Merge remote-tracking branch 'origin/dev' into pr-107-review

2026-09-18 12:46:03 +02:00
137 changed files with 724 additions and 15018 deletions
@@ -17,39 +17,3 @@ APP_LOG_LEVEL=INFO
 APP_SECRET_KEY=change_me
 APP_CORS_ORIGINS=http://localhost:4200
 BACKEND_PORT=8000
 FRONTEND_PORT=3000
 # Mailpit capture les courriels du backend, rien ne sort vers l'extérieur.
 MAILPIT_SMTP_PORT=1025
 MAILPIT_UI_PORT=8025
 # API Mock EnerVision
 APP_MOCK_API_BASE_URL=https://api-mock.charlieandre.fr
 APP_MOCK_API_USERNAME=change_me
 APP_MOCK_API_PASSWORD=change_me
 APP_MOCK_API_TIMEOUT_SECONDS=10
 # Airflow (webserver + scheduler, LocalExecutor). Base de métadonnées dédiée `airflow` dans le
 # même conteneur `db` (cf. db/init/120-airflow-database.sql), pas un conteneur de plus.
 AIRFLOW_PORT=8080
 # Chiffre les connexions/variables stockées par Airflow. Générer la vôtre :
 # python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
 AIRFLOW_FERNET_KEY=change_me
 # Clé Flask du webserver Airflow (signature de session), distincte de la précédente. Générer la
 # vôtre : python -c "import secrets; print(secrets.token_urlsafe(48))"
 AIRFLOW_WEBSERVER_SECRET_KEY=change_me
 AIRFLOW_ADMIN_USERNAME=admin
 # Compte Airflow créé au premier démarrage (service `airflow-init`), sans rapport avec les
 # comptes `app_user` d'EnerVision.
 AIRFLOW_ADMIN_PASSWORD=change_me
 AIRFLOW_ADMIN_EMAIL=admin@enervision.fr
 # `APP_SECRET_KEY` du backend, que le DAG `alertes` lance en sous-processus. Distincte de
 # celle de l'API : la détection ne signe aucun jeton, et Airflow exécute du code depuis son
 # interface (cf. ADR 0008). Générer la vôtre :
 # python -c "import secrets; print(secrets.token_urlsafe(48))"
 AIRFLOW_APP_SECRET_KEY=change_me
 # Stack complète derrière le reverse proxy (docker-compose.prod.yml).
 # PUBLIC_HOST alimente l'origine CORS, le lien de réinitialisation et le certificat.
 PUBLIC_HOST=enervision.local
 ACME_EMAIL=
@@ -38,9 +38,3 @@ updates:
    directory: "/apps/frontend"
    schedule:
      interval: "weekly"
  # Images du reverse proxy et du compagnon ACME, épinglées dans les fichiers Compose
  - package-ecosystem: "docker-compose"
    directory: "/"
    schedule:
      interval: "weekly"
@@ -1,101 +0,0 @@
 name: Airflow
 # Piège : la version de Python vient de etl/airflow/.python-version. C'est 3.12 et non 3.14
 # (contrairement à backend.yml et ml.yml) : apache-airflow 2.10 ne supporte pas 3.14. Le 3.14 de
 # ml/ ne vit que dans l'image Docker, dans son propre environnement (cf. etl/airflow/Dockerfile).
 #
 # Piège : l'image COPY les fichiers de dépendances et le code de ml/ et de apps/backend/. Une
 # modification de l'un ou de l'autre peut donc casser sa construction, d'où ces chemins dans
 # les déclencheurs, alors même que ce workflow ne teste ni le modèle ni l'API.
 on:
  push:
    paths:
      - "etl/airflow/**"
      - "ml/pyproject.toml"
      - "ml/uv.lock"
      - "ml/enervision_ml/**"
      - "apps/backend/pyproject.toml"
      - "apps/backend/uv.lock"
      - "apps/backend/app/**"
      - ".github/workflows/airflow.yml"
  pull_request:
    paths:
      - "etl/airflow/**"
      - "ml/pyproject.toml"
      - "ml/uv.lock"
      - "ml/enervision_ml/**"
      - "apps/backend/pyproject.toml"
      - "apps/backend/uv.lock"
      - "apps/backend/app/**"
      - ".github/workflows/airflow.yml"
 permissions:
  contents: read
 concurrency:
  group: airflow-${{ github.ref }}
  cancel-in-progress: true
 jobs:
  verification:
    name: Lint et intégrité des DAGs
    runs-on: ubuntu-latest
    defaults:
      run:
        working-directory: etl/airflow
    steps:
      - name: Récupère le dépôt
        uses: actions/checkout@v4
      - name: Installe uv
        uses: astral-sh/setup-uv@v5
        with:
          enable-cache: true
          cache-dependency-glob: etl/airflow/uv.lock
      - name: Installe l'interpréteur déclaré par .python-version
        run: uv python install
      - name: Synchronise les dépendances sans dévier du verrou
        run: uv sync --all-groups --frozen
      - name: Vérifie le formatage
        run: uv run ruff format --check .
      - name: Analyse statique
        run: uv run ruff check --output-format=github .
      # Aucun test ne lance de tâche ni de scheduler : DagBag charge les fichiers de dags/ et
      # vérifie import, planification, plafonds d'exécution et commande de chaque tâche.
      - name: Tests d'intégrité des DAGs
        run: uv run pytest
  image:
    name: Construction de l'image
    runs-on: ubuntu-latest
    steps:
      - name: Récupère le dépôt
        uses: actions/checkout@v4
      - name: Construit l'image (contexte à la racine, elle COPY ml/ et apps/backend/)
        run: docker build -f etl/airflow/Dockerfile -t enervision-airflow:ci .
