Merge branch 'feature/58_search' into dev

README.md

@@ -40,8 +40,9 @@ Ne pas oublier de mettre à jour les fichier .env.
 
 #### 2.2.0 ()
 
+- 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 ([#54](https://github.com/ColinMaudry/decp.info/issues/54))
+- Moins de colonnes affichées par défaut dans Tableau ([#54](https://github.com/ColinMaudry/decp.info/issues/54))
 
 ##### 2.1.7 (11 novembre 2025)
 

pyproject.toml

@@ -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

@@ -148,6 +148,35 @@ td[data-dash-column="objet"],td[data-dash-column="titulaire_nom"],td[data-dash-c
   margin-top: 25px;
 }
 
+/* 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 {
@@ -177,7 +206,7 @@ summary > h3 {
   padding-top: 28px;
 }
 
-/* Vue acheteur/titulaire    */
+/* Vue acheteur/titulaire/recherche    */
 .wrapper {
   display: grid;
   grid-gap: 10px;
@@ -185,9 +214,6 @@ summary > h3 {
   justify-content: space-between;
 }
 
-.wrapper > div {
-}
-
 .org_title {
   grid-column: 1 / 3;
   grid-row: 1;

src/pages/recherche.py

@@ -0,0 +1,104 @@
+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...",
+        ),
+        # 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

@@ -25,7 +25,7 @@ schema = df.collect_schema()
 name = "Tableau"
 register_page(
     __name__,
-    path="/",
+    path="/tableau",
     title=meta_content["title"],
     name=name,
     description=meta_content["description"],

src/utils.py

@@ -8,6 +8,7 @@ import polars.selectors as cs
 from httpx import get
 from polars import Schema
 from polars.exceptions import ComputeError
+from unidecode import unidecode
 
 operators = [
     ["s<", "<"],
@@ -50,30 +51,47 @@ def add_resource_link(dff: pl.DataFrame) -> pl.DataFrame:
     return dff
 
 
-def add_links(dff: pl.DataFrame):
+def add_links(dff: pl.DataFrame, target: str = "_blank"):
-    dff = dff.with_columns(
+    for col in ["uid", "acheteur_nom", "titulaire_nom", "acheteur_id", "titulaire_id"]:
-        pl.when(pl.col("titulaire_typeIdentifiant") == "SIRET")
+        if col in dff.columns:
-        .then(
+            if col.startswith("titulaire_"):
-            '<a href = "/titulaires/'
+                dff = dff.with_columns(
-            + pl.col("titulaire_id")
+                    pl.when(
-            + '">'
+                        pl.Expr.or_(
-            + pl.col("titulaire_id")
+                            pl.col("titulaire_typeIdentifiant").is_null(),
-            + "</a>"
+                            pl.col("titulaire_typeIdentifiant") == "SIRET",
-        )
+                        )
-        .otherwise(pl.col("titulaire_id"))
+                    )
-        .alias("titulaire_id")
+                    .then(
-    )
+                        '<a href = "/titulaires/'
-
+                        + pl.col("titulaire_id")
-    for column, path in [("acheteur_id", "acheteurs"), ("uid", "marches")]:
+                        + f'" target="{target}">'
-        dff = dff.with_columns(
+                        + pl.col(col)
-            (
+                        + "</a>"
-                f'<a href = "/{path}/'
+                    )
-                + pl.col(column)
+                    .otherwise(pl.col(col))
-                + '" target="_blank">'
+                    .alias(col)
-                + pl.col(column)
+                )
-                + "</a>"
+            if col.startswith("acheteur_"):
-            ).alias(column)
+                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
 
 
@@ -208,6 +226,18 @@ 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)
@@ -364,7 +394,84 @@ def get_data_schema() -> dict:
     return new_schema
 
 
+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"))
+
+    sleep(0.2)
+
+    # 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"