From 8fcad94df4efe509da130052182a488b4526f7ff Mon Sep 17 00:00:00 2001
From: Bertrand Benjamin <benjamin.bertrand@opytex.org>
Date: Sun, 10 Jan 2021 20:46:14 +0100
Subject: [PATCH] Feat: start analysis dash board

---
 recopytex/scripts/exam_dash.py | 125 +++++++++++++++++++++++++++++++++
 recopytex/scripts/recopytex.py |   4 ++
 2 files changed, 129 insertions(+)
 create mode 100644 recopytex/scripts/exam_dash.py

diff --git a/recopytex/scripts/exam_dash.py b/recopytex/scripts/exam_dash.py
new file mode 100644
index 0000000..5dc45f4
--- /dev/null
+++ b/recopytex/scripts/exam_dash.py
@@ -0,0 +1,125 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+import dash
+import dash_html_components as html
+import dash_core_components as dcc
+import dash_table
+from dash.exceptions import PreventUpdate
+from pathlib import Path
+import pandas as pd
+
+
+from .. import flat_df_students, pp_q_scores
+from .getconfig import config, CONFIGPATH
+
+COLORS = {
+        ".": "black",
+        0: "#E7472B",
+        1: "#FF712B",
+        2: "#F2EC4C",
+        3: "#68D42F",
+}
+
+app = dash.Dash(__name__)
+
+app.layout = html.Div([
+    html.H1("Coucou"),
+    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([dash_table.DataTable(
+        id="final_score_table",
+        columns = [{"id": "Élève", "name": "Élève"}, {"id": "Note", "name": "Note"},{"id": "Barème", "name": "Bareme"}],
+        data=[],
+        style_data_conditional=[
+            {
+                'if': {'row_index': 'odd'},
+                'backgroundColor': 'rgb(248, 248, 248)'
+                }
+            ],
+        style_header={
+            'backgroundColor': 'rgb(230, 230, 230)',
+            'fontWeight': 'bold'
+            },
+        style_data={
+            'width': '100px',
+            'maxWidth': '100px',
+            'minWidth': '100px',
+            },
+        ),
+        ]),
+    html.Br(),
+    html.Div([dash_table.DataTable(
+        id="scores_table",
+        columns = [{"id": "plop", "name": "popo"}],
+        style_cell={
+            'whiteSpace': 'normal',
+            'height': 'auto',
+            },
+        style_data_conditional=[]
+        )]),
+    ])
+
+@app.callback(
+        [dash.dependencies.Output("exam", "options"), dash.dependencies.Output("exam", "value")],
+        [dash.dependencies.Input("tribe", "value")],
+        )
+def update_exams(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])
+
+@app.callback(
+        [dash.dependencies.Output("final_score_table", "columns"), dash.dependencies.Output("final_score_table", "data")],
+        [dash.dependencies.Input("exam", "value")],
+        )
+def update_scores_table(value):
+    if not value:
+        raise PreventUpdate
+    try:
+        scores = pd.read_csv(value, encoding="UTF8")
+        comments = scores.iloc[0]
+        scores.drop([0], inplace=True)
+        scores = flat_df_students(scores).dropna(subset=["Score"])
+        scores = pp_q_scores(scores)
+        assessment_scores = scores.groupby(["Eleve"]).agg({"Note": "sum", "Bareme": "sum"})
+        return [{"id": c, "name": c} for c in assessment_scores.reset_index().columns], assessment_scores.reset_index().to_dict('records')
+    except KeyError:
+        raise PreventUpdate
+
+
+def highlight_value(df):
+    """ Cells style  """
+    hight = []
+    for v, color in COLORS.items():
+        hight +=[
+                {
+                    'if': {
+                        'filter_query': '{{{}}} = {}'.format(col, v),
+                        'column_id': col
+                        },
+                    'backgroundColor': color,
+                    'color': 'white'
+                    } for col in df.columns if col not in ["Exercice", "Question", "Commentaire"]
+                ]
+    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")],
+        )
+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
+    return [{"id": c, "name": c} for c in stack.columns], stack.to_dict('records'), highlight_value(stack)
diff --git a/recopytex/scripts/recopytex.py b/recopytex/scripts/recopytex.py
index 3cd5416..27079bd 100644
--- a/recopytex/scripts/recopytex.py
+++ b/recopytex/scripts/recopytex.py
@@ -13,6 +13,7 @@ from .getconfig import config, CONFIGPATH
 from .prompts import prompt_exam, prompt_exercise, prompt_validate
 from ..config import NO_ST_COLUMNS
 from .exam import Exam
+from .exam_dash import app as exam_app
 
 
 @click.group()
@@ -84,6 +85,9 @@ def new_exam():
     base_df.to_csv(exam.path(".csv"), index=False)
     print(f"Le fichier note a été enregistré à {exam.path('.csv')}")
 
+@cli.command()
+def exam_analysis():
+    exam_app.run_server(debug=True)
 
 @cli.command()
 @click.argument("csv_file")