      # Vérifie ce qui ne casse qu'à l'exécution, pas à la construction : libgomp1 absent
      # (`OSError: libgomp.so.1` au premier import) ou environnement ml/ non figé.
      - name: Vérifie que le pipeline ML s'importe sans réseau
        run: >
          docker run --rm --network none enervision-airflow:ci
          bash -c "cd /opt/ml && env -u VIRTUAL_ENV uv run --no-sync python -m enervision_ml.train --help"
      # `--help` sort par argparse avant `get_settings()` : ni base ni secret requis, et
      # l'import du module prouve que l'environnement /opt/backend est complet. Les deux
      # commandes du DAG `alertes` sont couvertes, `app.cli` tirant tout FastAPI derrière lui.
      - name: Vérifie que les deux commandes du DAG alertes s'importent sans réseau
        run: >
          docker run --rm --network none enervision-airflow:ci
          bash -c "cd /opt/backend
          && env -u VIRTUAL_ENV uv run --no-sync python -m app.detection.internal_alerts --help
          && env -u VIRTUAL_ENV uv run --no-sync python -m app.cli generate-recommendations --help"
@@ -57,66 +57,6 @@ jobs:
      - name: Tests et couverture
        run: uv run pytest --cov-fail-under=85
  # Piège : l'image est celle de docker-compose.yml, pas une image `postgres` nue. La première
  # migration (`5353c0e4f094`) échoue volontairement si l'extension TimescaleDB manque, et un
  # écart d'image entre la CI et le poste rendrait ce job vert sur une base qui n'est pas la nôtre.
  integration:
    name: Tests exigeant une base
    runs-on: ubuntu-latest
    defaults:
      run:
        working-directory: apps/backend
    services:
      db:
        image: timescale/timescaledb-ha:pg17
        env:
          POSTGRES_USER: enervision
          POSTGRES_PASSWORD: change_me
          POSTGRES_DB: enervision_test
        ports:
          - "5433:5432"
        options: >-
          --health-cmd "pg_isready -U enervision -d enervision_test"
          --health-interval 10s
          --health-timeout 5s
          --health-retries 12
          --health-start-period 40s
    env:
      DATABASE_URL: postgresql+asyncpg://enervision:change_me@localhost:5433/enervision_test
      APP_SECRET_KEY: secret-de-test-assez-long-pour-le-validateur
      PGPASSWORD: change_me
    steps:
      - name: Récupère le dépôt
        uses: actions/checkout@v4
      - name: Installe uv
        uses: astral-sh/setup-uv@v5
        with:
          enable-cache: true
          cache-dependency-glob: apps/backend/uv.lock
      - name: Installe l'interpréteur déclaré par .python-version
        run: uv python install
      - name: Synchronise les dépendances sans dévier du verrou
        run: uv sync --all-groups --frozen
      # Sur le poste, c'est db/init/110-test-database.sql qui pose l'extension. Ce fichier n'est
      # pas monté ici, et sans lui `alembic upgrade head` s'arrête sur la garde de la révision 1.
      - name: Active TimescaleDB sur la base de test
        run: psql -h localhost -p 5433 -U enervision -d enervision_test -c "CREATE EXTENSION IF NOT EXISTS timescaledb"
      - name: Applique les migrations
        run: uv run alembic upgrade head
      # `-m` en ligne de commande écrase celui d'`addopts`. La couverture est désactivée : ce job
      # ne joue qu'une partie de la suite, son taux n'aurait aucun sens face au seuil de 85 %.
      - name: Tests d'intégration
        run: uv run pytest -m integration --no-cov
  security-audit:
    name: Audit des dépendances
    runs-on: ubuntu-latest
@@ -140,29 +80,3 @@ jobs:
        # Piège : sans `shell: bash`, un échec de `uv export` serait masqué par le pipe.
        shell: bash
        run: uv export --frozen --no-dev --no-emit-project --no-hashes | uvx pip-audit --requirement /dev/stdin --no-deps
  sast:
    name: Analyse statique de sécurité
    runs-on: ubuntu-latest
    defaults:
      run:
        working-directory: apps/backend
    steps:
      - name: Récupère le dépôt
        uses: actions/checkout@v4
      # Pourquoi : pas de cache ici. uvx n'installe pas le projet, le verrou n'alimente donc
      # aucune clé de cache ; la seule roue téléchargée est celle de Bandit.
      - name: Installe uv
        uses: astral-sh/setup-uv@v5
      # Pourquoi : le périmètre est `app`, le code livré. Les tests emploient légitimement des
      # secrets factices et des `assert` que Bandit signalerait sans qu'aucun n'atteigne la prod.
      - name: Analyse le code livré (bloquant à partir de MEDIUM)
        run: uvx bandit==1.9.4 --recursive app --severity-level medium --confidence-level medium
      # Piège : sans cette seconde passe, un constat LOW disparaîtrait du journal sans trace.
      - name: Rapport complet, tous niveaux
        continue-on-error: true
        run: uvx bandit==1.9.4 --recursive app
@@ -51,14 +51,30 @@ jobs:
          node-version: 24
          cache: npm
          cache-dependency-path: apps/frontend/package-lock.json
-      - name : Installation des dépendances (Front)
+      - run: npm ci
        run: npm ci 
        working-directory: apps/frontend
-      - name : Lancement des tests et génénration du rapport de couverture (Front)
+      - run: npm test -- --watch=false --coverage
        run: npm test --watch=false --code-coverage --coverageReporters=lcov
        working-directory: apps/frontend
      - name: Upload coverage
        uses: actions/upload-artifact@v4
        with:
          name: frontend-coverage
          path: apps/frontend/coverage/frontend/lcov.info
  sonarqube:
    needs: [build, test]
    name: SonarQube
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
        with:
          fetch-depth: 0
      - name: Download coverage
        uses: actions/download-artifact@v4
        with:
          name: frontend-coverage
          path: apps/frontend/coverage/frontend
      - name: SonarQube Scan
        uses: SonarSource/sonarqube-scan-action@v8
        env:
          SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
@@ -57,26 +57,3 @@ jobs:
      # synthetiques ou un magasin SQLite local jetable (cf. ml/tests/test_train.py).
      - name: Tests
        run: uv run pytest
  sast:
    name: Analyse statique de sécurité
    runs-on: ubuntu-latest
    defaults:
      run:
        working-directory: ml
    steps:
      - name: Récupère le dépôt
        uses: actions/checkout@v4
      # Pourquoi : pas de cache ici. uvx n'installe pas le projet, le verrou n'alimente donc
      # aucune clé de cache ; la seule roue téléchargée est celle de Bandit.
      - name: Installe uv
        uses: astral-sh/setup-uv@v5
      - name: Analyse le code livré (bloquant à partir de MEDIUM)
        run: uvx bandit==1.9.4 --recursive enervision_ml --severity-level medium --confidence-level medium
      - name: Rapport complet, tous niveaux
        continue-on-error: true
        run: uvx bandit==1.9.4 --recursive enervision_ml
@@ -1,169 +0,0 @@
 name: SonarQube
 on:
  push:
    paths:
      - "apps/frontend/**"
      - "apps/backend/**"
      - "ml/**"
      - "etl/airflow/**"
      - ".github/workflows/sonarqube.yml"
  pull_request:
    paths:
      - "apps/frontend/**"
      - "apps/backend/**"
      - "ml/**"
      - "etl/airflow/**"
      - ".github/workflows/sonarqube.yml"
 # Build l'ensemble du projet, puis lance les tests
 # Génère les rapports de couverture, puis lance l'analyse SonarQube
 jobs:
  build-front:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
      - uses: actions/setup-node@v6
        with:
          node-version: 24
          cache: npm
          cache-dependency-path: apps/frontend/package-lock.json
      - run: npm ci 
        working-directory: apps/frontend
      - run: npm run build
        working-directory: apps/frontend
  test-front:  
    needs: build-front
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
      - uses: actions/setup-node@v6
        with:
          node-version: 24
          cache: npm
          cache-dependency-path: apps/frontend/package-lock.json
      - name : Installation des dépendances (Front)
        run: npm ci 
        working-directory: apps/frontend
      - name : Lancement des tests et génénration du rapport de couverture (Front)
        run: npm test --watch=false --code-coverage --coverageReporters=lcov
        working-directory: apps/frontend
      - name: Upload coverage
        uses: actions/upload-artifact@v4
        with:
          name: frontend-coverage
          path: apps/frontend/coverage/frontend/lcov.info
  build-back:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
      - name: Installe uv
        uses: astral-sh/setup-uv@v5
        with:
          enable-cache: true
          cache-dependency-glob: apps/backend/uv.lock
      - name: Installe l'interpréteur déclaré par .python-version
        run: uv python install
        working-directory: apps/backend
      - name: Synchronise les dépendances sans dévier du verrou
        run: uv sync --all-groups --frozen
        working-directory: apps/backend
      - name: Vérifie le formatage
        run: uv run ruff format --check .
        working-directory: apps/backend
      - name: Analyse statique
        run: uv run ruff check --output-format=github .
        working-directory: apps/backend
      - name: Typage
        run: uv run mypy app
        working-directory: apps/backend
  test-back:
    needs: build-back
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
      - name: Installe uv
        uses: astral-sh/setup-uv@v5
        with:
          enable-cache: true
          cache-dependency-glob: apps/backend/uv.lock
      - name : Lancement des tests et génénration du rapport de couverture (Back)
        run: uv run pytest --cov-fail-under=85 --cov-report=xml
        working-directory: apps/backend
      - name: Upload coverage
        uses: actions/upload-artifact@v4
        with:
          name: backend-coverage
          path: apps/backend/coverage.xml
  test-ml:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
      - name: Installe uv
        uses: astral-sh/setup-uv@v5
        with:
          enable-cache: true
          cache-dependency-glob: ml/uv.lock
      - name: Installe l'interpréteur déclaré par .python-version
        run: uv python install
        working-directory: ml
      - name: Synchronise les dépendances sans dévier du verrou
        run: uv sync --all-groups --frozen
        working-directory: ml
      - name: Lancement des tests et génération du rapport de couverture (ML)
        run: uv run pytest --cov-report=xml
        working-directory: ml
      - name: Upload coverage
        uses: actions/upload-artifact@v4
        with:
          name: ml-coverage
          path: ml/coverage.xml
  sonarqube:
    needs: [build-front, build-back, test-front, test-back, test-ml]
    name: SonarQube
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v6
        with:
          fetch-depth: 0
      - name: Téléchargement du rapport de couverture (Front)
        uses: actions/download-artifact@v4
        with:
          name: frontend-coverage
          path: apps/frontend/coverage/frontend
      - name: Téléchargement du rapport de couverture (Back)
        uses: actions/download-artifact@v4
        with:
          name: backend-coverage
          path: apps/backend
      - name: Téléchargement du rapport de couverture (ML)
        uses: actions/download-artifact@v4
        with:
          name: ml-coverage
          path: ml
      - name: SonarQube Scan
        uses: SonarSource/sonarqube-scan-action@v8
        env:
          SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
@@ -66,12 +66,6 @@ ml/mlruns/
 ml/mlartifacts/
 ml/mlflow.db
 # Airflow : base sqlite locale generee par les tests d'integrite des DAGs (etl/airflow/tests)
 etl/airflow/tests/.airflow_home/
 # TLS : certificats du reverse proxy, générés par script ou par certbot
 infra/proxy/tls/*.pem
 # IDE et OS
 .idea/
 .vscode/
@@ -1,31 +1,17 @@
 BACKEND := apps/backend
 FRONTEND := apps/frontend
 ML := ml
 AIRFLOW := etl/airflow
 COMPOSE_PROD := docker compose -f docker-compose.yml -f docker-compose.prod.yml
 # Piège : sans `export`, une valeur passée en ligne de commande n'atteindrait pas docker compose.
 # PUBLIC_HOST retombe sur le `.env`, que make ne lit pas, puis sur la valeur de `.env.example`.
 PUBLIC_HOST ?= $(shell sed -n 's/^PUBLIC_HOST=//p' .env 2>/dev/null | tail -1)
 PUBLIC_HOST := $(or $(strip $(PUBLIC_HOST)),enervision.local)
 export PUBLIC_HOST
 ifdef ACME_EMAIL
 export ACME_EMAIL
 endif
 .DEFAULT_GOAL := help
-.PHONY: help install install-backend install-frontend install-ml install-airflow \
+.PHONY: help install install-backend install-frontend install-ml dev dev-backend dev-frontend \
        dev dev-backend dev-frontend \
        lint format typecheck test test-cov test-integration check \
        openapi docker-build db-up db-down db-reset db-logs db-psql migrate bootstrap-admin \
-        ml-lint ml-typecheck ml-test ml-check ml-train ml-score detect-alerts recommendations \
+        ml-lint ml-typecheck ml-test ml-check ml-train
        airflow-lint airflow-test airflow-check airflow-up airflow-down airflow-logs \
        tls-selfsigned tls-acme tls-renew stack-up stack-down stack-logs
 help: ## Liste les cibles disponibles
 	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "  \033[36m%-16s\033[0m %s\n", $$1, $$2}'
-install: install-backend install-frontend install-ml install-airflow ## Installe les dépendances backend, frontend, ML et Airflow
+install: install-backend install-frontend install-ml ## Installe les dépendances backend, frontend et ML
 install-backend: ## Installe les dépendances du backend
 	cd $(BACKEND) && uv sync --all-groups
@@ -36,9 +22,6 @@ install-frontend: ## Installe les dépendances du frontend
 install-ml: ## Installe les dépendances du pipeline ML
 	cd $(ML) && uv sync --all-groups
 install-airflow: ## Installe les dépendances de lint/test des DAGs Airflow
 	cd $(AIRFLOW) && uv sync --all-groups
 dev: ## Lance toute la stack (backend + frontend) en rechargement à chaud
 	@trap 'kill 0' EXIT INT TERM; \
 	$(MAKE) --no-print-directory dev-backend & \
@@ -91,65 +74,9 @@ ml-check: ml-lint ml-typecheck ml-test ## Chaîne de vérification complète du
 ml-train: ## Entraine le modele LightGBM. CSV=chemin optionnel, sinon lit ML_DATABASE_URL
 	cd $(ML) && uv run python -m enervision_ml.train $(if $(CSV),--csv $(CSV),)
 ml-score: ## Score le prochain pas horaire et l'ecrit dans `prediction`. CSV=chemin optionnel
 	cd $(ML) && uv run python -m enervision_ml.score $(if $(CSV),--csv $(CSV),)
 detect-alerts: ## Détecte les alertes internes depuis les lectures en base. SITE= et NOW= optionnels
 	cd $(BACKEND) && uv run python -m app.detection.internal_alerts $(if $(SITE),--site-id $(SITE),) $(if $(NOW),--now $(NOW),)
 recommendations: ## Genere les recommandations depuis les alertes en base. SITE=identifiant optionnel
 	cd $(BACKEND) && uv run python -m app.cli generate-recommendations $(if $(SITE),--site-id $(SITE),)
 airflow-lint: ## Analyse statique des DAGs Airflow
 	cd $(AIRFLOW) && uv run ruff check .
 airflow-test: ## Verifie que les DAGs s'importent sans erreur et ont la structure attendue
 	cd $(AIRFLOW) && uv run pytest
 airflow-check: airflow-lint airflow-test ## Chaîne de vérification complète des DAGs Airflow
 airflow-up: ## Démarre Airflow (webserver + scheduler, LocalExecutor). db-up requis avant.
 	docker compose up -d airflow-init airflow-webserver airflow-scheduler
 	@echo "airflow  -> http://localhost:$${AIRFLOW_PORT:-8080}"
 airflow-down: ## Arrête le webserver et le scheduler Airflow
 	docker compose stop airflow-webserver airflow-scheduler
 airflow-logs: ## Suit les journaux du scheduler Airflow (où tournent les tâches, LocalExecutor)
 	docker compose logs -f airflow-scheduler
 docker-build: ## Construit l'image du backend
 	docker build -t enervision-backend:local $(BACKEND)
 tls-selfsigned: ## Génère le certificat de démonstration. PUBLIC_HOST=..., FORCE=1 pour écraser
 	./scripts/tls-selfsigned.sh $(if $(FORCE),--force,)
 stack-up: ## Démarre la stack complète derrière le reverse proxy (80/443). PUBLIC_HOST=... au besoin
 	@test -f infra/proxy/tls/fullchain.pem \
 		|| { echo "Aucun certificat dans infra/proxy/tls. Lancer d'abord make tls-selfsigned"; exit 1; }
 	@openssl x509 -in infra/proxy/tls/fullchain.pem -noout -checkhost "$(PUBLIC_HOST)" >/dev/null \
 		|| { echo "Le certificat ne couvre pas $(PUBLIC_HOST). Relancer make tls-selfsigned PUBLIC_HOST=$(PUBLIC_HOST) FORCE=1"; exit 1; }
 	$(COMPOSE_PROD) up -d --build
 stack-down: ## Arrête la stack complète en conservant les données
 	$(COMPOSE_PROD) stop
 stack-logs: ## Suit les journaux du reverse proxy
 	$(COMPOSE_PROD) logs -f proxy
 tls-acme: ## Demande un certificat Let's Encrypt. PUBLIC_HOST public et ACME_EMAIL requis
 	@test "$(PUBLIC_HOST)" != enervision.local \
 		|| { echo "PUBLIC_HOST doit être un domaine public résolvable, pas le nom de démonstration"; exit 1; }
 	$(COMPOSE_PROD) --profile acme run --rm certbot certonly --webroot -w /var/www/certbot \
 		-d $(PUBLIC_HOST) \
 		--email $${ACME_EMAIL:?ACME_EMAIL=... requis} \
 		--agree-tos --no-eff-email --deploy-hook /deploy-hook.sh
 	$(COMPOSE_PROD) exec proxy nginx -s reload
 tls-renew: ## Renouvelle les certificats Let's Encrypt et recharge le proxy
 	$(COMPOSE_PROD) --profile acme run --rm certbot renew --deploy-hook /deploy-hook.sh
 	$(COMPOSE_PROD) exec proxy nginx -s reload
 db-up: ## Démarre la base PostgreSQL TimescaleDB
 	docker compose up -d db
