Merge branch 'dev' of git_opytex:/lafrite/recopytex into dev

recopytex/dashboard/assets/style.css

@@ -0,0 +1,41 @@
+body {
+    margin: 0px;
+    font-family: 'Source Sans Pro','Roboto','Open Sans','Liberation Sans','DejaVu Sans','Verdana','Helvetica','Arial',sans-serif;
+}
+
+header {
+    margin: 0px 0px 20px 0px;
+    background-color: #333333;
+    color: #ffffff;
+    padding: 20px;
+}
+
+header > h1 {
+    margin: 0px;
+}
+
+main {
+    width: 95vw;
+    margin: auto;
+}
+
+#select {
+    margin-bottom: 20px;
+}
+
+#select > div {
+    width: 40vw;
+    margin: auto;
+}
+
+#analysis {
+    display: flex;
+    flex-flow: row wrap;
+}
+
+#analysis > * {
+    display: flex;
+    flex-flow: column;
+    width: 45vw;
+    margin: auto;
+}

recopytex/dashboard/exam.py

@@ -26,29 +26,26 @@ COLORS = {
     3: "#68D42F",
 }
 
-app = dash.Dash(external_stylesheets=[dbc.themes.SIMPLEX])
 # external_stylesheets = ["https://codepen.io/chriddyp/pen/bWLwgP.css"]
 # app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
-# app = dash.Dash(__name__)
+app = dash.Dash(__name__)
 
 app.layout = html.Div(
     children=[
-        dbc.NavbarSimple(
+        html.Header(
             children=[
-                dbc.Alert("Dernière sauvegarde", id="lastsave", color="success"),
+                html.H1("Analyse des notes"),
+                html.P("Dernière sauvegarde", id="lastsave"),
             ],
-            brand="Analyse des notes",
-            brand_href="#",
-            color="success",
-            dark=True,
         ),
-        html.H2("Choix de l'évaluation"),
+        html.Main(
-        dbc.Row(
             [
-                dbc.Col(
+                html.Section(
+                    [
+                        html.Div(
                             [
                                 "Classe: ",
-                        dbc.Select(
+                                dcc.Dropdown(
                                     id="tribe",
                                     options=[
                                         {"label": t["name"], "value": t["name"]}
@@ -56,9 +53,30 @@ app.layout = html.Div(
                                     ],
                                     value=config["tribes"][0]["name"],
                                 ),
-                    ]
+                            ],
+                            style={
+                                "display": "flex",
+                                "flex-flow": "column",
+                            },
                         ),
-                dbc.Col(
+                        html.Div(
+                            [
+                                "Evaluation: ",
+                                dcc.Dropdown(id="csv"),
+                            ],
+                            style={
+                                "display": "flex",
+                                "flex-flow": "column",
+                            },
+                        ),
+                    ],
+                    id="select",
+                    style={
+                        "display": "flex",
+                        "flex-flow": "row wrap",
+                    },
+                ),
+                html.Div(
                     [
                         "Evaluation: ",
                         dbc.Select(id="csv"),
@@ -95,35 +113,13 @@ app.layout = html.Div(
                         },
                     )
                 ),
-                dbc.Col(
+                html.Div(
-                    [
-                        dash_table.DataTable(
-                            id="final_score_describe",
-                            columns=[{"id": "count", "name": "count"},
-                                {"id": "mean", "name": "mean"},
-                                {"id": "std", "name":  "std"},
-                                {"id": "min", "name":  "min"},
-                                {"id": "25%", "name":  "25%"},
-                                {"id": "50%", "name":  "50%"},
-                                {"id": "75%", "name":  "75%"}, 
-                                {"id": "max", "name":  "max"}, 
-                                ]
-
-                        ),
-                        dcc.Graph(
-                            id="fig_assessment_hist",
-                        ),
-                        dcc.Graph(id="fig_competences"),
-                    ]
-                ),
-            ],
-        ),
-        html.H2("Édition des notes"),
-        dbc.Row(
                     [
                         dash_table.DataTable(
                             id="scores_table",
-                    columns=[{"id": c, "name": c} for c in NO_ST_COLUMNS.values()],
+                            columns=[
+                                {"id": c, "name": c} for c in NO_ST_COLUMNS.values()
+                            ],
                             style_cell={
                                 "whiteSpace": "normal",
                                 "height": "auto",
@@ -131,12 +127,19 @@ app.layout = html.Div(
                             style_data_conditional=[],
                             editable=True,
                         ),
-                dbc.Button("Ajouter un élément", id="btn_add_element"),
+                        html.Button("Ajouter un élément", id="btn_add_element"),
-            ]
+                    ],
+                    id="big_table",
                 ),
-        html.H2("Actions"),
                 dcc.Store(id="final_score"),
-    ]
+            ],
+            className="content",
+            style={
+                "width": "95vw",
+                "margin": "auto",
+            },
+        ),
+    ],
 )
 
