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Feat: autosave while editing scores

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This commit is contained in:
Bertrand Benjamin 2021-01-12 17:25:58 +01:00
parent 8fcad94df4
commit cfd5928853
1 changed files with 35 additions and 20 deletions
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55
recopytex/scripts/exam_dash.py
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@ -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)