@@ -21,9 +21,8 @@ Ce que la documentation apporte à chacun : [docs/architecture/00-vue-ensemble.m
 | Backend    | FastAPI, Python 3.14                | `apps/backend`      | Initialise    |
 | Frontend   | Angular 22, Node 24 LTS             | `apps/frontend`     | Tableau de bord |
 | Base       | PostgreSQL 17 + TimescaleDB         | `db`                | Initialise    |
-| ETL        | Apache Airflow                      | `etl/airflow`       | Trois DAGs    |
+| ETL        | Apache Airflow                      | `etl/airflow`       | A initialiser |
 | Infra      | Terraform (k3s single-node)         | `infra/terraform`   | Initialise    |
 | Reverse proxy | Nginx, TLS                       | `infra/proxy`       | En place      |
 | CI/CD      | GitHub Actions                      | `.github/workflows` | Backend en place |
 | Monitoring | Prometheus, Grafana, Alertmanager   | `monitoring`        | A initialiser |
 | ML         | LightGBM, MLflow                    | `ml`                | Entrainement initialise |
@@ -48,15 +47,13 @@ L'etat detaille de chaque brique et les vues d'architecture sont dans
 │   ├── migrations/     Migrations SQL versionnees
 │   └── seeds/          Jeux de donnees de reference
 ├── etl/airflow/
-│   ├── dags/           DAGs d'orchestration (pipeline ML, alertes)
+│   ├── dags/           DAGs d'ingestion et d'agregation
 │   ├── plugins/        Operateurs et hooks maison
 │   ├── include/        Requetes SQL et ressources des DAGs
 │   └── tests/          Tests d'integrite des DAGs
-├── infra/
+├── infra/terraform/
-│   ├── proxy/          Reverse proxy Nginx : terminaison TLS et routage
+│   ├── modules/        Modules reutilisables
-│   └── terraform/
+│   └── environments/   Racines Terraform, une par environnement
 │       ├── modules/        Modules reutilisables
 │       └── environments/   Racines Terraform, une par environnement
 ├── ml/                 Pipeline d'entrainement LightGBM, suivi MLflow
 ├── monitoring/
 │   ├── prometheus/     Collecte et regles d'alerte
@@ -101,21 +98,6 @@ Verifier que la base repond et que l'extension est chargee :
 curl -s localhost:8000/api/v1/health/ready
 ```
 ## Stack complète derrière le reverse proxy
 Pour servir l'application comme sur la machine cible, en HTTPS et sous une seule origine.
 L'overlay emploie `!override` et `!reset`, donc **Docker Compose 2.24.4 ou plus récent** :
 ```bash
 make tls-selfsigned PUBLIC_HOST=enervision.local   # certificat de démonstration
 make stack-up PUBLIC_HOST=enervision.local         # nginx en 80/443, rien d'autre n'est publié
 ```
 Le navigateur avertit d'un émetteur inconnu : Let's Encrypt reste hors d'atteinte tant qu'aucun
 nom de domaine public ne résout vers la machine. Routage, mode ACME et renouvellement dans
 [`infra/proxy/README.md`](infra/proxy/README.md) ; la décision et ses motifs dans
 [l'ADR 0007](docs/adr/0007-terminaison-tls-et-reverse-proxy-nginx.md).
 ## Conventions
 - Branches : `feat/`, `fix/`, `chore/`, `docs/`, `test/` suivi d'un libelle court.
@@ -18,7 +18,3 @@ APP_SMTP_HOST=localhost
 APP_SMTP_PORT=1025
 APP_SMTP_USE_TLS=false
 APP_SMTP_FROM_ADDRESS=no-reply@enervision.fr
 APP_MOCK_API_BASE_URL=https://api-mock.charlieandre.fr
 APP_MOCK_API_USERNAME=change_me
 APP_MOCK_API_PASSWORD=change_me
 APP_MOCK_API_TIMEOUT_SECONDS=10
@@ -11,14 +11,13 @@ WORKDIR /app
 RUN --mount=type=cache,target=/root/.cache/uv \
    --mount=type=bind,source=uv.lock,target=uv.lock \
    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
-    uv sync --locked --no-install-project --no-dev --no-build
+    uv sync --locked --no-install-project --no-dev
 # Le projet lui-meme n'est pas installe (pas de second `uv sync`) : il tourne depuis /app, le
 # repertoire de travail, et rien ne lit ses metadonnees. L'installer imposerait de le construire
 # (backend hatchling), donc de retirer `--no-build` de l'etape ci-dessus, qui garantit que
 # l'installation des dependances n'execute aucun script de build (regle Sonar docker:S8541).
 COPY . /app
 RUN --mount=type=cache,target=/root/.cache/uv \
    uv sync --locked --no-dev
 FROM python:3.14-slim AS runtime
@@ -113,7 +113,6 @@ Le sens de dependance est unique : `endpoints` vers `services` vers `repositorie
 | `/api/v1/sites/{site_id}` | Décrit un site | `lecteur` |
 | `/api/v1/recommendations` | Liste les recommandations | `lecteur` |
 | `/api/v1/recommendations/{recommendation_id}` | Décrit une recommandation | `lecteur` |
 | `/api/v1/recommendations/generate` | Génère les recommandations depuis les alertes (POST) | `admin` |
 | `/metrics` | Métriques au format Prometheus | jeton si `APP_METRICS_TOKEN` |
 | `/docs`, `/openapi.json` | Documentation, fermée en `staging` et `prod` | public sinon |
@@ -123,11 +123,6 @@ async def test_repository_reads_back_what_it_wrote(session: AsyncSession) -> Non
 defaut, ce qui garde `make check` jouable sans Docker. Tout autre marqueur doit etre
 declare dans `pyproject.toml` : `--strict-markers` refuse les marqueurs inconnus.
 Ces tests ne sont pas pour autant facultatifs : le job `integration` de
 `.github/workflows/backend.yml` monte un service TimescaleDB, applique les migrations et
 les joue a chaque poussee. Un test `integration` casse donc la CI comme un autre. En local,
 `make db-up` puis `make test-integration`.
 ## Couverture
 Les branches sont mesurees, pas seulement les lignes. Le seuil de 85 % ne s'applique
@@ -147,27 +142,14 @@ uv run pytest tests/api/test_health.py           # un seul fichier
 uv run pytest -k readiness                       # par motif de nom
 ```
-## Quatre fichiers à connaître avant de toucher à l'authentification
+## Trois fichiers à connaître avant de toucher à l'authentification
 `tests/api/acces.py` porte la classification des routes du contrat, en quatre ensembles :
 `ROUTES_PUBLIQUES`, `ROUTE_COOKIE`, `ROUTES_SANS_ROLE` et la table `ROLE_MINIMUM`. Ce n'est pas
 un fichier de test, c'est la référence que les trois autres confrontent au comportement observé.
