colin/colibre
1
0
Fork 0
Code Issues 30 Pull Requests Actions Packages Projects Releases 33 Activity

Merge branch 'release/2.2.0'

Browse Source
This commit is contained in:
Colin Maudry
2025-11-13 14:26:41 +01:00
parent 2f3ce6a467 18f8388df5
commit c3c868d52a
11 changed files with 490 additions and 70 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.template.env
+8
View File
@@ -6,9 +6,17 @@ SOURCE_STATS_CSV_PATH="https://www.data.gouv.fr/api/1/datasets/r/8ded94de-3b80-4
# Chemin vers le schéma de données
DATA_SCHEMA_PATH=https://www.data.gouv.fr/api/1/datasets/r/9a4144c0-ee44-4dec-bee5-bbef38191d9a
# Colonnes masquées par défaut
DISPLAYED_COLUMNS="uid, acheteur_id, acheteur_nom, montant, objet, titulaire_nom, titulaire_id, dateNotification, dureeMois, acheteur_departement_code, sourceDataset"
# Formulaire de contact
SENDER_SERVER_DOMAIN="mail.example.com" # serveur SMTP
LOGIN_PASSWORD="" # mot de passe du serveur
LOGIN_EMAIL="connect@example.fr" # adresse utilisée pour se connecter au serveur SMTP
FROM_EMAIL="from@example.com" # adresse d'envoi des emails (From)
TO_EMAIL="to@example.com" # adresse de destination des emails (To)
# Matomo
MATOMO_ID_SITE=
MATOMO_BASE_URL=
MATOMO_TOKEN=
README.md
+6
View File
@@ -38,6 +38,12 @@ Ne pas oublier de mettre à jour les fichier .env.
## Notes de version
#### 2.2.0 (13 novembre 2025)
- Moteur de recherche (acheteurs et titulaires) en page d'accueil ([#58](https://github.com/ColinMaudry/decp.info/issues/58))
- Top acheteurs / titulaires par montant attribué/remporté (([#55](https://github.com/ColinMaudry/decp.info/issues/55)))
- Moins de colonnes affichées par défaut dans Tableau ([#54](https://github.com/ColinMaudry/decp.info/issues/54))
##### 2.1.7 (11 novembre 2025)
- Remplacement du formulaire de contact par une adresse email
pyproject.toml
+3 -2
View File
@@ -1,7 +1,7 @@
[project]
name = "decp.info"
description = "Interface d'exploration et d'analyse des marchés publics français."
version = "2.1.7"
version = "2.2.0"
requires-python = ">= 3.10"
authors = [
{ name = "Colin Maudry", email = "colin+decp@maudry.com" }
@@ -16,7 +16,8 @@ dependencies = [
"xlsxwriter",
"plotly[express]",
"httpx",
"pandas" # utilisé pour la création de certains graphiques
"pandas", # utilisé pour la création de certains graphiques
"unidecode"
]
[project.optional-dependencies]
src/assets/style.css
+38 -6
View File
@@ -53,9 +53,10 @@ div.logo > a {
/* Réduire la taille du texte de la colonne Objet */
td[data-dash-column="objet"] {
/*
td[data-dash-column="objet"],td[data-dash-column="titulaire_nom"],td[data-dash-column="acheteur_nom"], {
font-size: 85%;
}
}*/
/* Couleur des en-têtes */
.dash-table-container
@@ -149,6 +150,35 @@ td[data-dash-column="objet"] {
font-size: 90%;
}
/* Page de recherche */
#search {
margin: 50px auto 0px auto;
width: 450px;
font-size: 18px;
height: 30px;
display: block;
}
.search_options {
margin: 16px auto;
width: 450px;
}
.search_options input {
margin-right: 12px;
}
.results_acheteur {
grid-column: 1;
grid-row: 1;
}
.results_titulaire {
grid-column: 2;
grid-row: 1;
}
/* Menu de navigation */
.navbar {
@@ -178,7 +208,7 @@ summary > h3 {
padding-top: 28px;
}
/* Vue acheteur/titulaire */
/* Vue acheteur/titulaire/recherche */
.wrapper {
display: grid;
grid-gap: 10px;
@@ -186,9 +216,6 @@ summary > h3 {
justify-content: space-between;
}
.wrapper > div {
}
.org_title {
grid-column: 1 / 3;
grid-row: 1;
@@ -218,6 +245,11 @@ summary > h3 {
grid-row: 2;
}
.org_top {
grid-column: 1/3;
grid-row: 3;
}
/* Vue marché */
.marche_infos p {
src/callbacks.py
