Files
colibre/src/pages/acheteur.py
T

539 lines
19 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
import datetime
from typing import Any
import dash_bootstrap_components as dbc
import polars as pl
from dash import (
ClientsideFunction,
Input,
Output,
State,
callback,
clientside_callback,
dcc,
html,
register_page,
)
from src.db import query_marches, schema
from src.figures import (
DataTable,
get_distance_histogram,
get_top_org_table,
make_card,
make_column_picker,
point_on_map,
)
from src.utils.data import DF_ACHETEURS, get_annuaire_data, get_departement_region
from src.utils.frontend import get_button_properties
from src.utils.seo import META_CONTENT
from src.utils.table import (
COLUMNS,
filter_table_data,
format_number,
get_default_hidden_columns,
prepare_table_data,
sort_table_data,
)
from src.utils.tracking import track_search
def get_title(acheteur_id: str | None = None) -> str:
acheteur_nom = DF_ACHETEURS.filter(pl.col("acheteur_id") == acheteur_id).select(
"acheteur_nom"
)
if acheteur_nom.height > 0:
return f"Marchés publics attribués par {acheteur_nom.item(0, 0)} | decp.info"
return "Marchés publics attribués | decp.info"
register_page(
__name__,
path_template="/acheteurs/<acheteur_id>",
title=get_title,
name="Acheteur",
description="Consultez les marchés publics attribués par cet acheteur.",
image_url=META_CONTENT["image_url"],
order=5,
)
DATATABLE = html.Div(
className="marches_table",
children=DataTable(
dtid="acheteur_datatable",
persistence=True,
persistence_type="local",
persisted_props=["filter_query", "sort_by"],
page_action="custom",
filter_action="custom",
sort_action="custom",
page_size=10,
hidden_columns=[],
columns=[{"id": col, "name": col} for col in schema.names()],
),
)
layout = [
dcc.Store(id="acheteur_data", storage_type="memory"),
dcc.Store(id="acheteur-hidden-columns", storage_type="local"),
dcc.Store(id="filter-cleanup-trigger-acheteur"),
dcc.Location(id="acheteur_url", refresh="callback-nav"),
html.Div(
children=[
html.Div(
style={"marginBottom": "50px"},
children=[
dbc.Row(
className="mb-2",
children=[
dbc.Col(
html.H2(
children=[
html.Span(id="acheteur_siret"),
" - ",
html.Span(id="acheteur_nom"),
],
),
width=8,
),
dbc.Col(
dcc.Dropdown(
id="acheteur_year",
options=["Toutes les années"]
+ [
str(year)
for year in range(
2018, int(datetime.date.today().year) + 1
)
],
placeholder="Année",
),
width=4,
),
],
),
dbc.Row(
className="mb-2",
children=[
dbc.Col(
className="org_infos",
children=[
# TODO: ajouter le type d'acheteur : commune, CD, CR, etc.
html.P(
[
"Commune : ",
html.Strong(id="acheteur_commune"),
]
),
html.P(
[
"Département : ",
html.Strong(id="acheteur_departement"),
]
),
html.P(
["Région : ", html.Strong(id="acheteur_region")]
),
html.A(
id="acheteur_lien_annuaire",
children="Plus de détails sur l'Annuaire des entreprises",
),
],
width=4,
),
dbc.Col(
children=[
html.P(id="acheteur_titre_stats"),
html.P(id="acheteur_marches_attribues"),
html.P(id="acheteur_titulaires_differents"),
html.Button(
"Téléchargement au format Excel",
id="btn-download-data-acheteur",
className="btn btn-primary",
),
dcc.Download(id="download-data-acheteur"),
],
width=4,
),
dbc.Col(
id="acheteur_map",
width=4,
),
],
),
dbc.Row(
children=[
dbc.Col(
className="marches_table",
id="top10_titulaires",
width=8,
),
dbc.Col(id="acheteur-distance-histogram", width=4),
],
),
],
),
# récupérer les données de l'acheteur sur l'api annuaire
html.H3("Derniers marchés publics attribués"),
dcc.Loading(
overlay_style={"visibility": "visible", "filter": "blur(2px)"},
id="loading-home",
type="default",
children=[
html.Div(
[
# Bouton modal des colonnes affichées
dbc.Button(
"Colonnes affichées",
id="acheteur_columns_open",
className="column_list",
),
html.P("lignes", id="acheteur_nb_rows"),
html.Button(
"Téléchargement désactivé au-delà de 65 000 lignes",
id="btn-download-filtered-data-acheteur",
className="btn btn-primary",
disabled=True,
),
dcc.Download(id="acheteur-download-filtered-data"),
dbc.Button(
"Remise à zéro",
title="Supprime tous les filtres et les tris. Autrement ils sont conservés même si vous fermez la page.",
id="btn-acheteur-reset",
),
],
className="table-menu",
),
dbc.Modal(
[
dbc.ModalHeader(
dbc.ModalTitle("Choix des colonnes à afficher")
),
dbc.ModalBody(
id="acheteur_columns_body",
children=make_column_picker("acheteur"),
),
dbc.ModalFooter(
dbc.Button(
"Fermer",
id="acheteur_columns_close",
className="ms-auto",
n_clicks=0,
)
),
],