 **Toute route ajoutée doit y être classée** : `test_every_declared_route_is_classified` échoue
 sinon, et échoue aussi sur une entrée qui ne correspond plus à aucune route.
 `tests/api/test_route_protection.py` interroge réellement chaque route sans identifiant et
 échoue si l'une d'elles répond autre chose qu'un 401 ou un 403. Il n'inspecte pas l'arbre de
 dépendances : celui-ci n'est accessible que par l'API privée de FastAPI, et surtout une route
 peut porter la bonne dépendance tout en répondant quand même. **Rendre une route publique impose
-donc de modifier `ROUTES_PUBLIQUES` dans `acces.py`**, ce qui apparaît en clair dans la diff
+donc de modifier la liste `ROUTES_PUBLIQUES` de ce fichier**, ce qui apparaît en clair dans la
-d'une pull request.
+diff d'une pull request.
 `tests/api/test_matrice_acces.py` croise chaque route gardée avec chacun des trois rôles, dans
 les deux sens : un rôle insuffisant reçoit un 403 `Droits insuffisants`, un rôle suffisant ne le
 reçoit jamais. Le second sens est ce qui rend visible une garde posée trop haut, par exemple
 `AdminDep` sur une route de lecture. La même matrice est rejouée sous `integration` avec de vrais
 jetons, donc en traversant le décodage du JWT et la relecture du compte en base, que
 `dependency_overrides` court-circuite.
 `tests/services/test_auth.py` donne au faux hacheur un **compteur d'appels**. C'est ce qui rend
 possibles les deux assertions qui prouvent la conception, et qu'aucune autre forme de test
@@ -27,7 +27,6 @@ from app.repositories.audit_log import AuditLogRepository
 from app.repositories.login_attempt import LoginAttemptRepository
 from app.repositories.password_reset_attempt import PasswordResetAttemptRepository
 from app.repositories.password_reset_token import PasswordResetTokenRepository
 from app.repositories.prediction import PredictionRepository
 from app.repositories.reading import ReadingRepository
 from app.repositories.recommendation import RecommendationRepository
 from app.repositories.refresh_token import RefreshTokenRepository
@@ -35,7 +34,6 @@ from app.repositories.site import SiteRepository
 from app.repositories.user import UserRepository
 from app.services.alert import AlertService
 from app.services.auth import AuthService, LoginPolicy, PasswordResetPolicy
 from app.services.prediction import PredictionService
 from app.services.reading import ReadingService
 from app.services.recommendation import RecommendationService
 from app.services.sensor import SensorService
@@ -180,23 +178,14 @@ SiteServiceDep = Annotated[SiteService, Depends(get_site_service)]
 def get_alert_service(session: SessionDep) -> AlertService:
-    return AlertService(
+    return AlertService(alerts=AlertRepository(session))
        alerts=AlertRepository(session),
        readings=ReadingRepository(session),
        predictions=PredictionRepository(session),
        sites=SiteRepository(session),
    )
 AlertServiceDep = Annotated[AlertService, Depends(get_alert_service)]
 def get_recommendation_service(session: SessionDep) -> RecommendationService:
-    return RecommendationService(
+    return RecommendationService(recommendations=RecommendationRepository(session))
        recommendations=RecommendationRepository(session),
        alerts=AlertRepository(session),
        transaction=session,
    )
 RecommendationServiceDep = Annotated[RecommendationService, Depends(get_recommendation_service)]
@@ -223,15 +212,6 @@ def get_sensor_service(session: SessionDep) -> SensorService:
 SensorServiceDep = Annotated[SensorService, Depends(get_sensor_service)]
 def get_prediction_service(session: SessionDep) -> PredictionService:
    return PredictionService(
        sites=SiteRepository(session), predictions=PredictionRepository(session)
    )
 PredictionServiceDep = Annotated[PredictionService, Depends(get_prediction_service)]
 async def get_current_principal(
    credentials: CredentialsDep,
    session: SessionDep,
@@ -63,7 +63,7 @@ TAGS: Final[list[dict[str, Any]]] = [
        "name": "recommendations",
        "description": (
            "Consultation des recommandations issues des alertes. Accessible à partir du rôle "
-            "`lecteur`. Leur génération par le moteur de règles est réservée au rôle `admin`."
+            "`lecteur`."
        ),
    },
    {
@@ -83,13 +83,6 @@ TAGS: Final[list[dict[str, Any]]] = [
        "name": "sensors",
        "description": "État de santé des capteurs par site. Réservé au rôle `admin`.",
    },
    {
        "name": "predictions",
        "description": (
            "Dernière prévision de consommation par site, calculée hors ligne par le pipeline "
            "de scoring (`ml/`) et simplement lue ici. Accessible à partir du rôle `lecteur`."