+65
View File
@@ -0,0 +1,65 @@
import polars as pl
from dash import dash_table, html
from utils import add_links_in_dict, format_values, setup_table_columns
def get_top_org_table(data, org_type: str):
dff = pl.DataFrame(data)
if dff.height == 0:
return html.Div()
dff = dff.select(
["uid", f"{org_type}_id", f"{org_type}_nom", "distance", "montant"]
)
dff_nb = dff.group_by(f"{org_type}_id", f"{org_type}_nom", "distance").agg(
pl.len().alias("Attributions"), pl.sum("montant").alias("montant")
)
dff_nb = dff_nb.sort(by="montant", descending=True)
dff_nb = dff_nb.cast(pl.String)
dff_nb = dff_nb.fill_null("")
dff_nb = format_values(dff_nb)
columns, tooltip = setup_table_columns(
dff_nb, hideable=False, exclude=[f"{org_type}_id"]
)
data = dff_nb.to_dicts()
data = add_links_in_dict(data, f"{org_type}")
return dash_table.DataTable(
data=data,
markdown_options={"html": True},
page_action="native",
page_size=10,
columns=columns,
cell_selectable=False,
tooltip_header=tooltip,
style_cell_conditional=[
{
"if": {"column_id": "objet"},
"minWidth": "350px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "14px",
"whiteSpace": "normal",
"fontSize": "85%",
},
{
"if": {"column_id": "acheteur_nom"},
"minWidth": "200px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "16px",
# "fontSize": "85%",
"whiteSpace": "normal",
},
{
"if": {"column_id": "titulaire_nom"},
"minWidth": "200px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "16px",
"whiteSpace": "normal",
# "fontSize": "85%",
},
],
)
src/pages/acheteur.py
+28 -9
View File
@@ -3,12 +3,13 @@ import datetime
import polars as pl
from dash import Input, Output, State, callback, dash_table, dcc, html, register_page
from src.callbacks import get_top_org_table
from src.figures import point_on_map
from src.utils import (
add_links_in_dict,
df,
format_montant,
format_number,
format_values,
get_annuaire_data,
get_departement_region,
meta_content,
@@ -89,6 +90,13 @@ layout = [
],
),
html.Div(className="org_map", id="acheteur_map"),
html.Div(
className="org_top",
children=[
html.H3("Top titulaires"),
html.Div(className="marches_table", id="top10_titulaires"),
],
),
],
),
# récupérer les données de l'acheteur sur l'api annuaire
@@ -146,22 +154,22 @@ def update_acheteur_infos(url):
Input(component_id="acheteur_data", component_property="data"),
)
def update_acheteur_stats(data):
df = pl.DataFrame(data)
if df.height == 0:
df = pl.DataFrame(schema=df.collect_schema())
df_marches = df.unique("id")
dff = pl.DataFrame(data)
if dff.height == 0:
dff = pl.DataFrame(schema=df.collect_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 = df.unique("titulaire_id").height
nb_titulaires = dff.unique("titulaire_id").height
nb_titulaires = [
html.Strong(format_number(nb_titulaires)),
" titulaires (SIRET) différents",
]
del df
del dff
return marches_attribues, nb_titulaires
@@ -183,6 +191,7 @@ def get_acheteur_marches_data(url, acheteur_year: str) -> list[dict]:
"titulaire_id",
"titulaire_typeIdentifiant",
"titulaire_nom",
"distance",
"montant",
"codeCPV",
"dureeMois",
@@ -203,9 +212,11 @@ def get_acheteur_marches_data(url, acheteur_year: str) -> list[dict]:
)
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_montant(dff)
dff = format_values(dff)
columns, tooltip = setup_table_columns(
dff,
hideable=False,
@@ -235,7 +246,7 @@ def get_last_marches_table(data) -> html.Div:
"minWidth": "300px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "14px",
"lineHeight": "18px",
"whiteSpace": "normal",
},
{
@@ -252,6 +263,14 @@ def get_last_marches_table(data) -> html.Div:
return table
