Colin Maudry
278 lines
9.6 KiB
Python
278 lines
9.6 KiB
Python
import datetime
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import polars as pl
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from dash import Input, Output, State, callback, dash_table, dcc, html, register_page
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from src.figures import point_on_map
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from src.utils import (
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add_links_in_dict,
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df,
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format_montant,
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format_number,
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get_annuaire_data,
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get_departement_region,
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meta_content,
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setup_table_columns,
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)
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register_page(
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__name__,
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path_template="/acheteurs/<acheteur_id>",
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title=meta_content["title"],
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name="Acheteur",
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description=meta_content["description"],
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image_url=meta_content["image_url"],
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order=5,
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)
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layout = [
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dcc.Store(id="acheteur_data", storage_type="memory"),
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dcc.Location(id="url", refresh="callback-nav"),
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html.Div(
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className="container",
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children=[
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html.Div(
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className="wrapper",
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children=[
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html.H2(
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className="org_title",
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children=[
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html.Span(id="acheteur_siret"),
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" - ",
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html.Span(id="acheteur_nom"),
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],
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),
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html.Div(
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className="org_year",
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children=dcc.Dropdown(
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id="acheteur_year",
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options=["Toutes"]
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+ [
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str(year)
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for year in range(
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2018, int(datetime.date.today().year) + 1
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)
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],
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placeholder="Année",
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),
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),
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html.Div(
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className="org_infos",
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children=[
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# TODO: ajouter le type d'acheteur : commune, CD, CR, etc.
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html.P(["Commune : ", html.Strong(id="acheteur_commune")]),
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html.P(
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[
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"Département : ",
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html.Strong(id="acheteur_departement"),
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]
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),
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html.P(["Région : ", html.Strong(id="acheteur_region")]),
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html.A(
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id="acheteur_lien_annuaire",
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children="Plus de détails sur l'Annuaire des entreprises",
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target="_blank",
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),
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],
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),
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html.Div(
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className="org_stats",
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children=[
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html.P(id="acheteur_titre_stats"),
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html.P(id="acheteur_marches_attribues"),
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html.P(id="acheteur_titulaires_differents"),
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html.Button(
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"Téléchargement au format Excel",
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id="btn-download-acheteur-data",
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),
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dcc.Download(id="download-acheteur-data"),
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],
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),
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html.Div(className="org_map", id="acheteur_map"),
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],
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),
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# récupérer les données de l'acheteur sur l'api annuaire
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html.H3("Derniers marchés publics attribués"),
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html.Div(id="acheteur_last_marches", children=""),
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],
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),
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]
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@callback(
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Output(component_id="acheteur_siret", component_property="children"),
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Output(component_id="acheteur_nom", component_property="children"),
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Output(component_id="acheteur_commune", component_property="children"),
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Output(component_id="acheteur_map", component_property="children"),
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Output(component_id="acheteur_departement", component_property="children"),
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Output(component_id="acheteur_region", component_property="children"),
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Output(component_id="acheteur_lien_annuaire", component_property="href"),
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Input(component_id="url", component_property="pathname"),
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)
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def update_acheteur_infos(url):
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acheteur_siret = url.split("/")[-1]
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if len(acheteur_siret) != 14:
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acheteur_siret = (
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f"Le SIRET renseigné doit faire 14 caractères ({acheteur_siret})"
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)
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data = get_annuaire_data(acheteur_siret)
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data_etablissement = data["matching_etablissements"][0]
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acheteur_map = point_on_map(
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data_etablissement["latitude"], data_etablissement["longitude"]
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)
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code_departement, nom_departement, nom_region = get_departement_region(
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data_etablissement["code_postal"]
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)
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departement = f"{nom_departement} ({code_departement})"
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lien_annuaire = (
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f"https://annuaire-entreprises.data.gouv.fr/etablissement/{acheteur_siret}"
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)
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return (
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acheteur_siret,
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data["nom_raison_sociale"],
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data_etablissement["libelle_commune"],
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acheteur_map,
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departement,
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nom_region,
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lien_annuaire,
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)
