feat(ml,backend): implemente le service de scoring et GET /predictions (#37)
This commit is contained in:
Dorian
@@ -37,6 +37,7 @@ ROUTES_A_ROLE = {
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("GET", "/api/v1/stats/summary"),
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("GET", "/api/v1/readings"),
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("GET", "/api/v1/sensors/status"),
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("GET", "/api/v1/predictions"),
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}
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@@ -0,0 +1,82 @@
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from collections.abc import Callable, Iterator
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from datetime import UTC, datetime
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from uuid import uuid4
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import pytest
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from fastapi import FastAPI
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from httpx import AsyncClient
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from app.api.deps import get_current_principal, get_prediction_service
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from app.core.principal import Principal
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from app.core.roles import AccountKind, Role
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from app.services.prediction import PredictionSummary, SitePrediction, SitePredictionSummary
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TARGET_AT = datetime(2026, 9, 16, 13, 0, tzinfo=UTC)
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CREATED_AT = datetime(2026, 9, 16, 12, 0, tzinfo=UTC)
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def principal(role: Role = Role.LECTEUR) -> Principal:
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return Principal(
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id=uuid4(),
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email=f"{role.value}@enervision.fr",
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role=role,
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kind=AccountKind.HUMAIN,
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must_change_password=False,
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)
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class FauxService:
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def __init__(self) -> None:
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self.resume = PredictionSummary(
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timestamp=datetime.now(UTC),
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sites=[
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SitePredictionSummary(
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site_id="SITE001",
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site_name="Bureau Paris La Défense",
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prediction=SitePrediction(
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target_at=TARGET_AT,
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target_metric="consumption_kwh",
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period_minutes=60,
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predicted_value=812.5,
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status="available",
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failure_reason=None,
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model_reference="lightgbm-abc123",
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created_at=CREATED_AT,
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),
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),
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SitePredictionSummary(site_id="SITE002", site_name="Usine Lyon", prediction=None),
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],
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)
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async def summary(self) -> PredictionSummary:
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return self.resume
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@pytest.fixture
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def servi(app: FastAPI) -> Iterator[Callable[[], FauxService]]:
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def installe() -> FauxService:
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service = FauxService()
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app.dependency_overrides[get_prediction_service] = lambda: service
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app.dependency_overrides[get_current_principal] = lambda: principal()
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return service
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yield installe
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app.dependency_overrides.pop(get_prediction_service, None)
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app.dependency_overrides.pop(get_current_principal, None)
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async def test_get_predictions_returns_the_service_result(
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servi: Callable[[], FauxService], client: AsyncClient
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) -> None:
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servi()
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response = await client.get("/api/v1/predictions")
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assert response.status_code == 200
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corps = response.json()
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premier, second = corps["sites"]
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assert premier["site_id"] == "SITE001"
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assert premier["prediction"]["predicted_value"] == 812.5
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assert premier["prediction"]["status"] == "available"
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assert second["site_id"] == "SITE002"
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assert second["prediction"] is None
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@@ -0,0 +1,92 @@
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from datetime import UTC, datetime
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import pytest
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models.energy import Prediction
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from app.repositories.prediction import PredictionRepository
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from tests.repositories.test_site import creer as creer_site
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from tests.repositories.test_site import identifiant as identifiant_site
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pytestmark = pytest.mark.integration
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async def creer_prediction(
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session: AsyncSession, *, site_id: str, **overrides: object
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) -> Prediction:
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prediction = Prediction(
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site_id=site_id,
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target_at=overrides.get("target_at", datetime(2026, 9, 16, tzinfo=UTC)),
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target_metric=overrides.get("target_metric", "consumption_kwh"),
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period_minutes=overrides.get("period_minutes", 60),
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predicted_value=overrides.get("predicted_value", 42.0),
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model_reference=overrides.get("model_reference", "lightgbm-test"),
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status=overrides.get("status", "available"),
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failure_reason=overrides.get("failure_reason"),
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)
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session.add(prediction)
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await session.flush()
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return prediction
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async def test_latest_by_site_keeps_only_the_most_recent_target(session: AsyncSession) -> None:
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site = await creer_site(session)
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depot = PredictionRepository(session)
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ancienne = await creer_prediction(
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session, site_id=site.site_id, target_at=datetime(2026, 9, 1, tzinfo=UTC)
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)
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recente = await creer_prediction(
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session, site_id=site.site_id, target_at=datetime(2026, 9, 15, tzinfo=UTC)
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)
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resultats = await depot.latest_by_site()
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identifiants = [
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p.prediction_id
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for p in resultats
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if p.prediction_id in (ancienne.prediction_id, recente.prediction_id)
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]
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await session.rollback()
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assert identifiants == [recente.prediction_id]
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async def test_latest_by_site_returns_one_row_per_site(session: AsyncSession) -> None:
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premier = await creer_site(session)
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second = await creer_site(session)
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depot = PredictionRepository(session)
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voulue_premier = await creer_prediction(session, site_id=premier.site_id)
