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Merge branch 'feature/share_filtering_datatables' into dev

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This commit is contained in:
Colin Maudry
2025-11-24 16:01:34 +01:00
parent 193cf5302c e216b42379
commit 80a7e51ec4
7 changed files with 384 additions and 206 deletions
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README.md
+2 -3
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@@ -1,8 +1,7 @@
# decp.info
> v2.2.2
Outil d'exploration et de téléchargement des données essentielles de la commande publique.
> v2.3.0
> Outil d'exploration et de téléchargement des données essentielles de la commande publique.
=> [decp.info](https://decp.info)
pyproject.toml
+2 -2
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@@ -1,13 +1,13 @@
[project]
name = "decp.info"
description = "Interface d'exploration et d'analyse des marchés publics français."
version = "2.2.2"
version = "2.3.0"
requires-python = ">= 3.10"
authors = [
{ name = "Colin Maudry", email = "colin+decp@maudry.com" }
]
dependencies = [
"dash==3.2.0",
"dash==3.3.0",
"dash[compress]",
"polars",
"gunicorn",
src/assets/style.css
+7 -1
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@@ -133,6 +133,12 @@ td[data-dash-column="objet"],td[data-dash-column="titulaire_nom"],td[data-dash-c
.marches_table {
font-family: "Open Sans", sans-serif;
}
.marches_table.stuck {
position: relative;
right: 200px;
}
.marches_table .cell-table tr:nth-child(even) td {
background-color: #feeeee;
font-family: "Open Sans", sans-serif;
@@ -212,7 +218,7 @@ summary > h3 {
}
#_pages_content {
padding-top: 28px;
padding: 28px 24px 0 24px;
}
/* Vue acheteur/titulaire/recherche */
src/pages/acheteur.py
+107 -58
View File
@@ -6,14 +6,16 @@ from dash import Input, Output, State, callback, dcc, html, register_page
from src.callbacks import get_top_org_table
from src.figures import DataTable, point_on_map
from src.utils import (
add_links_in_dict,
df,
filter_table_data,
format_number,
format_values,
get_annuaire_data,
get_button_properties,
get_default_hidden_columns,
get_departement_region,
meta_content,
setup_table_columns,
prepare_table_data,
sort_table_data,
)
register_page(
@@ -26,11 +28,22 @@ register_page(
order=5,
)
datatable = html.Div(
className="marches_table",
children=DataTable(
dtid="acheteur_datatable",
page_action="custom",
filter_action="custom",
sort_action="custom",
page_size=10,
hidden_columns=get_default_hidden_columns(page="acheteur"),
),
)
layout = [
dcc.Store(id="acheteur_data", storage_type="memory"),
dcc.Location(id="url", refresh="callback-nav"),
html.Div(
className="container",
children=[
html.Div(
className="wrapper",
@@ -84,9 +97,9 @@ layout = [
html.P(id="acheteur_titulaires_differents"),
html.Button(
"Téléchargement au format Excel",
id="btn-download-acheteur-data",
id="btn-download-data-acheteur",
),
dcc.Download(id="download-acheteur-data"),
dcc.Download(id="download-data-acheteur"),
],
),
html.Div(className="org_map", id="acheteur_map"),
@@ -101,7 +114,26 @@ layout = [
),
# récupérer les données de l'acheteur sur l'api annuaire
html.H3("Derniers marchés publics attribués"),
html.Div(id="acheteur_last_marches", children=""),
dcc.Loading(
overlay_style={"visibility": "visible", "filter": "blur(2px)"},
id="loading-home",
type="default",
children=[
html.Div(
[
html.P("lignes", id="acheteur_nb_rows"),
html.Button(
"Téléchargement désactivé au-delà de 65 000 lignes",
id="btn-download-filtered-data-acheteur",
disabled=True,
),
dcc.Download(id="acheteur-download-filtered-data"),
],
className="table-menu",
),
datatable,
],
),
],
),
]
@@ -176,68 +208,49 @@ def update_acheteur_stats(data):
@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="url", component_property="pathname"),
Input(component_id="acheteur_year", component_property="value"),
)
def get_acheteur_marches_data(url, acheteur_year: str) -> list[dict]:
def get_acheteur_marches_data(url, acheteur_year: str) -> tuple:
acheteur_siret = url.split("/")[-1]
lff = df.lazy()
lff = lff.filter(pl.col("acheteur_id") == acheteur_siret)
lff = lff.select(
"id",
"uid",
"objet",
"dateNotification",
"titulaire_id",
"titulaire_typeIdentifiant",
"titulaire_nom",
"distance",
"montant",
"codeCPV",
"dureeMois",
)
if acheteur_year and acheteur_year != "Toutes":
lff = lff.filter(
pl.col("dateNotification").cast(pl.String).str.starts_with(acheteur_year)
)
lff = lff.sort(["dateNotification", "id"], descending=True, nulls_last=True)
acheteur_year = int(acheteur_year)
lff = lff.filter(pl.col("dateNotification").dt.year() == acheteur_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 = lff.collect(engine="streaming").to_dicts()
return data
data = dff.to_dicts()
return data, download_disabled, download_text, download_title
@callback(
Output(component_id="acheteur_last_marches", component_property="children"),
Input(component_id="acheteur_data", component_property="data"),
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"),
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_table(data) -> html.Div:
dff = pl.DataFrame(data)
if dff.height == 0:
return html.Div(html.P("Aucun marché trouvé."))