@callback(
Output(component_id="top10_titulaires", component_property="children"),
Input(component_id="acheteur_data", component_property="data"),
)
def get_top_titulaires(data):
return get_top_org_table(data, "titulaire")
@callback(
Output("download-acheteur-data", "data"),
Input("btn-download-acheteur-data", "n_clicks"),
src/pages/marche.py
+2 -2
View File
@@ -4,7 +4,7 @@ import polars as pl
from dash import Input, Output, callback, dcc, html, register_page
from polars import selectors as cs
from src.utils import data_schema, df, format_montant, meta_content
from src.utils import data_schema, df, format_values, meta_content
register_page(
__name__,
@@ -75,7 +75,7 @@ def get_marche_data(url) -> tuple[dict, list]:
# Données du marché
dff_marche = lff.unique("uid").collect(engine="streaming")
dff_marche = format_montant(dff_marche)
dff_marche = format_values(dff_marche)
return dff_marche.to_dicts()[0], dff_titulaires.to_dicts()
src/pages/recherche.py
+105
View File
@@ -0,0 +1,105 @@
from dash import Input, Output, callback, dash_table, dcc, html, register_page
from src.utils import (
df_acheteurs,
df_titulaires,
meta_content,
search_org,
setup_table_columns,
)
name = "Recherche"
register_page(
__name__,
path="/",
title=meta_content["title"],
name=name,
description=meta_content["description"],
image_url=meta_content["image_url"],
order=0,
)
layout = html.Div(
className="container",
children=[
dcc.Input(
id="search",
type="text",
placeholder="Nom d'acheteur, d'entreprise, SIREN...",
autoFocus=True,
),
# html.Div(
# className="search_options",
# children=[dcc.RadioItems(options=["Acheteur(s)"])],
# ),
html.Div(id="search_results", className="wrapper"),
],
)
@callback(
Output("search_results", "children"),
Input("search", "value"),
prevent_initial_call=True,
)
def update_search_results(query):
if len(query) >= 1:
content = []
for org_type in ["acheteur", "titulaire"]:
if org_type == "acheteur":
dff = df_acheteurs
elif org_type == "titulaire":
dff = df_titulaires
else:
raise ValueError(f"{org_type} is not supported")
# Search acheteurs and titulaires using the same function
results = search_org(dff, query, org_type=org_type)
count = results.height
# Format output
columns, tooltip = setup_table_columns(results, hideable=False)
org_content = [
html.Div(
className=f"results_{org_type}",
children=[
html.H3(f"{org_type.title()}s : {count}"),
dash_table.DataTable(
columns=columns,
data=results.to_dicts(),
page_size=10,
# style_table={"overflowX": "auto"},
markdown_options={"html": True},
cell_selectable=False,
style_cell_conditional=[
{
"if": {"column_id": "acheteur_nom"},
"maxWidth": "250px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "18px",
"whiteSpace": "normal",
},
{
"if": {"column_id": "titulaire_nom"},
"maxWidth": "250px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "18px",
"whiteSpace": "normal",
},
],
),
],
)
if count > 0
else html.P(f"Aucun {org_type} trouvé."),
]
content.extend(org_content)
return content
else:
return html.P("")
src/pages/tableau.py
+8 -6
View File
@@ -9,8 +9,9 @@ from src.utils import (
add_resource_link,
df,
filter_table_data,
format_montant,
format_number,
format_values,
get_default_hidden_columns,
meta_content,
setup_table_columns,
sort_table_data,
@@ -24,7 +25,7 @@ schema = df.collect_schema()
name = "Tableau"
register_page(
__name__,
path="/",
path="/tableau",
title=meta_content["title"],
name=name,
description=meta_content["description"],
@@ -52,7 +53,7 @@ datatable = html.Div(
"minWidth": "350px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "14px",