 
@@ -179,9 +182,7 @@ def update_final_scores(data):
         return [{}]
 
     scores = pp_q_scores(scores)
-    assessment_scores = scores.groupby(["Eleve"]).agg(
+    assessment_scores = scores.groupby(["Eleve"]).agg({"Note": "sum", "Bareme": "sum"})
-        {"Note": "sum", "Bareme": "sum"}
-    )
     return [assessment_scores.reset_index().to_dict("records")]
 
 
@@ -223,7 +224,9 @@ def update_final_scores_hist(data):
         return [{'data': [], 'layout':[]}]
 
     ranges = np.linspace(
-        0, assessment_scores.Bareme.max(), int(assessment_scores.Bareme.max() * 2 + 1)
+        -0.5,
+        assessment_scores.Bareme.max(),
+        int(assessment_scores.Bareme.max() * 2 + 2),
     )
     bins = pd.cut(assessment_scores["Note"], ranges)
     assessment_scores["Bin"] = bins
@@ -279,11 +282,11 @@ def update_competence_fig(data):
         pt.loc[(str(i), "", ""), :] = ""
     pt.sort_index(inplace=True)
     index = (
-        pt.index.get_level_values(0)
+        pt.index.get_level_values(0).map(str)
         + ":"
-        + pt.index.get_level_values(1)
+        + pt.index.get_level_values(1).map(str)
         + " "
-        + pt.index.get_level_values(2)
+        + pt.index.get_level_values(2).map(str)
     )
 
     fig = go.Figure()
@@ -312,7 +315,6 @@ def update_competence_fig(data):
 @app.callback(
     [
         dash.dependencies.Output("lastsave", "children"),
-        dash.dependencies.Output("lastsave", "color"),
     ],
     [
         dash.dependencies.Input("scores_table", "data"),
@@ -324,9 +326,9 @@ def save_scores(data, csv):
         scores = pd.DataFrame.from_records(data)
         scores.to_csv(csv, index=False)
     except:
-        return [f"Soucis pour sauvegarder à  {datetime.today()} dans {csv}"], "warning"
+        return [f"Soucis pour sauvegarder à  {datetime.today()} dans {csv}"]
     else:
-        return [f"Dernière sauvegarde {datetime.today()} dans {csv}"], "success"
+        return [f"Dernière sauvegarde {datetime.today()} dans {csv}"]
 
 
 def highlight_value(df):
@@ -359,15 +361,16 @@ def highlight_value(df):
 )
 def update_scores_table(csv, add_element, data):
     ctx = dash.callback_context
-    if ctx.triggered[0]['prop_id'] ==  "csv.value":
+    if ctx.triggered[0]["prop_id"] == "csv.value":
         stack = pd.read_csv(csv, encoding="UTF8")
-    elif ctx.triggered[0]['prop_id'] ==  "btn_add_element.n_clicks":
+    elif ctx.triggered[0]["prop_id"] == "btn_add_element.n_clicks":
         stack = pd.DataFrame.from_records(data)
-        infos = pd.DataFrame.from_records([{k: stack.iloc[-1][k] for k in NO_ST_COLUMNS.values()}])
+        infos = pd.DataFrame.from_records(
+            [{k: stack.iloc[-1][k] for k in NO_ST_COLUMNS.values()}]
+        )
         stack = stack.append(infos)
     return (
         [{"id": c, "name": c} for c in stack.columns],
         stack.to_dict("records"),
         highlight_value(stack),
     )
-

recopytex/scripts/recopytex.py

@@ -87,8 +87,9 @@ def new_exam():
 
 
 @cli.command()
-def exam_analysis():
+@click.option("--debug", default=0, help="Debug mode for dash")
-    exam_app.run_server(debug=True)
+def exam_analysis(debug):
+    exam_app.run_server(debug=bool(debug))
 
 
 @cli.command()