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

0
recopytex/dashboard/student_analysis/__init__.py
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217
recopytex/dashboard/student_analysis/app.py
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@ -1,217 +0,0 @@
#!/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 [{}]