"lineHeight": "18px",
"whiteSpace": "normal",
},
{
@@ -60,7 +61,7 @@ datatable = html.Div(
"minWidth": "250px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "14px",
"lineHeight": "18px",
"whiteSpace": "normal",
},
{
@@ -68,7 +69,7 @@ datatable = html.Div(
"minWidth": "250px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "14px",
"lineHeight": "18px",
"whiteSpace": "normal",
},
],
@@ -76,6 +77,7 @@ datatable = html.Div(
markdown_options={"html": True},
tooltip_duration=8000,
tooltip_delay=350,
hidden_columns=get_default_hidden_columns(schema),
),
)
@@ -206,7 +208,7 @@ def update_table(page_current, page_size, filter_query, sort_by, data_timestamp)
dff = add_resource_link(dff)
# Formatage des montants
dff = format_montant(dff)
dff = format_values(dff)
columns, tooltip = setup_table_columns(dff)
src/pages/titulaire.py
+21 -4
View File
@@ -3,12 +3,13 @@ import datetime
import polars as pl
from dash import Input, Output, State, callback, dash_table, dcc, html, register_page
from src.callbacks import get_top_org_table
from src.figures import point_on_map
from src.utils import (
add_links_in_dict,
df,
format_montant,
format_number,
format_values,
get_annuaire_data,
get_departement_region,
meta_content,
@@ -91,6 +92,13 @@ layout = [
],
),
html.Div(className="org_map", id="titulaire_map"),
html.Div(
className="org_top",
children=[
html.H3("Top acheteurs"),
html.Div(className="marches_table", id="top10_acheteurs"),
],
),
],
),
# récupérer les données de l'acheteur sur l'api annuaire
@@ -161,7 +169,7 @@ def update_titulaire_stats(data):
nb_acheteurs = dff.unique("acheteur_id").height
nb_acheteurs = [
html.Strong(format_number(nb_acheteurs)),
" titulaires (SIRET) différents",
" acheteurs (SIRET) différents",
]
del dff
@@ -187,6 +195,7 @@ def get_titulaire_marches_data(url, titulaire_year: str) -> list[dict]:
"dateNotification",
"acheteur_id",
"acheteur_nom",
"distance",
"montant",
"codeCPV",
"dureeMois",
@@ -219,7 +228,7 @@ def get_last_marches_table(data) -> html.Div:
dff = pl.DataFrame(data)
dff = dff.cast(pl.String)
dff = dff.fill_null("")
dff = format_montant(dff)
dff = format_values(dff)
columns, tooltip = setup_table_columns(
dff, hideable=False, exclude=["acheteur_id", "id"]
)
@@ -249,7 +258,7 @@ def get_last_marches_table(data) -> html.Div:
"minWidth": "300px",
"textAlign": "left",
"overflow": "hidden",
"lineHeight": "14px",
"lineHeight": "18px",
"whiteSpace": "normal",
},
{
@@ -266,6 +275,14 @@ def get_last_marches_table(data) -> html.Div:
return table
@callback(
Output(component_id="top10_acheteurs", component_property="children"),
Input(component_id="titulaire_data", component_property="data"),
)
def get_top_acheteurs(data):
return get_top_org_table(data, "acheteur")
@callback(
Output("download-titulaire-data", "data"),
Input("btn-download-titulaire-data", "n_clicks"),
src/utils.py
+206 -41
View File
@@ -1,22 +1,19 @@
import json
import logging
import os
from time import sleep
import uuid
from time import localtime, sleep
import polars as pl
import polars.selectors as cs
from httpx import get
from httpx import get, post
from polars import Schema
from polars.exceptions import ComputeError
operators = [
["s<", "<"],
["s>", ">"],
["i<", "<"],
["i>", ">"],
["icontains", "contains"],
]
from unidecode import unidecode
logger = logging.getLogger("decp.info")
logging.getLogger("httpx").setLevel("WARNING")
logging.basicConfig(
format="%(asctime)s %(levelname)-8s %(message)s",
level=logging.INFO,
@@ -25,6 +22,13 @@ logging.basicConfig(
def split_filter_part(filter_part):
operators = [
