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Merge branch 'feature/preview_data' into dev

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Colin Maudry
2026-03-21 10:28:19 +01:00
parent 91ea9eccea e6bf671f16
commit a3dce84cc5
2 changed files with 234 additions and 38 deletions
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src/pages/observatoire.py
+230 -36
View File
@@ -3,7 +3,6 @@ from datetime import datetime
import dash_bootstrap_components as dbc
import polars as pl
import polars.selectors as cs
from dash import (
ALL,
Input,
@@ -18,6 +17,7 @@ from dash import (
)
from src.figures import (
DataTable,
get_barchart_sources,
get_dashboard_summary_table,
get_distance_histogram,
@@ -25,16 +25,21 @@ from src.figures import (
get_geographic_maps,
get_top_org_table,
make_card,
make_column_picker,
make_donut,
)
from src.utils import (
columns,
departements,
df,
df_acheteurs,
df_titulaires,
get_default_hidden_columns,
get_enum_values_as_dict,
logger,
meta_content,
prepare_dashboard_data,
prepare_table_data,
)
name = "Observatoire"
@@ -61,9 +66,36 @@ for code in departements.keys():
}
options_departements.append(departement)
OBSERVATOIRE_COLUMNS = [
col
for col in df.columns
if col.startswith("acheteur")
or col.startswith("titulaire")
or col
in [
"uid",
"dateNotification",
"montant",
"considerationsSociales",
"considerationsEnvironnementales",
"marcheInnovant",
"sousTraitanceDeclaree",
"techniques",
"sourceDataset",
"type",
"codeCPV",
]
]
DF_FILTERED: pl.DataFrame = pl.DataFrame()
layout = [
dcc.Location(id="dashboard_url", refresh="callback-nav"),
dcc.Store(id="observatoire-filters", storage_type="local"),
dcc.Store(id="observatoire-hidden-columns", storage_type="local"),
dcc.Store(
id="filter-cleanup-trigger-observatoire-preview"
), # utilisé juste pour ne pas avoir à adapter les données retournées de prepare_table data
dbc.Modal(
[
dbc.ModalHeader(dbc.ModalTitle("Montants")),
@@ -372,10 +404,16 @@ Alors, on fait comment ?
),
dcc.Download(id="download-observatoire"),
dbc.Button(
"Télécharger au format Excel",
id="btn-download-observatoire",
disabled=True,
className="mt-2",
"Prévisualiser les données",
id="btn-observatoire-preview",
className="btn btn-primary",
color="primary",
outline=True,
),
dcc.Input(
id="observatoire-share-url",
readOnly=True,
style={"display": "none"},
),
dcc.Input(
id="observatoire-share-url",
@@ -398,6 +436,81 @@ Alors, on fait comment ?
),
],
),
dbc.Offcanvas(
id="observatoire-preview",
title="Prévisualisation des données",
placement="bottom",
is_open=False,
scrollable=True,
style={"height": "75vh"},
children=[
# Header row: title + "Colonnes affichées" button
dbc.Row(
[
dbc.Col(
html.Div(
className="table-menu",
children=[
dbc.Button(
"Choisir les colonnes",
id="observatoire-preview-columns-open",
className="btn btn-primary",
),
html.P(id="nb_rows_observatoire"),
dbc.Button(
"Télécharger au format Excel",
id="btn-download-observatoire",
disabled=True,
className="btn btn-primary",
outline=True,
),
],
),
width="auto",
),
],
className="mb-2 align-items-center",
),
# Column picker modal
dbc.Modal(
[
dbc.ModalHeader(
dbc.ModalTitle("Colonnes affichées dans la prévisualisation")
),
dbc.ModalBody(
id="observatoire-preview-columns-body",
children=make_column_picker("observatoire_preview"),
),
dbc.ModalFooter(
dbc.Button(
"Fermer",
id="observatoire-preview-columns-close",
className="ms-auto",
n_clicks=0,
)
),
],
id="observatoire-preview-columns-modal",
is_open=False,
fullscreen="md-down",
scrollable=True,
size="xl",
),
# DataTable
html.Div(
className="marches_table",
children=DataTable(
dtid="observatoire-preview-table",
page_size=5,
page_action="custom",
sort_action="custom",
filter_action="custom",
hidden_columns=[],
columns=[{"id": col, "name": col} for col in OBSERVATOIRE_COLUMNS],
),
),
],
),
]
@@ -500,8 +613,6 @@ def sync_observatoire_share_url(acheteur_id, titulaire_id, href):
@callback(
Output("cards", "children"),
Output("btn-download-observatoire", "disabled"),
Output("btn-download-observatoire", "children"),
Input("dashboard_year", "value"),
Input("dashboard_acheteur_id", "value"),
Input("dashboard_acheteur_categorie", "value"),
@@ -541,27 +652,6 @@ def udpate_dashboard_cards(
):
lff: pl.LazyFrame = df.lazy()
columns = [
"uid",
cs.starts_with("acheteur"),
cs.starts_with("titulaire"),
"dateNotification",
"montant",
"considerationsSociales",
"considerationsEnvironnementales",
"marcheInnovant",
"sousTraitanceDeclaree",
"techniques",
"sourceDataset",
"type",
"codeCPV",
]
if dashboard_marche_objet:
columns.append("objet")
lff = lff.select(columns)
# Filtrage des données
lff = prepare_dashboard_data(
lff=lff,
@@ -586,18 +676,17 @@ def udpate_dashboard_cards(
# Génération des métriques
dff = lff.collect(engine="streaming")
global DF_FILTERED
DF_FILTERED = dff
logger.debug("Filter data: " + str(dff.height))
df_per_uid = (
dff.select("uid", "montant").group_by("uid").agg(pl.col("montant").first())
)
nb_marches = df_per_uid.height
if nb_marches == 0:
dl_disabled, dl_text = True, "Pas de données à télécharger"
elif nb_marches > 65000:
