fix(map): make area analysis scale-aware

backend/app/api/routes/selection_partitions.py

@@ -0,0 +1,87 @@
+from __future__ import annotations
+
+from uuid import UUID
+
+from fastapi import APIRouter, Depends
+from sqlalchemy.orm import Session
+
+from app.core.errors import AppError
+from app.db.session import get_db
+from app.models import Area, Dataset
+from app.schemas.common import Envelope
+from app.schemas.operations import VectorSelectionResponse
+from app.schemas.selection_partitions import VectorPartitionSelectionRequest
+from app.services.vector_feature_service import VectorFeatureService
+from app.utils.response import envelope
+
+
+router = APIRouter(prefix="/projects/{project_id}", tags=["selection-partitions"])
+
+
+def _product_identity(dataset: Dataset) -> str:
+    metadata = dataset.source_metadata if isinstance(dataset.source_metadata, dict) else {}
+    return str(metadata.get("product_key") or dataset.reference_layer_name or "")
+
+
+@router.post(
+    "/datasets/vector/partitions/select",
+    response_model=Envelope[VectorSelectionResponse],
+)
+def select_vector_partitions(
+    project_id: UUID,
+    payload: VectorPartitionSelectionRequest,
+    db: Session = Depends(get_db),
+):
+    datasets = db.query(Dataset).filter(Dataset.id.in_(payload.dataset_ids)).all()
+    by_id = {dataset.id: dataset for dataset in datasets}
+    ordered = [by_id.get(dataset_id) for dataset_id in payload.dataset_ids]
+    if any(dataset is None or dataset.project_id != project_id for dataset in ordered):
+        raise AppError(code="DATASET_NOT_FOUND", message="One or more selection partitions were not found", status_code=404)
+    typed_datasets = [dataset for dataset in ordered if dataset is not None]
+    if any(dataset.dataset_type not in {"vector", "geojson"} or dataset.status != "ready" for dataset in typed_datasets):
+        raise AppError(
+            code="INVALID_VECTOR_PARTITIONS",
+            message="Every selection partition must be a ready vector dataset",
+            status_code=409,
+        )
+    source_names = {dataset.source_name for dataset in typed_datasets}
+    product_keys = {_product_identity(dataset) for dataset in typed_datasets}
+    if len(source_names) != 1 or len(product_keys) != 1:
+        raise AppError(
+            code="VECTOR_PARTITION_SOURCE_MISMATCH",
+            message="Selection partitions must belong to one governed source product",
+            details={"source_names": sorted(str(value) for value in source_names), "product_keys": sorted(product_keys)},
+            status_code=409,
+        )
+
+    selection_geometry = None
+    selection_area_id = None
+    if payload.area_id is not None:
+        selection_area = db.get(Area, payload.area_id)
+        if selection_area is None or selection_area.project_id != project_id:
+            raise AppError(code="AREA_NOT_FOUND", message="Area not found", status_code=404)
+        selection_geometry, _covers_full_area = VectorFeatureService.constrain_bbox_to_area(
+            payload.bbox.model_dump(),
+            selection_area.geometry,
+        )
+        selection_area_id = selection_area.id
+
+    representative = typed_datasets[0]
+    dataset_ids = [dataset.id for dataset in typed_datasets]
+    result = VectorFeatureService.select_features_by_bbox(
+        db,
+        dataset_id=representative.id,
+        dataset_ids=dataset_ids,
+        bbox=payload.bbox.model_dump(),
+        limit=payload.limit,
+        dataset=representative,
+        selection_geometry=selection_geometry,
+        selection_area_id=selection_area_id,
+        deduplicate_source_features=True,
+    )
+    result.update(
+        partition_count=len(dataset_ids),
+        source_name=representative.source_name,
+        dataset_ids=dataset_ids,
+    )
+    return envelope(VectorSelectionResponse(**result).model_dump(exclude_none=True))