["s<", "<"],
["s>", ">"],
["i<", "<"],
["i>", ">"],
["icontains", "contains"],
]
print("filter part", filter_part)
for operator_group in operators:
if operator_group[0] in filter_part:
@@ -49,42 +53,60 @@ def add_resource_link(dff: pl.DataFrame) -> pl.DataFrame:
return dff
def add_links(dff: pl.DataFrame):
dff = dff.with_columns(
pl.when(pl.col("titulaire_typeIdentifiant") == "SIRET")
.then(
'<a href = "/titulaires/'
+ pl.col("titulaire_id")
+ '">'
+ pl.col("titulaire_id")
+ "</a>"
)
.otherwise(pl.col("titulaire_id"))
.alias("titulaire_id")
)
for column, path in [("acheteur_id", "acheteurs"), ("uid", "marches")]:
dff = dff.with_columns(
(
f'<a href = "/{path}/'
+ pl.col(column)
+ '" target="_blank">'
+ pl.col(column)
+ "</a>"
).alias(column)
)
def add_links(dff: pl.DataFrame, target: str = "_blank"):
for col in ["uid", "acheteur_nom", "titulaire_nom", "acheteur_id", "titulaire_id"]:
if col in dff.columns:
if col.startswith("titulaire_"):
dff = dff.with_columns(
pl.when(
pl.Expr.or_(
pl.col("titulaire_typeIdentifiant").is_null(),
pl.col("titulaire_typeIdentifiant") == "SIRET",
)
)
.then(
'<a href = "/titulaires/'
+ pl.col("titulaire_id")
+ f'" target="{target}">'
+ pl.col(col)
+ "</a>"
)
.otherwise(pl.col(col))
.alias(col)
)
if col.startswith("acheteur_"):
dff = dff.with_columns(
(
'<a href = "/acheteurs/'
+ pl.col("acheteur_id")
+ f'" target="{target}">'
+ pl.col(col)
+ "</a>"
).alias(col)
)
if col == "uid":
dff = dff.with_columns(
(
'<a href = "/marches/'
+ pl.col("uid")
+ f'" target="{target}">'
+ pl.col("uid")
+ "</a>"
).alias("uid")
)
return dff
def add_links_in_dict(data: list, org_type: str) -> list:
def add_links_in_dict(data: list[dict], org_type: str) -> list:
new_data = []
for marche in data:
org_id = marche[org_type + "_id"]
marche[org_type + "_nom"] = (
f'<a href="/{org_type}s/{org_id}">{marche[org_type + "_nom"]}</a>'
)
marche["id"] = f'<a href="/marches/{marche["uid"]}">{marche["id"]}</a>'
marche["uid"] = f'<a href="/marches/{marche["uid"]}">{marche["uid"]}</a>'
if marche.get("uid"):
marche["id"] = f'<a href="/marches/{marche["uid"]}">{marche["id"]}</a>'
marche["uid"] = f'<a href="/marches/{marche["uid"]}">{marche["uid"]}</a>'
new_data.append(marche)
return new_data
@@ -123,8 +145,8 @@ def format_number(number) -> str:
return number
def format_montant(dff: pl.DataFrame) -> pl.DataFrame:
def format_function(expr, scale=None):
def format_values(dff: pl.DataFrame) -> pl.DataFrame:
def format_montant(expr, scale=None):
# https://stackoverflow.com/a/78636786
expr = expr.cast(pl.String)
expr = expr.str.splitn(".", 2)
@@ -142,7 +164,7 @@ def format_montant(dff: pl.DataFrame) -> pl.DataFrame:
frac: pl.Expr = (
pl.when(frac.is_not_null() & ~frac.is_in(["0"]))
.then("," + frac)
.then("," + frac.str.head(2))
.otherwise(pl.lit(""))
)
@@ -154,7 +176,17 @@ def format_montant(dff: pl.DataFrame) -> pl.DataFrame:
return montant
dff = dff.with_columns(pl.col("montant").pipe(format_function).alias("montant"))
def format_distance(expr):
expr = expr.cast(pl.String)
return pl.concat_str(expr, pl.lit(" km"))
if "montant" in dff.columns:
dff = dff.with_columns(pl.col("montant").pipe(format_montant).alias("montant"))
if "distance" in dff.columns:
dff = dff.with_columns(
pl.col("distance").pipe(format_distance).alias("distance")
)
return dff
@@ -196,6 +228,18 @@ def get_decp_data() -> pl.DataFrame:
return lff.collect()
def get_org_data(dff: pl.DataFrame, org_type: str) -> pl.DataFrame:
lff = dff.lazy()
lff = lff.select(
"uid",
cs.starts_with(org_type).exclude(
f"{org_type}_latitude", f"{org_type}_longitude"