        ),
    },
 ]
 cookie_de_rafraichissement = APIKeyCookie(
@@ -1,18 +0,0 @@
 from fastapi import APIRouter
 from app.api.deps import LecteurDep, PredictionServiceDep
 from app.schemas.prediction import PredictionSummaryResponse
 router = APIRouter()
@router.get(
    "",
    response_model=PredictionSummaryResponse,
    summary="Dernière prédiction de consommation par site",
 )
 async def get_predictions(
    _: LecteurDep, service: PredictionServiceDep
 ) -> PredictionSummaryResponse:
    resume = await service.summary()
    return PredictionSummaryResponse.model_validate(resume)
@@ -1,18 +1,13 @@
 from fastapi import APIRouter, HTTPException, status
-from app.api.deps import AdminDep, LecteurDep, RecommendationServiceDep
+from app.api.deps import LecteurDep, RecommendationServiceDep
-from app.api.openapi import REPONSE_VALIDATION, REPONSES_ADMIN, Reponses
+from app.api.openapi import REPONSE_VALIDATION, Reponses
 from app.schemas.errors import ErrorResponse
-from app.schemas.recommendation import (
+from app.schemas.recommendation import RecommendationResponse
    RecommendationGenerationResponse,
    RecommendationResponse,
 )
 from app.services.recommendation import RecommendationNotFoundError
 router = APIRouter()
 REPONSES_GENERATION: Reponses = {**REPONSES_ADMIN, **REPONSE_VALIDATION}
 REPONSES_INTROUVABLE: Reponses = {
    **REPONSE_VALIDATION,
    404: {"model": ErrorResponse, "description": "Aucune recommandation ne porte cet identifiant."},
@@ -43,22 +38,3 @@ async def get_recommendation(
            status_code=status.HTTP_404_NOT_FOUND, detail="Recommandation introuvable"
        ) from erreur
    return RecommendationResponse.model_validate(recommendation)
@router.post(
    "/generate",
    response_model=RecommendationGenerationResponse,
    summary="Génère les recommandations à partir des alertes",
    responses=REPONSES_GENERATION,
 )
 async def generate_recommendations(
    _: AdminDep,
    service: RecommendationServiceDep,
    site_id: str | None = None,
 ) -> RecommendationGenerationResponse:
    rapport = await service.generate(site_id=site_id)
    return RecommendationGenerationResponse(
        alerts_examined=rapport.alertes_examinees,
        recommendations_created=rapport.recommandations_creees,
        already_present=rapport.deja_presentes,
    )
@@ -5,7 +5,6 @@ from app.api.v1.endpoints import (
    alerts,
    auth,
    health,
    predictions,
    readings,
    recommendations,
    sensors,
@@ -35,6 +34,3 @@ api_router.include_router(
 api_router.include_router(
    sensors.router, prefix="/sensors", tags=["sensors"], responses=REPONSES_ADMIN
 )
 api_router.include_router(
    predictions.router, prefix="/predictions", tags=["predictions"], responses=REPONSES_LECTEUR
 )
@@ -22,11 +22,8 @@ from app.core.hashing import build_hasher
 from app.core.roles import Role
 from app.db.session import get_session_factory
 from app.main import create_app
 from app.repositories.alert import AlertRepository
 from app.repositories.recommendation import RecommendationRepository
 from app.repositories.user import UserRepository
 from app.schemas.auth import PASSWORD_MIN_LENGTH, SPECIAL_CHARACTERS, valide_complexite
 from app.services.recommendation import RecommendationService
 LONGUEUR_MOT_DE_PASSE_GENERE = 24
 CHEMIN_CONTRAT = Path(__file__).resolve().parent.parent / "openapi.json"
@@ -66,22 +63,6 @@ async def create_admin(
    )
 async def generate_recommendations(*, site_id: str | None) -> str:
    async with get_session_factory()() as session:
        service = RecommendationService(
            recommendations=RecommendationRepository(session),
            alerts=AlertRepository(session),
            transaction=session,
        )
        rapport = await service.generate(site_id=site_id)
    return (
        f"{rapport.alertes_examinees} alerte(s) examinée(s), "
        f"{rapport.recommandations_creees} recommandation(s) créée(s), "
        f"{rapport.deja_presentes} déjà présente(s)"
    )
 # Piège : le schéma ne doit dépendre ni du `.env` du poste ni des variables `APP_*`, sinon le
 # fichier versionné changerait de machine en machine et le test de dérive deviendrait un oracle
 # de configuration locale. Tout ce qui atteint le schéma est donc posé ici, `_env_file` compris.
@@ -128,14 +109,6 @@ def build_parser() -> argparse.ArgumentParser:
        "export-openapi", help="Écrit le contrat OpenAPI sur disque"
    )
    contrat.add_argument("--output", default=str(CHEMIN_CONTRAT))
    recommandations = sous_commandes.add_parser(
        "generate-recommendations",
        help="Applique le moteur de règles aux alertes en base",
    )
    recommandations.add_argument(
        "--site-id", default=None, help="Limite le traitement aux alertes d'un site"
    )
    return parser
@@ -179,10 +152,6 @@ def main(argv: list[str] | None = None) -> int:
        print(export_openapi(Path(arguments.output)))
        return 0
    if arguments.commande == "generate-recommendations":
        print(asyncio.run(generate_recommendations(site_id=arguments.site_id)))
        return 0
    mot_de_passe = read_password(generate=arguments.generate)
    succes, message = asyncio.run(
@@ -34,11 +34,6 @@ class Settings(BaseSettings):
    database_pool_size: int = 5
    database_max_overflow: int = 10
    mock_api_base_url: str = "https://api-mock.charlieandre.fr"
    mock_api_username: str | None = None
    mock_api_password: SecretStr | None = None
    mock_api_timeout_seconds: float = Field(default=10.0, gt=0)
    jwt_issuer: str = "enervision-api"
    jwt_audience: str = "enervision-web"
    access_token_ttl_seconds: int = Field(default=900, ge=60, le=3600)
@@ -1,68 +0,0 @@
 # Détection d'alertes internes EnerVision (issue #104) : script lancé à la main pour l'instant,
 # comme `enervision_ml.score` côté ML, sans automatisation Airflow pour l'ordonnancer.
 from __future__ import annotations
 import argparse
 import asyncio
 import sys
 from datetime import UTC, datetime
 from app.core.config import get_settings
 from app.db.session import get_session_factory
 from app.repositories.alert import AlertRepository
 from app.repositories.prediction import PredictionRepository
 from app.repositories.reading import ReadingRepository
 from app.repositories.site import SiteRepository
 from app.services.alert import AlertService
 async def run_detection(*, now: datetime | None = None, site_id: str | None = None) -> int:
    """Exécute les cinq règles de détection et enregistre les nouvelles alertes. Rend le nombre de
    lignes effectivement insérées (les doublons de `source_alert_id` sont silencieusement
    ignorés)."""
    async with get_session_factory()() as session:
        service = AlertService(
            alerts=AlertRepository(session),
            readings=ReadingRepository(session),
            predictions=PredictionRepository(session),
            sites=SiteRepository(session),
        )
        nouvelles = await service.detect(now=now, site_id=site_id)
        await session.commit()
    return len(nouvelles)
 def _parse_instant(valeur: str) -> datetime:
    instant = datetime.fromisoformat(valeur)
    return instant if instant.tzinfo is not None else instant.replace(tzinfo=UTC)
 def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
    parser = argparse.ArgumentParser(
        prog="python -m app.detection.internal_alerts",
        description="Détection d'alertes internes EnerVision",
    )
    parser.add_argument("--site-id", default=None, help="Limite la détection à un seul site.")
    parser.add_argument(
        "--now",
        type=_parse_instant,
        default=None,
        help=(
            "Instant de référence (ISO 8601, UTC si le fuseau est omis). Défaut : l'heure courante."