dff = dff.cast(pl.String)
dff = dff.fill_null("")
dff = format_values(dff)
columns, tooltip = setup_table_columns(
dff,
hideable=False,
exclude=["titulaire_id", "titulaire_typeIdentifiant", "uid"],
def get_last_marches_data(
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
)
data = dff.to_dicts()
data = add_links_in_dict(data, "titulaire")
table = html.Div(
className="marches_table",
children=DataTable(
dtid="acheteur_datatable",
data=data,
page_action="native",
filter_action="native",
columns=columns,
tooltip_header=tooltip,
page_size=10,
),
)
return table
@callback(
@@ -249,8 +262,8 @@ def get_top_titulaires(data):
@callback(
Output("download-acheteur-data", "data"),
Input("btn-download-acheteur-data", "n_clicks"),
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"),
@@ -271,3 +284,39 @@ def download_acheteur_data(
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
):
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:
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"
)
src/pages/tableau.py
+4 -66
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@@ -6,22 +6,17 @@ from dash import Input, Output, State, callback, dcc, html, register_page
from src.figures import DataTable
from src.utils import (
add_links,
add_resource_link,
df,
filter_table_data,
format_number,
format_values,
get_default_hidden_columns,
meta_content,
setup_table_columns,
sort_table_data,
)
from utils import prepare_table_data
update_date = os.path.getmtime(os.getenv("DATA_FILE_PARQUET_PATH"))
update_date = datetime.fromtimestamp(update_date).strftime("%d/%m/%Y")
schema = df.collect_schema()
name = "Tableau"
register_page(
@@ -42,7 +37,7 @@ datatable = html.Div(
page_action="custom",
filter_action="custom",
sort_action="custom",
hidden_columns=get_default_hidden_columns(schema),
hidden_columns=get_default_hidden_columns(None),
),
)
@@ -138,65 +133,8 @@ layout = [
State("table", "data_timestamp"),
)
def update_table(page_current, page_size, filter_query, sort_by, data_timestamp):
if os.getenv("DEVELOPMENT").lower() == "true":
print(" + + + + + + + + + + + + + + + + + + ")
# Application des filtres
lff: pl.LazyFrame = df.lazy() # start from the original data
if filter_query:
lff = filter_table_data(lff, filter_query)
if len(sort_by) > 0:
lff = sort_table_data(lff, sort_by)
# Matérialisation des filtres
dff: pl.DataFrame = lff.collect()
height = dff.height
nb_rows = f"{format_number(height)} lignes ({format_number(dff.select('uid').unique().height)} marchés)"
# Pagination des données
start_row = page_current * page_size
# end_row = (page_current + 1) * page_size
dff = dff.slice(start_row, page_size)
# Tout devient string
dff = dff.cast(pl.String)
# Remplace les strings null par "", mais pas les numeric null
dff = dff.fill_null("")
# Ajout des liens vers l'annuaire des entreprises
dff = add_links(dff)
# Ajout des liens vers les fichiers Open Data
dff = add_resource_link(dff)
# Formatage des montants
dff = format_values(dff)
columns, tooltip = setup_table_columns(dff)
dicts = dff.to_dicts()
if height > 65000:
download_disabled = True
download_text = "Téléchargement désactivé au-delà de 65 000 lignes"
download_title = "Excel ne supporte pas d'avoir plus de 65 000 URLs dans une même feuille de calcul. Contactez-moi pour me présenter votre besoin en téléchargement afin que je puisse adapter la solution."