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@callback(
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Output(component_id="acheteur_marches_attribues", component_property="children"),
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Output(
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component_id="acheteur_titulaires_differents", component_property="children"
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),
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Input(component_id="acheteur_data", component_property="data"),
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)
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def update_acheteur_stats(data):
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df = pl.DataFrame(data)
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if df.height == 0:
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df = pl.DataFrame(schema=df.collect_schema())
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df_marches = df.unique("id")
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nb_marches = format_number(df_marches.height)
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# somme_marches = format_number(int(df_marches.select(pl.sum("montant")).item()))
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marches_attribues = [html.Strong(nb_marches), " marchés et accord-cadres attribués"]
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# + ", pour un total de ", html.Strong(somme_marches + " €")]
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del df_marches
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nb_titulaires = df.unique("titulaire_id").height
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nb_titulaires = [
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html.Strong(format_number(nb_titulaires)),
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" titulaires (SIRET) différents",
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]
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del df
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return marches_attribues, nb_titulaires
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@callback(
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Output(component_id="acheteur_data", component_property="data"),
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Input(component_id="url", component_property="pathname"),
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Input(component_id="acheteur_year", component_property="value"),
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)
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def get_acheteur_marches_data(url, acheteur_year: str) -> list[dict]:
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acheteur_siret = url.split("/")[-1]
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lff = df.lazy()
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lff = lff.filter(pl.col("acheteur_id") == acheteur_siret)
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lff = lff.select(
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"id",
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"uid",
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"objet",
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"dateNotification",
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"titulaire_id",
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"titulaire_typeIdentifiant",
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"titulaire_nom",
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"montant",
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"codeCPV",
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"dureeMois",
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)
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if acheteur_year and acheteur_year != "Toutes":
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lff = lff.filter(
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pl.col("dateNotification").cast(pl.String).str.starts_with(acheteur_year)
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)
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lff = lff.sort(["dateNotification", "id"], descending=True, nulls_last=True)
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data = lff.collect(engine="streaming").to_dicts()
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return data
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@callback(
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Output(component_id="acheteur_last_marches", component_property="children"),
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Input(component_id="acheteur_data", component_property="data"),
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)
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def get_last_marches_table(data) -> html.Div:
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dff = pl.DataFrame(data)
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dff = dff.cast(pl.String)
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dff = dff.fill_null("")
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dff = format_montant(dff)
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columns, tooltip = setup_table_columns(
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dff,
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hideable=False,
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exclude=["titulaire_id", "titulaire_typeIdentifiant", "uid"],
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)
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data = dff.to_dicts()
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data = add_links_in_dict(data, "titulaire")
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table = html.Div(
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className="marches_table",
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id="acheteur_datatable",
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children=dash_table.DataTable(
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data=data,
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markdown_options={"html": True},
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page_action="native",
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filter_action="native",
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filter_options={"case": "insensitive", "placeholder_text": "Filtrer..."},
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columns=columns,
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tooltip_header=tooltip,
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tooltip_duration=8000,
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tooltip_delay=350,
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cell_selectable=False,
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page_size=10,
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style_cell_conditional=[
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{
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"if": {"column_id": "objet"},
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"minWidth": "300px",
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"textAlign": "left",
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"overflow": "hidden",
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"lineHeight": "14px",
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"whiteSpace": "normal",
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},
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{
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"if": {"column_id": "titulaire_nom"},
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"minWidth": "200px",
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"textAlign": "left",
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"overflow": "hidden",
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"lineHeight": "18px",
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"whiteSpace": "normal",
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},
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],
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),
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)
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return table
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@callback(
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Output("download-acheteur-data", "data"),
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Input("btn-download-acheteur-data", "n_clicks"),
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State(component_id="acheteur_data", component_property="data"),
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State(component_id="acheteur_nom", component_property="children"),
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State(component_id="acheteur_year", component_property="value"),
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prevent_initial_call=True,
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)
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def download_acheteur_data(
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n_clicks,
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data: [dict],
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acheteur_nom: str,
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annee: str,
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):
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df_to_download = pl.DataFrame(data)
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def to_bytes(buffer):
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df_to_download.write_excel(
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buffer, worksheet="DECP" if annee in ["Toutes", None] else annee
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)
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date = datetime.datetime.now().strftime("%Y-%m-%d_%H:%M:%S")
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return dcc.send_bytes(to_bytes, filename=f"decp_{acheteur_nom}_{date}.xlsx")
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