id="acheteur_columns",
is_open=False,
fullscreen="md-down",
scrollable=True,
size="xl",
),
DATATABLE,
],
),
],
),
]
@callback(
Output(component_id="acheteur_siret", component_property="children"),
Output(component_id="acheteur_nom", component_property="children"),
Output(component_id="acheteur_commune", component_property="children"),
Output(component_id="acheteur_map", component_property="children"),
Output(component_id="acheteur_departement", component_property="children"),
Output(component_id="acheteur_region", component_property="children"),
Output(component_id="acheteur_lien_annuaire", component_property="href"),
Input(component_id="acheteur_url", component_property="pathname"),
)
def update_acheteur_infos(url):
acheteur_siret = url.split("/")[-1]
# if len(acheteur_siret) != 14:
# acheteur_siret = (
# f"Le SIRET renseigné doit faire 14 caractères ({acheteur_siret})"
# )
data = get_annuaire_data(acheteur_siret)
data_etablissement = data.get("matching_etablissements") if data else None
if data_etablissement:
data_etablissement = data_etablissement[0]
# Extraction du code département à partir du code postal
code_postal = data_etablissement.get("code_postal", "")
departement_code = code_postal[:2] if code_postal else None
# Création de la carte avec le code département pour un centrage approprié
acheteur_map = point_on_map(
data_etablissement["latitude"],
data_etablissement["longitude"],
departement_code,
)
code_departement, nom_departement, nom_region = get_departement_region(
data_etablissement["code_postal"]
)
departement = f"{nom_departement} ({code_departement})"
lien_annuaire = (
f"https://annuaire-entreprises.data.gouv.fr/etablissement/{acheteur_siret}"
)
raison_sociale = data["nom_raison_sociale"]
libelle_commune = data_etablissement["libelle_commune"]
else:
acheteur_map = html.Div()
code_departement, nom_departement, nom_region = "", "", ""
departement = ""
lien_annuaire = ""
raison_sociale = ""
libelle_commune = ""
return (
acheteur_siret,
raison_sociale,
libelle_commune,
acheteur_map,
departement,
nom_region,
lien_annuaire,
)
@callback(
Output(component_id="acheteur_marches_attribues", component_property="children"),
Output(
component_id="acheteur_titulaires_differents", component_property="children"
),
Input(component_id="acheteur_data", component_property="data"),
)
def update_acheteur_stats(data):
dff = pl.DataFrame(data, strict=False, infer_schema_length=5000)
if dff.height == 0:
dff = pl.DataFrame(schema=schema)
df_marches = dff.unique("id")
nb_marches = format_number(df_marches.height)
# somme_marches = format_number(int(df_marches.select(pl.sum("montant")).item()))
marches_attribues = [html.Strong(nb_marches), " marchés et accord-cadres attribués"]
# + ", pour un total de ", html.Strong(somme_marches + " €")]
del df_marches
nb_titulaires = dff.unique("titulaire_id").height
nb_titulaires = [
html.Strong(format_number(nb_titulaires)),
" titulaires (SIRET) différents",
]
del dff
return marches_attribues, nb_titulaires
@callback(
Output(component_id="acheteur_data", component_property="data"),
Output("btn-download-data-acheteur", "disabled"),
Output("btn-download-data-acheteur", "children"),
Output("btn-download-data-acheteur", "title"),
Input(component_id="acheteur_url", component_property="pathname"),
Input(component_id="acheteur_year", component_property="value"),
)
def get_acheteur_marches_data(url, ach_year: str) -> tuple:
acheteur_siret = url.split("/")[-1]
lff = query_marches("acheteur_id = ?", (acheteur_siret,)).lazy()
if ach_year and ach_year != "Toutes les années":
ach_year = int(ach_year)
lff = lff.filter(pl.col("dateNotification").dt.year() == ach_year)
lff = lff.sort(["dateNotification", "uid"], descending=True, nulls_last=True)
dff: pl.DataFrame = lff.collect(engine="streaming")
download_disabled, download_text, download_title = get_button_properties(dff.height)
data = dff.to_dicts()
return data, download_disabled, download_text, download_title
@callback(
Output("acheteur_datatable", "data"),
Output("acheteur_datatable", "columns"),
Output("acheteur_datatable", "tooltip_header"),
Output("acheteur_datatable", "data_timestamp"),
Output("acheteur_nb_rows", "children"),
Output("btn-download-filtered-data-acheteur", "disabled"),
Output("btn-download-filtered-data-acheteur", "children"),
Output("btn-download-filtered-data-acheteur", "title"),
Output("filter-cleanup-trigger-acheteur", "data"),
Input("acheteur_url", "href"),