),
)
lff = lff.group_by(cs.starts_with(org_type)).len("Marchés")
return lff.collect()
def get_departements() -> dict:
with open("data/departements.json", "rb") as f:
data = json.load(f)
@@ -312,6 +356,20 @@ def setup_table_columns(dff, hideable: bool = True, exclude: list = None) -> tup
return columns, tooltip
def get_default_hidden_columns(schema: Schema):
displayed_columns = os.getenv("DISPLAYED_COLUMNS")
hidden_columns = []
if displayed_columns:
displayed_columns = displayed_columns.replace(" ", "").split(",")
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:
# Récupération du schéma des données tabulaires
path = os.getenv("DATA_SCHEMA_PATH")
@@ -338,7 +396,114 @@ def get_data_schema() -> dict:
return new_schema
def track_search(query):
if (
len(query) >= 4
and os.getenv("DEVELOPMENT").lower != "true"
and os.getenv("MATOMO_DOMAIN")
):
if os.getenv("DEVELOPMENT").lower() == "true":
url = "https://test.decp.info"
else:
url = "https://decp.info"
params = {
"idsite": os.getenv("MATOMO_ID_SITE"),
"url": url,
"rec": "1",
"action_name": "front_page_search",
"rand": uuid.uuid4().hex,
"apiv": "1",
"h": localtime().tm_hour,
"m": localtime().tm_min,
"s": localtime().tm_sec,
"search": query,
"token_auth": os.getenv("MATOMO_TOKEN"),
}
post(
url=f"https://{os.getenv('MATOMO_DOMAIN')}/matomo.php",
params=params,
).raise_for_status()
def search_org(dff: pl.DataFrame, query: str, org_type: str) -> pl.DataFrame:
"""
Search in either 'acheteur' or 'titulaire' DataFrame.
:param dff: Polars DataFrame with acheteur or titulaire columns
:param query: User search string
:param org_type: 'acheteur' or 'titulaire'
:return: Filtered DataFrame with 'matches' column
"""
if not query.strip():
return dff.select(pl.lit(False).alias("matches"))
# Enregistrement des recherche dans Matomo
track_search(query)
# Normalize query
normalized_query = unidecode(query.strip()).upper()
tokens = [" " + t.strip() for t in normalized_query.split() if t.strip()]
# Define columns based on entity type
cols = [
f"{org_type}_id",
f"{org_type}_nom",
f"{org_type}_departement_nom",
f"{org_type}_departement_code",
f"{org_type}_commune_nom",
]
# Concatenate all fields into one string per row
org_str = pl.concat_str(pl.lit(" "), pl.col(cols), separator=" ")
# For each token, create a boolean column: True if token is found
token_matches = []
for token in tokens:
token_match = org_str.str.contains(token).alias(f"token_{token}")
token_matches.append(token_match)
# Count how many tokens match per row
match_score = pl.sum_horizontal(token_matches).alias("match_score")
# For each token, create a boolean column: True if token is found
token_matches = []
for token in tokens:
token_match = org_str.str.contains(token).alias(f"token_{token}")
token_matches.append(token_match)
# Sélection des colonnes
if org_type == "acheteur":
dff = dff.select(cols + ["Marchés"])
if org_type == "titulaire":
dff = dff.select(cols + ["Marchés", "titulaire_typeIdentifiant"])
# Apply and filter
dff = (
dff.with_columns(token_matches + [match_score])
.filter(pl.col("match_score") == len(tokens))
.sort("Marchés", descending=True)
.drop([f"token_{token}" for token in tokens])
)
# Format result
dff = add_links(dff, target="")
dff = dff.with_columns(
pl.concat_str(
pl.col(f"{org_type}_departement_nom"),
pl.lit(" ("),
pl.col(f"{org_type}_departement_code"),
pl.lit(")"),
).alias("Département")
)
dff = dff.select(f"{org_type}_id", f"{org_type}_nom", "Département", "Marchés")
return dff
df: pl.DataFrame = get_decp_data()
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"