harden delivery pipeline and production runtime

tests/ml/test_feature_store.py

@@ -1,7 +1,5 @@
 from __future__ import annotations
 
-import pytest
-
 from app.ml.feature_store import FeatureStore, FeatureVector
 
 
@@ -31,12 +29,18 @@ def test_add_batch_appends_all_vectors() -> None:
     ]
     store.add_batch(vectors)
     assert len(store.all()) == 3
-    assert store.latest("sensor.kitchen").values["temperature"] == 20.0
+    latest = store.latest("sensor.kitchen")
+    assert latest is not None
+    assert latest.values["temperature"] == 20.0
 
 
 def test_different_sensors_are_stored_independently() -> None:
     store = FeatureStore()
     store.add(_vector("sensor.living_room", 21.0))
     store.add(_vector("sensor.bedroom", 18.5))
-    assert store.latest("sensor.living_room").values["temperature"] == 21.0
-    assert store.latest("sensor.bedroom").values["temperature"] == 18.5
+    living_room = store.latest("sensor.living_room")
+    bedroom = store.latest("sensor.bedroom")
+    assert living_room is not None
+    assert bedroom is not None
+    assert living_room.values["temperature"] == 21.0
+    assert bedroom.values["temperature"] == 18.5

tests/ml/test_model_registry.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import json
+from pathlib import Path
 
 import pytest
 
@@ -8,7 +9,7 @@ from app.ml.registry.model_registry import ModelRegistry
 from app.ml.training import TrainedArtifact
 
 
-def test_registry_loads_persisted_artifacts_after_restart(tmp_path) -> None:
+def test_registry_loads_persisted_artifacts_after_restart(tmp_path: Path) -> None:
     registry = ModelRegistry(tmp_path)
     artifact = TrainedArtifact("model-v1", ("sensor.kitchen", "sensor.bedroom"))
     registry.register(artifact)
@@ -19,7 +20,7 @@ def test_registry_loads_persisted_artifacts_after_restart(tmp_path) -> None:
 
 
 @pytest.mark.parametrize("artifact_id", ["../escape", "nested/model", "..", ""])
-def test_registry_rejects_unsafe_artifact_ids(tmp_path, artifact_id: str) -> None:
+def test_registry_rejects_unsafe_artifact_ids(tmp_path: Path, artifact_id: str) -> None:
     registry = ModelRegistry(tmp_path)
 
     with pytest.raises(ValueError):
@@ -28,7 +29,7 @@ def test_registry_rejects_unsafe_artifact_ids(tmp_path, artifact_id: str) -> Non
     assert list(tmp_path.parent.glob("escape.json")) == []
 
 
-def test_registry_rejects_corrupt_persisted_artifact(tmp_path) -> None:
+def test_registry_rejects_corrupt_persisted_artifact(tmp_path: Path) -> None:
     (tmp_path / "broken.json").write_text(
         json.dumps({"artifact_id": "../broken", "supported_sensors": []}),
         encoding="utf-8",

tests/ml/test_training.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import pytest
 
 from app.ml.feature_store import FeatureStore, FeatureVector
-from app.ml.training import TrainingPipeline, TrainedArtifact
+from app.ml.training import TrainingPipeline
 
 
 def _vector(sensor_id: str, temperature: float, label: str | None = None) -> FeatureVector:
@@ -45,4 +45,4 @@ def test_export_returns_registered_artifact() -> None:
 def test_export_missing_artifact_raises_key_error() -> None:
     pipeline = store_with_data()
     with pytest.raises(KeyError):
-        pipeline.export("artifact_v1")
+        pipeline.export("artifact_v1")