else:
download_disabled = False
download_text = "Télécharger au format Excel"
download_title = ""
return (
dicts,
columns,
tooltip,
data_timestamp + 1,
nb_rows,
download_disabled,
download_text,
download_title,
return prepare_table_data(
None, data_timestamp, filter_query, page_current, page_size, sort_by
)
src/pages/titulaire.py
+117 -61
View File
@@ -6,14 +6,16 @@ from dash import Input, Output, State, callback, dcc, html, register_page
from src.callbacks import get_top_org_table
from src.figures import DataTable, point_on_map
from src.utils import (
add_links_in_dict,
df,
filter_table_data,
format_number,
format_values,
get_annuaire_data,
get_button_properties,
get_default_hidden_columns,
get_departement_region,
meta_content,
setup_table_columns,
prepare_table_data,
sort_table_data,
)
register_page(
@@ -26,13 +28,22 @@ register_page(
order=5,
)
# 21690123100011
datatable = html.Div(
className="marches_table",
children=DataTable(
dtid="titulaire_datatable",
page_action="custom",
filter_action="custom",
sort_action="custom",
page_size=10,
hidden_columns=get_default_hidden_columns(page="titulaire"),
),
)
layout = [
dcc.Store(id="titulaire_data", storage_type="memory"),
dcc.Location(id="url", refresh="callback-nav"),
html.Div(
className="container",
children=[
html.Div(
className="wrapper",
@@ -86,9 +97,9 @@ layout = [
html.P(id="titulaire_acheteurs_differents"),
html.Button(
"Téléchargement au format Excel",
id="btn-download-titulaire-data",
id="btn-download-data-titulaire",
),
dcc.Download(id="download-titulaire-data"),
dcc.Download(id="download-data-titulaire"),
],
),
html.Div(className="org_map", id="titulaire_map"),
@@ -103,7 +114,26 @@ layout = [
),
# récupérer les données de l'acheteur sur l'api annuaire
html.H3("Derniers marchés publics remportés"),
html.Div(id="titulaire_last_marches", children=""),
dcc.Loading(
overlay_style={"visibility": "visible", "filter": "blur(2px)"},
id="loading-home",
type="default",
children=[
html.Div(
[
html.P("lignes", id="titulaire_nb_rows"),
html.Button(
"Téléchargement désactivé au-delà de 65 000 lignes",
id="btn-download-filtered-data-titulaire",
disabled=True,
),
dcc.Download(id="titulaire-download-filtered-data"),
],
className="table-menu",
),
datatable,
],
),
],
),
]
@@ -158,88 +188,78 @@ def update_titulaire_infos(url):
def update_titulaire_stats(data):
dff = pl.DataFrame(data)
if dff.height == 0:
dff = pl.DataFrame(schema=dff.collect_schema())
nb_marches = 0
nb_acheteurs = 0
else:
df_marches = dff.unique("uid")
nb_marches = format_number(df_marches.height)
# somme_marches = format_number(int(df_marches.select(pl.sum("montant")).item()))
marches_remportes = [html.Strong(nb_marches), " marchés et accord-cadres remportés"]
# + ", pour un total de ", html.Strong(somme_marches + " €")]
del df_marches
nb_acheteurs = dff.unique("acheteur_id").height
nb_acheteurs = [
texte_marches_remportes = [
html.Strong(nb_marches),
" marchés et accord-cadres remportés",
]
# + ", pour un total de ", html.Strong(somme_marches + " €")]
texte_nb_acheteurs = [
html.Strong(format_number(nb_acheteurs)),
" acheteurs (SIRET) différents",
]
del dff
return marches_remportes, nb_acheteurs
return texte_marches_remportes, texte_nb_acheteurs
@callback(
Output(component_id="titulaire_data", component_property="data"),
Output("btn-download-data-titulaire", "disabled"),
Output("btn-download-data-titulaire", "children"),
Output("btn-download-data-titulaire", "title"),
Input(component_id="url", component_property="pathname"),
Input(component_id="titulaire_year", component_property="value"),
)
def get_titulaire_marches_data(url, titulaire_year: str) -> list[dict]:
def get_titulaire_marches_data(url, titulaire_year: str) -> tuple:
titulaire_siret = url.split("/")[-1]
lff = df.lazy()
lff = lff.filter(
(pl.col("titulaire_id") == titulaire_siret)
& (pl.col("titulaire_typeIdentifiant") == "SIRET")
)
lff = lff.select(
"id",
"uid",
"objet",
"dateNotification",
"acheteur_id",
"acheteur_nom",
"distance",
"montant",
