Feat: table des évaluations

recopytex/dashboard/index.py

@@ -5,6 +5,7 @@ from dash.dependencies import Input, Output
 from .app import app
 from .exam_analysis import app as exam_analysis
 from .create_exam import app as create_exam
+from .student_analysis import app as student_analysis
 
 
 app.layout = html.Div(
@@ -18,6 +19,8 @@ def display_page(pathname):
         return exam_analysis.layout
     elif pathname == "/create-exam":
         return create_exam.layout
+    elif pathname == "/students":
+        return student_analysis.layout
     else:
         return "404"
 

recopytex/dashboard/student_analysis/app.py

@@ -0,0 +1,217 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+import dash
+import dash_html_components as html
+import dash_core_components as dcc
+import dash_table
+import plotly.graph_objects as go
+from datetime import date, datetime
+import uuid
+import pandas as pd
+import yaml
+from pathlib import Path
+
+from ...scripts.getconfig import config
+from ... import flat_df_students, pp_q_scores
+from ...config import NO_ST_COLUMNS
+from ..app import app
+from ...scripts.exam import Exam
+
+def get_students(csv):
+    return list(pd.read_csv(csv).T.to_dict().values())
+
+
+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"},
+]
+
+layout = html.Div(
+    [
+        html.Header(
+            children=[
+                html.H1("Bilan des élèves"),
+            ],
+        ),
+        html.Main(
+            children=[
+                html.Section(
+                    children=[
+                        html.Form(
+                            id="select-student",
+                            children=[
+                                html.Label(
+                                    children=[
+                                        "Classe",
+                                        dcc.Dropdown(
+                                            id="tribe",
+                                            options=[
+                                                {"label": t["name"], "value": t["name"]}
+                                                for t in config["tribes"]
+                                            ],
+                                            value=config["tribes"][0]["name"],
+                                        ),
+                                    ]
+                                ),
+                                html.Label(
+                                    children=[
+                                        "Élève",
+                                        dcc.Dropdown(
+                                            id="student",
+                                            options=[
+                                                {"label": t["Nom"], "value": t["Nom"]}
+                                                for t in get_students(config["tribes"][0]["students"])
+                                            ],
+                                            value=get_students(config["tribes"][0]["students"])[0]["Nom"],
+                                        ),
+                                    ]
+                                ),
+                                html.Label(
+                                    children=[
+                                        "Trimestre",
+                                        dcc.Dropdown(
+                                            id="term",
+                                            options=[
+                                                {"label": i + 1, "value": i + 1}
+                                                for i in range(3)
+                                            ],
+                                            value=1,
+                                        ),
+                                    ]
+                                ),
+                            ],
+                        ),
+                    ],
+                    id="form",
+                ),
+                html.Section(
+                    children=[
+                        html.H2("Évaluations"),
+                        html.Div(
+                            dash_table.DataTable(
+                                id="exam_scores",
+                                columns=[
+                                    {"id": "Nom", "name": "Évaluations"},
+                                    {"id": "Note", "name": "Note"},
+                                    {"id": "Bareme", "name": "Barème"},
+                                ],
+                                data=[],
+                                style_data_conditional=[
+                                    {
+                                        "if": {"row_index": "odd"},
+                                        "backgroundColor": "rgb(248, 248, 248)",
+                                    }
+                                ],
+                                style_data={
+                                    "width": "100px",
+                                    "maxWidth": "100px",
+                                    "minWidth": "100px",
+                                },
+                            ),
+                            id="eval-table",
+                        ),
+                        html.Div(
+                            id="describe",
+                        ),
+                    ],
+                    id="Évaluations",
+                ),
+                html.Section(
+                    children=[
+                        html.Div(
+                            id="competences-viz",
+                        ),
+                        html.Div(
+                            id="themes-viz",
+                        ),
+                    ],
+                    id="visualisation",
+                ),
+            ]
+        ),
+        dcc.Store(id="student-scores"),
+    ]
+)
+
+
+@app.callback(
+        [
+            dash.dependencies.Output("student", "options"),
+            dash.dependencies.Output("student", "value"),
+            ],
+        [
+            dash.dependencies.Input("tribe", "value")
+            ],)
+def update_students_list(tribe):
+    tribe_config = [t for t in config["tribes"] if t["name"] == tribe][0]
+    students = get_students(tribe_config["students"])
+    options = [
+            {"label": t["Nom"], "value": t["Nom"]}
+            for t in students
+            ]
+    value = students[0]["Nom"]
+    return options, value
+
+
+@app.callback(
+    [
+        dash.dependencies.Output("student-scores", "data"),
+    ],
+    [
+        dash.dependencies.Input("tribe", "value"),
+        dash.dependencies.Input("student", "value"),
+        dash.dependencies.Input("term", "value"),
+        ],
+        )
+def update_student_scores(tribe, student, term):
+    tribe_config = [t for t in config["tribes"] if t["name"] == tribe][0]
+
+    p = Path(tribe_config["name"])
+    csvs = list(p.glob("*.csv"))
+
+    dfs = []
+    for csv in csvs:
+        try:
+            scores = pd.read_csv(csv)
+        except pd.errors.ParserError:
+            pass
+        else:
+            try:
+                if scores.iloc[0]["Commentaire"] == "commentaire":
+                    scores.drop([0], inplace=True)
+            except KeyError:
+                pass
+            scores = flat_df_students(scores).dropna(subset=["Score"])
+            scores = scores[scores["Eleve"] == student]
+            scores = scores[scores["Trimestre"] == term]
+            dfs.append(scores)
+
+    df = pd.concat(dfs)
+
+    return [df.to_dict("records")]
+
+
+@app.callback(
+    [
+        dash.dependencies.Output("exam_scores", "data"),
+    ],
+    [
+        dash.dependencies.Input("student-scores", "data"),
+        ],
+)
+def update_exam_scores(data):
+    scores = pd.DataFrame.from_records(data)
+    scores = pp_q_scores(scores)
+    assessment_scores = scores.groupby(["Nom"]).agg({"Note": "sum", "Bareme": "sum"})
+    return [assessment_scores.reset_index().to_dict("records")]
+    return [{}]
+