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voulue_second = await creer_prediction(session, site_id=second.site_id)
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resultats = await depot.latest_by_site()
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identifiants = {p.site_id for p in resultats if p.site_id in (premier.site_id, second.site_id)}
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await session.rollback()
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assert identifiants == {voulue_premier.site_id, voulue_second.site_id}
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async def test_latest_by_site_keeps_an_insufficient_data_prediction(session: AsyncSession) -> None:
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site = await creer_site(session)
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depot = PredictionRepository(session)
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voulue = await creer_prediction(
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session,
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site_id=site.site_id,
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status="insufficient_data",
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predicted_value=None,
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failure_reason="pas assez d'historique",
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)
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resultats = await depot.latest_by_site()
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identifiants = [p.prediction_id for p in resultats if p.site_id == site.site_id]
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await session.rollback()
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assert identifiants == [voulue.prediction_id]
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async def test_latest_by_site_returns_an_empty_list_when_there_is_nothing(
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session: AsyncSession,
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) -> None:
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depot = PredictionRepository(session)
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resultats = [p for p in await depot.latest_by_site() if p.site_id == identifiant_site()]
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assert resultats == []
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@@ -0,0 +1,121 @@
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from dataclasses import dataclass
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from datetime import UTC, datetime
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from app.services.prediction import PredictionService
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TARGET_AT = datetime(2026, 9, 16, 13, 0, tzinfo=UTC)
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CREATED_AT = datetime(2026, 9, 16, 12, 0, tzinfo=UTC)
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@dataclass
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class FauxSite:
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site_id: str
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site_name: str
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@dataclass
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class FauxPrediction:
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site_id: str
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target_at: datetime
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target_metric: str
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period_minutes: int | None
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predicted_value: float | None
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status: str
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failure_reason: str | None
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model_reference: str
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created_at: datetime
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class FauxDepotSites:
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def __init__(self, sites: list[FauxSite]) -> None:
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self._sites = sites
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async def list_all(self) -> list[FauxSite]:
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return self._sites
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class FauxDepotPredictions:
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def __init__(self, predictions: list[FauxPrediction]) -> None:
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self._predictions = predictions
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async def latest_by_site(self) -> list[FauxPrediction]:
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return self._predictions
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def prediction_disponible(site_id: str = "A") -> FauxPrediction:
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return FauxPrediction(
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site_id=site_id,
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target_at=TARGET_AT,
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target_metric="consumption_kwh",
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period_minutes=60,
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predicted_value=812.5,
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status="available",
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failure_reason=None,
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model_reference="lightgbm-abc123",
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created_at=CREATED_AT,
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)
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async def test_summary_attaches_the_latest_prediction_to_its_site() -> None:
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service = PredictionService(
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sites=FauxDepotSites([FauxSite("A", "Site A")]), # type: ignore[arg-type]
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predictions=FauxDepotPredictions([prediction_disponible("A")]), # type: ignore[arg-type]
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)
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resume = await service.summary()
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site = resume.sites[0]
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assert site.site_id == "A"
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assert site.prediction is not None
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assert site.prediction.predicted_value == 812.5
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assert site.prediction.status == "available"
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async def test_summary_leaves_prediction_none_for_a_site_never_scored() -> None:
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service = PredictionService(
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sites=FauxDepotSites([FauxSite("A", "Site A")]), # type: ignore[arg-type]
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predictions=FauxDepotPredictions([]), # type: ignore[arg-type]
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)
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resume = await service.summary()
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assert resume.sites[0].prediction is None
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async def test_summary_carries_an_insufficient_data_prediction_without_a_value() -> None:
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insuffisante = FauxPrediction(
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site_id="A",
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target_at=TARGET_AT,
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target_metric="consumption_kwh",
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period_minutes=60,
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predicted_value=None,
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status="insufficient_data",
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failure_reason="pas assez d'historique",
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model_reference="lightgbm-abc123",
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created_at=CREATED_AT,
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)
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service = PredictionService(
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sites=FauxDepotSites([FauxSite("A", "Site A")]), # type: ignore[arg-type]
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predictions=FauxDepotPredictions([insuffisante]), # type: ignore[arg-type]
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)
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resume = await service.summary()
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site = resume.sites[0]
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assert site.prediction is not None
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assert site.prediction.status == "insufficient_data"
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assert site.prediction.predicted_value is None
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assert site.prediction.failure_reason == "pas assez d'historique"
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async def test_summary_covers_every_site_even_with_a_single_prediction_in_the_repository() -> None:
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service = PredictionService(
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sites=FauxDepotSites([FauxSite("A", "Site A"), FauxSite("B", "Site B")]), # type: ignore[arg-type]
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predictions=FauxDepotPredictions([prediction_disponible("A")]), # type: ignore[arg-type]
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)
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resume = await service.summary()
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par_site = {site.site_id: site for site in resume.sites}
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assert par_site["A"].prediction is not None
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assert par_site["B"].prediction is None
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