"codeCPV",
"dureeMois",
)
if titulaire_year and titulaire_year != "Toutes":
lff = lff.filter(
pl.col("dateNotification").cast(pl.String).str.starts_with(titulaire_year)
)
lff = lff.sort(["dateNotification", "uid"], descending=True, nulls_last=True)
lff = lff.fill_null("")
data = lff.collect(engine="streaming").to_dicts()
return data
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(component_id="titulaire_last_marches", component_property="children"),
Input(component_id="titulaire_data", component_property="data"),
Output("titulaire_datatable", "data"),
Output("titulaire_datatable", "columns"),
Output("titulaire_datatable", "tooltip_header"),
Output("titulaire_datatable", "data_timestamp"),
Output("titulaire_nb_rows", "children"),
Output("btn-download-filtered-data-titulaire", "disabled"),
Output("btn-download-filtered-data-titulaire", "children"),
Output("btn-download-filtered-data-titulaire", "title"),
Input("titulaire_data", "data"),
Input("titulaire_datatable", "page_current"),
Input("titulaire_datatable", "page_size"),
Input("titulaire_datatable", "filter_query"),
Input("titulaire_datatable", "sort_by"),
State("titulaire_datatable", "data_timestamp"),
)
def get_last_marches_table(data) -> html.Div:
dff = pl.DataFrame(data)
dff = dff.cast(pl.String)
dff = dff.fill_null("")
dff = format_values(dff)
columns, tooltip = setup_table_columns(
dff, hideable=False, exclude=["acheteur_id", "id"]
def get_last_marches_data(
data, page_current, page_size, filter_query, sort_by, data_timestamp
) -> list[dict]:
return prepare_table_data(
data, data_timestamp, filter_query, page_current, page_size, sort_by
)
data = dff.to_dicts()
# Idéalement on utiliserait add_org_links(), mais le résultat attendu
# est différent de home.py (Tableau)
data = add_links_in_dict(data, "acheteur")
table = html.Div(
className="marches_table",
children=DataTable(
dtid="titulaire_data_table",
data=data,
page_action="native",
filter_action="native",
columns=columns,
tooltip_header=tooltip,
page_size=10,
),
)
return table
@callback(
@@ -251,8 +271,8 @@ def get_top_acheteurs(data):
@callback(
Output("download-titulaire-data", "data"),
Input("btn-download-titulaire-data", "n_clicks"),
Output("download-data-titulaire", "data"),
Input("btn-download-data-titulaire", "n_clicks"),
State(component_id="titulaire_data", component_property="data"),
State(component_id="titulaire_nom", component_property="children"),
State(component_id="titulaire_year", component_property="value"),
@@ -273,3 +293,39 @@ def download_titulaire_data(
date = datetime.datetime.now().strftime("%Y-%m-%d_%H:%M:%S")
return dcc.send_bytes(to_bytes, filename=f"decp_{titulaire_nom}_{date}.xlsx")
@callback(
Output("titulaire-download-filtered-data", "data"),
State("titulaire_data", "data"),
Input("btn-download-filtered-data-titulaire", "n_clicks"),
State("titulaire_nom", "children"),
State("titulaire_datatable", "filter_query"),
State("titulaire_datatable", "sort_by"),
State("titulaire_datatable", "hidden_columns"),
prevent_initial_call=True,
)
def download_filtered_titulaire_data(
data, n_clicks, titulaire_nom, filter_query, sort_by, hidden_columns: list = None
):
lff: pl.LazyFrame = pl.LazyFrame(
data
) # start from the full titulaire data, not from paginated table data
# Les colonnes masquées sont supprimées
if hidden_columns:
lff = lff.drop(hidden_columns)
if filter_query:
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_{titulaire_nom}_{date}.xlsx"
)
src/utils.py
+136 -6
View File
@@ -7,7 +7,6 @@ from time import localtime, sleep
import polars as pl
import polars.selectors as cs
from httpx import get, post
from polars import Schema
from polars.exceptions import ComputeError
from unidecode import unidecode
@@ -331,7 +330,7 @@ def setup_table_columns(dff, hideable: bool = True, exclude: list = None) -> tup
continue
column_object = data_schema.get(column_id)
if column_object:
column_name = column_object.get("title", column_id)
column_name = column_object.get("title")
else:
column_name = column_id
