def get_exams(tribe):
     return LOADER.get_exams([tribe])
 
 
-def get_scores(exam):
+def get_record_scores(exam):
-    return LOADER.get_exam_scores(exam).to_dict('records')
+    return LOADER.get_exam_scores(exam)
+
+
+def get_unstack_scores(exam, value_column="score", unstack_column="student_name"):
+    flat_scores = LOADER.get_exam_scores(exam)
+    pivot_columns = [col for col in LOADER.score_columns if col != value_column]
+    unstacked_df = (
+        flat_scores.set_index(pivot_columns)[value_column]
+        .unstack(unstack_column)
+        .reset_index()
+    )
+    return unstacked_df
+
+
+def get_students_from_exam(exam):
+    flat_scores = LOADER.get_exam_scores(exam)
+    return flat_scores["student_name"].unique()