Input("acheteur_data", "data"),
Input("acheteur_datatable", "page_current"),
Input("acheteur_datatable", "page_size"),
Input("acheteur_datatable", "filter_query"),
Input("acheteur_datatable", "sort_by"),
State("acheteur_datatable", "data_timestamp"),
)
def get_last_marches_data(
href, data, page_current, page_size, filter_query, sort_by, data_timestamp
) -> tuple:
return prepare_table_data(
data, data_timestamp, filter_query, page_current, page_size, sort_by, "acheteur"
)
@callback(
Output(component_id="top10_titulaires", component_property="children"),
Input(component_id="acheteur_data", component_property="data"),
)
def get_top_titulaires(data):
table = get_top_org_table(data, "titulaire", ["titulaire_distance"])
return make_card(fig=table, title="Top titulaires", lg=12, xl=12)
@callback(
Output("download-data-acheteur", "data"),
Input("btn-download-data-acheteur", "n_clicks"),
State(component_id="acheteur_data", component_property="data"),
State(component_id="acheteur_nom", component_property="children"),
State(component_id="acheteur_year", component_property="value"),
prevent_initial_call=True,
)
def download_acheteur_data(
n_clicks,
data: list[dict[str, Any]],
acheteur_nom: str,
annee: str,
):
df_to_download = pl.DataFrame(data)
def to_bytes(buffer):
df_to_download.write_excel(
buffer, worksheet="DECP" if annee in ["Toutes les années", None] else annee
)
date = datetime.datetime.now().strftime("%Y-%m-%d_%H:%M:%S")
return dcc.send_bytes(to_bytes, filename=f"decp_{acheteur_nom}_{date}.xlsx")
@callback(
Output("acheteur-download-filtered-data", "data"),
State("acheteur_data", "data"),
Input("btn-download-filtered-data-acheteur", "n_clicks"),
State("acheteur_nom", "children"),
State("acheteur_datatable", "filter_query"),
State("acheteur_datatable", "sort_by"),
State("acheteur_datatable", "hidden_columns"),
prevent_initial_call=True,
)
def download_filtered_acheteur_data(
data,
n_clicks,
acheteur_nom,
filter_query,
sort_by,
hidden_columns: list | None = None,
):
lff: pl.LazyFrame = pl.LazyFrame(
data
) # start from the full acheteur data, not from paginated table data
# Les colonnes masquées sont supprimées
if hidden_columns:
lff = lff.drop(hidden_columns)
if filter_query:
track_search(filter_query, "ach download")
lff = filter_table_data(lff, filter_query)
if len(sort_by) > 0:
lff = sort_table_data(lff, sort_by)
def to_bytes(buffer):
lff.collect(engine="streaming").write_excel(buffer, worksheet="DECP")
date = datetime.datetime.now().strftime("%Y-%m-%d_%H:%M:%S")
return dcc.send_bytes(
to_bytes, filename=f"decp_filtrées_{acheteur_nom}_{date}.xlsx"
)
# Pour nettoyer les icontains et i< des filtres
# voir aussi src/assets/dash_clientside.js
clientside_callback(
ClientsideFunction(
namespace="clientside",
function_name="clean_filters",
),
Output("filter-cleanup-trigger-acheteur", "data", allow_duplicate=True),
Input("filter-cleanup-trigger-acheteur", "data"),
prevent_initial_call=True,
)
@callback(
Output("acheteur-hidden-columns", "data", allow_duplicate=True),
Input("acheteur_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("acheteur_datatable", "hidden_columns"),
Input(
"acheteur-hidden-columns",
"data",
),
)
def store_hidden_columns(hidden_columns):
if hidden_columns is None:
hidden_columns = get_default_hidden_columns("acheteur")
return hidden_columns
@callback(
Output("acheteur_column_list", "selected_rows"),
Input("acheteur_datatable", "hidden_columns"),
State("acheteur_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("acheteur")
# 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("acheteur_columns", "is_open"),
Input("acheteur_columns_open", "n_clicks"),
Input("acheteur_columns_close", "n_clicks"),
State("acheteur_columns", "is_open"),
)
def toggle_acheteur_columns(click_open, click_close, is_open):
if click_open or click_close:
return not is_open
return is_open
@callback(
Output("acheteur_datatable", "filter_query", allow_duplicate=True),
Output("acheteur_datatable", "sort_by"),
Input("btn-acheteur-reset", "n_clicks"),
prevent_initial_call=True,
)
def reset_view(n_clicks):
return "", []
@callback(
Output("acheteur-distance-histogram", "children"),
Input("acheteur_data", "data"),
)
def update_acheteur_distance_histogram(data):
lff = pl.LazyFrame(data, strict=False, infer_schema_length=5000)
fig = get_distance_histogram(lff)
return make_card(
title="Distance acheteurtitulaire",
subtitle="en nombre de marchés, échelle logarithmique",
fig=fig,
lg=12,
xl=12,
)