dl_disabled, dl_text = True, "Téléchargement désactivé au-delà de 65 000 lignes"
else:
dl_disabled, dl_text = False, "Télécharger au format Excel"
cards = []
card_summary_table = get_dashboard_summary_table(dff, df_per_uid, nb_marches)
@@ -686,7 +775,7 @@ def udpate_dashboard_cards(
)
)
return dbc.Row(children=cards + geographic_maps + other_cards), dl_disabled, dl_text
return dbc.Row(children=cards + geographic_maps + other_cards)
@callback(
@@ -709,6 +798,7 @@ def udpate_dashboard_cards(
State("dashboard_marche_sousTraitanceDeclaree", "value"),
State("dashboard_marche_considerationsSociales", "value"),
State("dashboard_marche_considerationsEnvironnementales", "value"),
State("observatoire-hidden-columns", "data"),
prevent_initial_call=True,
)
def download_observatoire(
@@ -730,6 +820,7 @@ def download_observatoire(
dashboard_marche_sous_traitance_declaree,
dashboard_considerations_sociales,
dashboard_considerations_environnementales,
hidden_columns,
):
lff = prepare_dashboard_data(
lff=df.lazy(),
@@ -752,6 +843,9 @@ def download_observatoire(
sous_traitance_declaree=dashboard_marche_sous_traitance_declaree,
)
if hidden_columns:
lff = lff.drop(hidden_columns)
def to_bytes(buffer):
lff.collect(engine="streaming").write_excel(buffer, worksheet="DECP")
@@ -795,3 +889,103 @@ def add_organization_name_in_title(acheteur_id, titulaire_id):
html.Small(nom, className="text-muted d-block fw-normal fs-5"),
]
return name
@callback(
Output("observatoire-preview", "is_open"),
Input("btn-observatoire-preview", "n_clicks"),
State("observatoire-preview", "is_open"),
prevent_initial_call=True,
)
def toggle_observatoire_preview(n_clicks, is_open):
return not is_open
@callback(
Output("observatoire-preview-table", "data"),
Output("observatoire-preview-table", "columns"),
Output("observatoire-preview-table", "tooltip_header"),
Output("observatoire-preview-table", "data_timestamp"),
Output("nb_rows_observatoire", "children"),
Output("btn-download-observatoire", "disabled"),
Output("btn-download-observatoire", "children"),
Output("btn-download-observatoire", "title"),
Output("filter-cleanup-trigger-observatoire-preview", "data", allow_duplicate=True),
Input("observatoire-preview", "is_open"),
Input("observatoire-preview-table", "filter_query"),
Input("observatoire-preview-table", "page_current"),
Input("observatoire-preview-table", "page_size"),
Input("observatoire-preview-table", "sort_by"),
State("observatoire-preview-table", "data_timestamp"),
prevent_initial_call=True,
)
def populate_preview_table(
is_open, filter_query, page_current, page_size, sort_by, data_timestamp
):
if not is_open:
return (no_update,) * 9
global DF_FILTERED
lff = DF_FILTERED.lazy()
return prepare_table_data(
lff,
data_timestamp,
filter_query,
page_current,
page_size,
sort_by,
"observatoire-preview",
)
@callback(
Output("observatoire-hidden-columns", "data", allow_duplicate=True),
Input("observatoire_preview_column_list", "selected_rows"),
prevent_initial_call=True,
)
def update_hidden_columns_from_checkboxes(selected_columns):
if selected_columns:
selected_columns = [columns[i] for i in selected_columns]
hidden_columns = [col for col in columns if col not in selected_columns]
return hidden_columns
else:
return []
@callback(
Output("observatoire-preview-table", "hidden_columns"),
Input(
"observatoire-hidden-columns",
"data",
),
)
def store_hidden_columns(hidden_columns):
return hidden_columns
@callback(
Output("observatoire_preview_column_list", "selected_rows"),
Input("observatoire-preview-table", "hidden_columns"),
State(
"observatoire_preview_column_list", "selected_rows"
), # pour éviter la boucle infinie
)
def update_checkboxes_from_hidden_columns(hidden_cols, current_checkboxes):
hidden_cols = hidden_cols or get_default_hidden_columns("tableau")
# Show all columns that are NOT hidden
visible_cols = [columns.index(col) for col in columns if col not in hidden_cols]
return visible_cols
@callback(
Output("observatoire-preview-columns-modal", "is_open"),
Input("observatoire-preview-columns-open", "n_clicks"),
Input("observatoire-preview-columns-close", "n_clicks"),
State("observatoire-preview-columns-modal", "is_open"),
)
def toggle_tableau_columns(click_open, click_close, is_open):
if click_open or click_close:
return not is_open
return is_open
src/utils.py
+4 -2
View File
@@ -631,6 +631,8 @@ def prepare_table_data(
# Récupération des données
if isinstance(data, list):
lff: pl.LazyFrame = pl.LazyFrame(data, strict=False, infer_schema_length=5000)
elif isinstance(data, pl.LazyFrame):
lff = data
else:
lff: pl.LazyFrame = df.lazy() # start from the original data
@@ -751,10 +753,10 @@ def prepare_dashboard_data(
if code_cpv:
lff = lff.filter(pl.col("codeCPV").str.starts_with(code_cpv))
if marche_innovant != "all":
if marche_innovant and marche_innovant != "all":
lff = lff.filter(pl.col("marcheInnovant") == marche_innovant)
if sous_traitance_declaree != "all":
if sous_traitance_declaree and sous_traitance_declaree != "all":
lff = lff.filter(pl.col("sousTraitanceDeclaree") == sous_traitance_declaree)
if techniques: