Optimize regional BWK municipality selection

backend/app/api/routes/datasets.py

@@ -331,12 +331,19 @@ def select_vector_features(
         "limit": payload.limit,
     }
     full_dataset_area = False
+    preclipped_partition_filter = None
     if selection_area is not None:
         full_dataset_area = VectorFeatureService.can_use_full_area_fast_path(dataset, selection_area.id)
+        if not full_dataset_area:
+            preclipped_partition_filter = VectorFeatureService.preclipped_partition_filter(
+                dataset,
+                getattr(selection_area, "name", None),
+            )
         selection_kwargs.update(
             selection_geometry=selection_area.geometry,
             selection_area_id=selection_area.id,
             full_dataset_area=full_dataset_area,
+            preclipped_partition_filter=preclipped_partition_filter,
         )
     result = VectorFeatureService.select_features_by_bbox(db, **selection_kwargs)
     if VectorFeatureService.supports_selection_summary(dataset):
@@ -348,6 +355,7 @@ def select_vector_features(
         if selection_area is not None:
             summary_kwargs["selection_geometry"] = selection_area.geometry
             summary_kwargs["full_dataset_area"] = full_dataset_area
+            summary_kwargs["preclipped_partition_filter"] = preclipped_partition_filter
         result["summary"] = VectorFeatureService.summarize_features_by_bbox(db, **summary_kwargs)
     return envelope(VectorSelectionResponse(**result).model_dump(exclude_none=True))
 

backend/app/services/vector_feature_service.py

@@ -37,6 +37,10 @@ SEMANTIC_METRICS_DISABLED_OPERATOR_TOOLS = {
     "provision_regional_historical_landuse.py",
 }
 
+PRECLIPPED_MUNICIPALITY_PARTITION_OPERATOR_TOOLS = {
+    "provision_regional_bwk_natura2000.py",
+}
+
 
 SEMANTIC_SELECTION_METRICS: dict[str, tuple[dict[str, Any], ...]] = {
     "buildings": (
@@ -181,6 +185,30 @@ class VectorFeatureService:
         provenance = dataset.provenance_metadata if isinstance(dataset.provenance_metadata, dict) else {}
         return provenance.get("operator_tool") in FULL_AREA_CLIPPED_OPERATOR_TOOLS
 
+    @staticmethod
+    def preclipped_partition_filter(dataset: Dataset, selection_area_name: str | None) -> tuple[str, str] | None:
+        provenance = dataset.provenance_metadata if isinstance(dataset.provenance_metadata, dict) else {}
+        if provenance.get("operator_tool") not in PRECLIPPED_MUNICIPALITY_PARTITION_OPERATOR_TOOLS:
+            return None
+        source_metadata = dataset.source_metadata if isinstance(dataset.source_metadata, dict) else {}
+        if (
+            source_metadata.get("partitioned_source_audit") is not True
+            or source_metadata.get("geometry_clipped_to_area") is not True
+        ):
+            return None
+        normalized_name = str(selection_area_name or "").strip()
+        prefix = "Gemeente "
+        suffixes = (" - officiële grens", " - officiele grens")
+        if not normalized_name.startswith(prefix):
+            return None
+        municipality = normalized_name[len(prefix):]
+        for suffix in suffixes:
+            if municipality.endswith(suffix):
+                municipality = municipality[: -len(suffix)]
+                break
+        municipality = municipality.strip()
+        return ("municipality", municipality) if municipality else None
+
     @staticmethod
     def _feature_row(dataset_id: UUID, feature: dict[str, Any], index: int, feature_class: str | None) -> VectorFeature | None:
         geometry_payload = feature.get("geometry")
@@ -289,6 +317,7 @@ class VectorFeatureService:
         selection_geometry: Any | None = None,
         selection_area_id: UUID | None = None,
         full_dataset_area: bool = False,
+        preclipped_partition_filter: tuple[str, str] | None = None,
     ) -> dict[str, Any]:
         normalized_bbox = VectorFeatureService._normalize_selection_bbox(bbox)
         safe_limit = max(1, min(int(limit), 1000))
@@ -303,7 +332,10 @@ class VectorFeatureService:
             )
 
         query = db.query(VectorFeature).filter(VectorFeature.dataset_id == dataset_id)
-        if not full_dataset_area:
+        if preclipped_partition_filter is not None:
+            partition_property, partition_value = preclipped_partition_filter
+            query = query.filter(VectorFeature.properties_json.op("->>")(partition_property) == partition_value)
+        elif not full_dataset_area:
             query = query.filter(ST_Intersects(VectorFeature.geometry, selection_shape))
         if hasattr(query, "count"):
             total_feature_count = int(query.count())
@@ -327,6 +359,7 @@ class VectorFeatureService:
                 total_feature_count=total_feature_count,
                 selection_geometry=selection_geometry,
                 full_dataset_area=full_dataset_area,
+                preclipped_partition_filter=preclipped_partition_filter,
             )
 
         result = {
@@ -354,6 +387,7 @@ class VectorFeatureService:
         total_feature_count: int | None = None,
         selection_geometry: Any | None = None,
         full_dataset_area: bool = False,
+        preclipped_partition_filter: tuple[str, str] | None = None,
     ) -> dict[str, Any]:
         normalized_bbox = VectorFeatureService._normalize_selection_bbox(bbox)
         selection_shape = selection_geometry
@@ -366,8 +400,14 @@ class VectorFeatureService:
                 4326,
             )
         selection_filter = (VectorFeature.dataset_id == dataset.id,)
-        if not full_dataset_area:
+        if preclipped_partition_filter is not None:
+            partition_property, partition_value = preclipped_partition_filter
+            selection_filter += (
+                VectorFeature.properties_json.op("->>")(partition_property) == partition_value,
+            )
+        elif not full_dataset_area:
             selection_filter += (ST_Intersects(VectorFeature.geometry, selection_shape),)
+        selection_is_preclipped = full_dataset_area or preclipped_partition_filter is not None
         feature_count = total_feature_count
         if feature_count is None:
             feature_count = int(db.query(func.count(VectorFeature.id)).filter(*selection_filter).scalar() or 0)
@@ -438,7 +478,7 @@ class VectorFeatureService:
                 selection_filter=selection_filter,
                 selection_shape=selection_shape,
                 feature_count=feature_count,
-                full_dataset_area=full_dataset_area,
+                full_dataset_area=selection_is_preclipped,
             )
             for metric_config in metric_configs
         ]

backend/tests/test_sprint210_regional_bwk_natura2000.py

@@ -9,6 +9,9 @@ import sys
 import pytest
 from shapely.geometry import box, mapping, shape
 
+from app.models import Dataset
+from app.services.vector_feature_service import VectorFeatureService
+
 
 ROOT = Path(__file__).resolve().parents[2]
 SCRIPTS = ROOT / "scripts"
@@ -240,3 +243,28 @@ def test_regional_operator_is_packaged_release_checked_and_exact_area_is_preferr
     assert '"provision_regional_bwk_natura2000.py"' in service
     assert "dataset.area_id === selectedAreaId ? 10_000_000" in workspace
     assert "largestBwkSnapshot" in catalog
+
+
+def test_regional_bwk_uses_only_canonical_preclipped_municipality_partitions() -> None:
+    dataset = Dataset(
+        name="regional-bwk.geojson",
+        dataset_type="vector",
+        status="ready",
+        source_metadata={
+            "partitioned_source_audit": True,
+            "geometry_clipped_to_area": True,
+        },
+        provenance_metadata={"operator_tool": "provision_regional_bwk_natura2000.py"},
+    )
+
+    assert VectorFeatureService.preclipped_partition_filter(
+        dataset, "Gemeente Mol - officiële grens"
+    ) == ("municipality", "Mol")
+    assert VectorFeatureService.preclipped_partition_filter(
+        dataset, "Vervoerregio Kempen - officiële operationele grens"
+    ) is None
+
+    dataset.provenance_metadata = {"operator_tool": "unrelated_operator.py"}
+    assert VectorFeatureService.preclipped_partition_filter(
+        dataset, "Gemeente Mol - officiële grens"
+    ) is None