Spinner de chargemetn sur la préviusalisation des données

src/pages/observatoire.py

@@ -508,17 +508,26 @@ Alors, on fait comment ?
                 size="xl",
             ),
             # DataTable
-            html.Div(
+            dcc.Loading(
-                className="marches_table",
+                overlay_style={"visibility": "visible", "filter": "blur(2px)"},
-                children=DataTable(
+                id="loading-statistques",
-                    dtid="observatoire-preview-table",
+                type="default",
-                    page_size=5,
+                children=[
-                    page_action="custom",
+                    html.Div(
-                    sort_action="custom",
+                        className="marches_table",
-                    filter_action="custom",
+                        children=DataTable(
-                    hidden_columns=[],
+                            dtid="observatoire-preview-table",
-                    columns=[{"id": col, "name": col} for col in OBSERVATOIRE_COLUMNS],
+                            page_size=5,
-                ),
+                            page_action="custom",
+                            sort_action="custom",
+                            filter_action="custom",
+                            hidden_columns=[],
+                            columns=[
+                                {"id": col, "name": col} for col in OBSERVATOIRE_COLUMNS
+                            ],
+                        ),
+                    )
+                ],
             ),
         ],
     ),

tests/test_prepare_dashboard_data.py

@@ -1,47 +0,0 @@
-import polars as pl
-
-
-def test_returns_dataframe_with_year_filter():
-    from src.utils.data import prepare_dashboard_data
-
-    dff = prepare_dashboard_data(dashboard_year="2025")
-    assert isinstance(dff, pl.DataFrame)
-    assert dff.height == 1
-
-
-def test_year_mismatch_returns_empty():
-    from src.utils.data import prepare_dashboard_data
-
-    dff = prepare_dashboard_data(dashboard_year="2024")
-    assert isinstance(dff, pl.DataFrame)
-    assert dff.height == 0
-
-
-def test_acheteur_id_partial_match():
-    from src.utils.data import prepare_dashboard_data
-
-    dff = prepare_dashboard_data(
-        dashboard_year="2025",
-        dashboard_acheteur_id="12",
-    )
-    assert dff.height == 1
-
-
-def test_departement_in_clause():
-    from src.utils.data import prepare_dashboard_data
-
-    dff = prepare_dashboard_data(
-        dashboard_year="2025",
-        dashboard_acheteur_departement_code=["75", "92"],
-    )
-    assert dff.height == 1
-
-
-def test_montant_min_above_value_excludes_row():
-    from src.utils.data import prepare_dashboard_data
-
-    dff = prepare_dashboard_data(
-        dashboard_year="2025",
-        dashboard_montant_min=1000,
-    )
-    assert dff.height == 0