@@ -356,18 +355,47 @@ def setup_table_columns(dff, hideable: bool = True, exclude: list = None) -> tup
return columns, tooltip
def get_default_hidden_columns(schema: Schema):
def get_default_hidden_columns(page):
if page == "acheteur":
displayed_columns = [
"uid",
"objet",
"dateNotification",
"titulaire_id",
"titulaire_typeIdentifiant",
"titulaire_nom",
"distance",
"montant",
"codeCPV",
"dureeRestanteMois",
]
elif page == "titulaire":
displayed_columns = [
"uid",
"objet",
"dateNotification",
"acheteur_id",
"acheteur_nom",
"distance",
"montant",
"codeCPV",
"dureeRestanteMois",
]
else:
displayed_columns = os.getenv("DISPLAYED_COLUMNS")
hidden_columns = []
if displayed_columns:
if displayed_columns is None:
raise ValueError("DISPLAYED_COLUMNS n'est pas configuré")
else:
displayed_columns = displayed_columns.replace(" ", "").split(",")
hidden_columns = []
for col in schema.names():
if col in displayed_columns:
continue
else:
hidden_columns.append(col)
return hidden_columns
raise ValueError("DISPLAYED_COLUMNS n'est pas configuré")
def get_data_schema() -> dict:
@@ -503,9 +531,111 @@ def search_org(dff: pl.DataFrame, query: str, org_type: str) -> pl.DataFrame:
return dff
def prepare_table_data(
data, data_timestamp, filter_query, page_current, page_size, sort_by
):
"""
Fonction de préparation des données pour les datatables, afin de permettre une gestion fine des logiques,
notamment pour les filtres et les tris.
:param data
:param data_timestamp:
:param filter_query:
:param page_current:
:param page_size:
:param sort_by:
:return:
"""
if os.getenv("DEVELOPMENT").lower() == "true":
print(" + + + + + + + + + + + + + + + + + + ")
# Récupération des données
if isinstance(data, list):
lff: pl.LazyFrame = pl.LazyFrame(data)
else:
lff: pl.LazyFrame = df.lazy() # start from the original data
# Application des filtres
if filter_query:
lff = filter_table_data(lff, filter_query)
# Application des tris
if len(sort_by) > 0:
lff = sort_table_data(lff, sort_by)
# Matérialisation des filtres
dff: pl.DataFrame = lff.collect()
height = dff.height
if height > 0:
nb_rows = f"{format_number(height)} lignes ({format_number(dff.select('uid').unique().height)} marchés)"
else:
nb_rows = "0 lignes (0 marchés)"
# Pagination des données
start_row = page_current * page_size
# end_row = (page_current + 1) * page_size
dff = dff.slice(start_row, page_size)
# Tout devient string
dff = dff.cast(pl.String)
# Remplace les strings null par "", mais pas les numeric null
dff = dff.fill_null("")
# Ajout des liens vers l'annuaire des entreprises
dff = add_links(dff)
# Ajout des liens vers les fichiers Open Data
if "sourceFile" in dff.columns:
dff = add_resource_link(dff)
# Formatage des montants
if height > 0:
dff = format_values(dff)
# Récupération des colonnes et tooltip
columns, tooltip = setup_table_columns(dff)
dicts = dff.to_dicts()
# Propriétés du bouton de téléchargement
download_disabled, download_text, download_title = get_button_properties(height)
return (
dicts,
columns,
tooltip,
data_timestamp + 1,
nb_rows,
download_disabled,
download_text,
download_title,
)
def get_button_properties(height):
if height > 65000:
download_disabled = True
download_text = "Téléchargement désactivé au-delà de 65 000 lignes"
download_title = "Excel ne supporte pas d'avoir plus de 65 000 URLs dans une même feuille de calcul. Contactez-moi pour me présenter votre besoin en téléchargement afin que je puisse adapter la solution."
elif height == 0:
download_disabled = True
download_text = "Pas de données à télécharger"
download_title = ""
else:
download_disabled = False
download_text = "Télécharger au format Excel"
download_title = ""
return download_disabled, download_text, download_title
df: pl.DataFrame = get_decp_data()
schema = df.collect_schema()
df_acheteurs = get_org_data(df, "acheteur")
df_titulaires = get_org_data(df, "titulaire")
departements = get_departements()
domain_name = (
"test.decp.info" if os.getenv("DEVELOPMENT").lower() == "true" else "decp.info"