From cfd592885303cef9cc2595556f89a340d8ca5423 Mon Sep 17 00:00:00 2001
From: Bertrand Benjamin <benjamin.bertrand@opytex.org>
Date: Tue, 12 Jan 2021 17:25:58 +0100
Subject: [PATCH] Feat: autosave while editing scores

---
 recopytex/scripts/exam_dash.py | 55 +++++++++++++++++++++-------------
 1 file changed, 35 insertions(+), 20 deletions(-)

diff --git a/recopytex/scripts/exam_dash.py b/recopytex/scripts/exam_dash.py
index 5dc45f4..3a06436 100644
--- a/recopytex/scripts/exam_dash.py
+++ b/recopytex/scripts/exam_dash.py
@@ -7,10 +7,12 @@ import dash_core_components as dcc
 import dash_table
 from dash.exceptions import PreventUpdate
 from pathlib import Path
+from datetime import datetime
 import pandas as pd
 
 
 from .. import flat_df_students, pp_q_scores
+from ..config import NO_ST_COLUMNS
 from .getconfig import config, CONFIGPATH
 
 COLORS = {
@@ -24,13 +26,13 @@ COLORS = {
 app = dash.Dash(__name__)
 
 app.layout = html.Div([
-    html.H1("Coucou"),
+    html.H1("Analyse des notes"),
     html.Div(["Classe: ", dcc.Dropdown(
         id='tribe', 
         options=[{"label": t["name"], "value": t["name"]} for t in config["tribes"]],
         value=config["tribes"][0]["name"],
         )]),
-    html.Div(["Evaluation: ", dcc.Dropdown(id='exam')]),
+    html.Div(["Evaluation: ", dcc.Dropdown(id='csv')]),
     html.Div([dash_table.DataTable(
         id="final_score_table",
         columns = [{"id": "Élève", "name": "Élève"}, {"id": "Note", "name": "Note"},{"id": "Barème", "name": "Bareme"}],
@@ -55,37 +57,40 @@ app.layout = html.Div([
     html.Br(),
     html.Div([dash_table.DataTable(
         id="scores_table",
-        columns = [{"id": "plop", "name": "popo"}],
+        columns = [{"id": c, "name":c} for c in NO_ST_COLUMNS.values()],
         style_cell={
             'whiteSpace': 'normal',
             'height': 'auto',
             },
-        style_data_conditional=[]
+        style_data_conditional=[],
+        editable=True,
         )]),
+    html.P(id="lastsave"),
     ])
 
 @app.callback(
-        [dash.dependencies.Output("exam", "options"), dash.dependencies.Output("exam", "value")],
+        [dash.dependencies.Output("csv", "options"), dash.dependencies.Output("csv", "value")],
         [dash.dependencies.Input("tribe", "value")],
         )
-def update_exams(value):
+def update_csvs(value):
     if not value:
         raise PreventUpdate
     p = Path(value)
     csvs = list(p.glob("*.csv"))
-    return [{"label": str(c), "value": str(c)} for c in csvs], str(csvs[0])
+    try:
+        return [{"label": str(c), "value": str(c)} for c in csvs], str(csvs[0])
+    except IndexError:
+        return []
 
 @app.callback(
         [dash.dependencies.Output("final_score_table", "columns"), dash.dependencies.Output("final_score_table", "data")],
-        [dash.dependencies.Input("exam", "value")],
+        [dash.dependencies.Input("scores_table", "data")],
         )
-def update_scores_table(value):
-    if not value:
+def update_final_scores_table(data):
+    if not data:
         raise PreventUpdate
     try:
-        scores = pd.read_csv(value, encoding="UTF8")
-        comments = scores.iloc[0]
-        scores.drop([0], inplace=True)
+        scores = pd.DataFrame.from_records(data)
         scores = flat_df_students(scores).dropna(subset=["Score"])
         scores = pp_q_scores(scores)
         assessment_scores = scores.groupby(["Eleve"]).agg({"Note": "sum", "Bareme": "sum"})
@@ -93,6 +98,16 @@ def update_scores_table(value):
     except KeyError:
         raise PreventUpdate
 
+@app.callback(
+        [dash.dependencies.Output("lastsave", "children")],
+        [dash.dependencies.Input("scores_table", "data"), dash.dependencies.State("csv", "value")],
+        )
+def save_scores(data, csv):
+    scores = pd.DataFrame.from_records(data)
+    print(f"save at {csv} ({datetime.today()})")
+    scores.to_csv(csv, index=False)
+    return [datetime.today()]
+
 
 def highlight_value(df):
     """ Cells style  """
@@ -106,20 +121,20 @@ def highlight_value(df):
                         },
                     'backgroundColor': color,
                     'color': 'white'
-                    } for col in df.columns if col not in ["Exercice", "Question", "Commentaire"]
+                    } for col in df.columns if col not in NO_ST_COLUMNS.values()
                 ]
     return hight
 
 @app.callback(
         [dash.dependencies.Output("scores_table", "columns"), dash.dependencies.Output("scores_table", "data"), dash.dependencies.Output("scores_table", "style_data_conditional"), ],
-        [dash.dependencies.Input("exam", "value")],
+        [dash.dependencies.Input("csv", "value")],
         )
 def update_scores_table(value):
     if not value:
         raise PreventUpdate
-    scores = pd.read_csv(value, encoding="UTF8")
-    try:
-        stack = scores.drop(columns=["Nom", "Trimestre", "Date", "Competence", "Domaine", "Est_nivele", "Bareme"])
-    except KeyError:
-        stack = scores
+    stack = pd.read_csv(value, encoding="UTF8")
+    # try:
+    #     stack = stack.drop(columns=["Nom", "Trimestre", "Date", "Competence", "Domaine", "Est_nivele", "Bareme"])
+    # except KeyError:
+    #     stack = stack
     return [{"id": c, "name": c} for c in stack.columns], stack.to_dict('records'), highlight_value(stack)