Initial public release

backend/tests/test_segmentation_result_pagination.py

@@ -0,0 +1,151 @@
+"""Regression coverage for bounded, stable segmentation result listings."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime
+from types import SimpleNamespace
+from uuid import UUID
+
+import pytest
+from fastapi import FastAPI
+from fastapi.testclient import TestClient
+
+from app.api.routes import segmentation as segmentation_routes
+from app.db.session import get_db
+from app.schemas.segmentation import SegmentationListResponse
+from app.services.segmentation_service import SegmentationService
+
+
+RUN_ID = UUID("00000000-0000-0000-0000-000000000101")
+DATASET_ID = UUID("00000000-0000-0000-0000-000000000102")
+PROJECT_ID = UUID("00000000-0000-0000-0000-000000000103")
+
+
+def _segmentation(index: int) -> SimpleNamespace:
+    return SimpleNamespace(
+        id=UUID(int=index + 1),
+        project_id=PROJECT_ID,
+        dataset_id=DATASET_ID,
+        analysis_run_id=RUN_ID,
+        job_id=None,
+        model_name="segmentation-test-model",
+        model_version="1",
+        class_name="building",
+        confidence=0.99 - index / 100,
+        bbox_json=None,
+        area_m2=float(index + 1),
+        mask_path=None,
+        source_tile_path=None,
+        tile_index=index,
+        properties_json={},
+        provenance_json={},
+        created_at=datetime(2026, 8, 23, tzinfo=UTC),
+    )
+
+
+class _Session:
+    def get(self, _model, identifier):
+        if identifier == RUN_ID:
+            return SimpleNamespace(analysis_type="segmentation")
+        return None
+
+
+def test_service_returns_one_stable_page_with_complete_metadata(monkeypatch) -> None:
+    rows = [_segmentation(index) for index in range(5)]
+    monkeypatch.setattr(
+        SegmentationService,
+        "_query_segmentation_rows",
+        staticmethod(lambda _db, **_filters: rows),
+    )
+
+    result = SegmentationService.list_segmentations(
+        _Session(),
+        analysis_run_id=RUN_ID,
+        dataset_id=DATASET_ID,
+        limit=2,
+        offset=1,
+    )
+
+    assert [item.id for item in result.items] == [rows[1].id, rows[2].id]
+    assert result.total == 5
+    assert result.limit == 2
+    assert result.offset == 1
+    assert result.truncated is True
+
+
+def test_service_pages_cover_the_stably_ordered_population_once(monkeypatch) -> None:
+    rows = [_segmentation(index) for index in range(5)]
+    monkeypatch.setattr(
+        SegmentationService,
+        "_query_segmentation_rows",
+        staticmethod(lambda _db, **_filters: rows),
+    )
+
+    seen = []
+    for offset in (0, 2, 4):
+        result = SegmentationService.list_segmentations(
+            _Session(),
+            dataset_id=DATASET_ID,
+            limit=2,
+            offset=offset,
+        )
+        seen.extend(item.id for item in result.items)
+        assert result.total == len(rows)
+        assert result.offset == offset
+
+    assert seen == [row.id for row in rows]
+
+
+@pytest.mark.parametrize(
+    ("path", "expected_run_id", "expected_dataset_id"),
+    [
+        (f"/api/v1/segmentation/runs/{RUN_ID}/segmentations", RUN_ID, None),
+        (f"/api/v1/segmentation/datasets/{DATASET_ID}/segmentations", None, DATASET_ID),
+    ],
+)
+def test_both_listing_routes_forward_the_page_window_and_return_it(
+    monkeypatch,
+    path: str,
+    expected_run_id: UUID | None,
+    expected_dataset_id: UUID | None,
+) -> None:
+    calls: list[dict] = []
+
+    def _list(_db, analysis_run_id=None, **parameters):
+        calls.append({"analysis_run_id": analysis_run_id, **parameters})
+        return SegmentationListResponse(
+            items=[],
+            total=9,
+            limit=2,
+            offset=4,
+            truncated=True,
+        )
+
+    monkeypatch.setattr(SegmentationService, "list_segmentations", staticmethod(_list))
+    app = FastAPI()
+    app.include_router(segmentation_routes.router, prefix="/api/v1")
+    app.dependency_overrides[get_db] = lambda: object()
+
+    response = TestClient(app).get(
+        path,
+        params={"limit": 2, "offset": 4, "class_name": "building", "min_confidence": 0.5},
+    )
+
+    assert response.status_code == 200
+    assert response.json()["data"] == {
+        "items": [],
+        "total": 9,
+        "limit": 2,
+        "offset": 4,
+        "truncated": True,
+    }
+    assert calls == [
+        {
+            "analysis_run_id": expected_run_id,
+            "limit": 2,
+            "offset": 4,
+            "dataset_id": expected_dataset_id,
+            "class_name": "building",
+            "min_confidence": 0.5,
+        }
+    ]