        ),
    )
    return parser.parse_args(argv)
 def main(argv: list[str] | None = None) -> int:
    args = parse_args(argv)
    # Échoue tôt si `APP_SECRET_KEY`/`DATABASE_URL` manquent, avant toute requête à la base.
    get_settings()
    nombre = asyncio.run(run_detection(now=args.now, site_id=args.site_id))
    print(f"{nombre} nouvelle(s) alerte(s) enregistrée(s).")
    return 0
 if __name__ == "__main__":  # pragma: no cover
    sys.exit(main())
@@ -1,416 +0,0 @@
 # Contrainte : la réponse de l'API Mock est une entrée hostile, pas une source de confiance.
 # Voir OWASP API10 dans docs/architecture/owasp-traceabilite.md. Rien de ce qu'elle renvoie
 # n'atteint la base sans passer par build_site_row() ou build_reading_row() : seuls les champs
 # attendus sont recopiés, les grandeurs physiques sont bornées par PHYSICAL_BOUNDS et la taille
 # des tableaux est plafonnée par MAX_SITES et par --limit. Une valeur hors bornes devient NULL
 # et laisse sa trace dans null_reasons plutôt que de lever : le mock émet des anomalies par
 # construction, et raw_data conserve de toute façon la réponse d'origine intacte.
 from __future__ import annotations
 import argparse
 import asyncio
 import json
 from datetime import datetime
 from typing import Any
 import httpx
 from sqlalchemy import text
 from sqlalchemy.ext.asyncio import AsyncConnection, create_async_engine
 from app.core.config import get_settings
 SOURCE_HISTORY = "api_history"
 MAX_SITES = 100
 MAX_LIMIT = 1000
 # Les quatre seules valeurs que la contrainte ck_reading_quality accepte.
 ACCEPTED_QUALITIES = frozenset({"good", "partial", "degraded", "critical"})
 PHYSICAL_BOUNDS: dict[str, tuple[float, float]] = {
    "consumption_kw": (0.0, 100_000.0),
    "consumption_kwh": (0.0, 100_000.0),
    "voltage_v": (0.0, 1_000.0),
    "current_a": (0.0, 10_000.0),
    "power_factor": (0.0, 1.0),
    "temperature_celsius": (-90.0, 60.0),
    "humidity_percent": (0.0, 100.0),
 }
 CAPACITY_BOUNDS = (0.0, 100_000.0)
 def create_mock_api_client() -> httpx.AsyncClient:
    settings = get_settings()
    if settings.mock_api_username is None or settings.mock_api_password is None:
        raise ValueError("Les identifiants de l'API Mock ne sont pas configurés.")
    return httpx.AsyncClient(
        base_url=settings.mock_api_base_url.rstrip("/"),
        auth=(
            settings.mock_api_username,
            settings.mock_api_password.get_secret_value(),
        ),
        timeout=settings.mock_api_timeout_seconds,
    )
 def read_text(payload: dict[str, Any], key: str) -> str:
    value = payload.get(key)
    if not isinstance(value, str) or not value:
        raise ValueError(f"Champ {key} absent ou invalide dans la réponse de l'API Mock.")
    return value
 def optional_text(value: Any) -> str | None:
    return value if isinstance(value, str) else None
 def coerce_measure(
    value: Any,
    bounds: tuple[float, float],
 ) -> float | None:
    if isinstance(value, bool) or not isinstance(value, int | float):
        return None
    lower, upper = bounds
    # Écarte aussi NaN et les infinis, qu'aucune comparaison de bornes ne retient.
    return float(value) if lower <= value <= upper else None
 def resolve_quality(
    value: Any,
    rejected: list[str],
 ) -> str | None:
    quality = value if isinstance(value, str) and value in ACCEPTED_QUALITIES else None
    if rejected:
        return "critical" if quality == "critical" else "degraded"
    return quality
 def resolve_null_reasons(
    value: Any,
    rejected: list[str],
 ) -> list[str]:
    reported = [str(reason) for reason in value] if isinstance(value, list) else []
    return reported + rejected
 async def fetch_sites(
    client: httpx.AsyncClient,
 ) -> list[dict[str, Any]]:
    response = await client.get("/api/v1/sites")
    response.raise_for_status()
    payload = response.json()
    if not isinstance(payload, list):
        raise ValueError("La réponse /api/v1/sites doit être une liste.")
    if len(payload) > MAX_SITES:
        raise ValueError(f"La réponse /api/v1/sites dépasse le plafond de {MAX_SITES} sites.")
    return payload
 def build_site_row(
    site: dict[str, Any],
 ) -> dict[str, Any]:
    return {
        "site_id": read_text(site, "site_id"),
        "site_type": read_text(site, "site_type"),
        "site_name": read_text(site, "site_name"),
        "location": optional_text(site.get("location")),
        "capacity_kw": coerce_measure(site.get("capacity_kw"), CAPACITY_BOUNDS),
        "status": optional_text(site.get("status")),
    }
 async def upsert_sites(
    connection: AsyncConnection,
    sites: list[dict[str, Any]],
 ) -> None:
    rows = [build_site_row(site) for site in sites]
    if not rows:
        return
    await connection.execute(
        text(
            """
            INSERT INTO site (
                site_id,
                site_type,
                site_name,
                location,
                capacity_kw,
                status
            )
            VALUES (
                :site_id,
                :site_type,
                :site_name,
                :location,
                :capacity_kw,
                :status
            )
            ON CONFLICT (site_id)
            DO UPDATE SET
                site_type = EXCLUDED.site_type,
                site_name = EXCLUDED.site_name,
                location = EXCLUDED.location,
                capacity_kw = EXCLUDED.capacity_kw,
                status = EXCLUDED.status
            """
        ),
        rows,
    )
 async def fetch_readings(
    client: httpx.AsyncClient,
    site_id: str,
    start_time: datetime,
    end_time: datetime,
    limit: int = MAX_LIMIT,
 ) -> list[dict[str, Any]]:
    response = await client.get(
        "/api/v1/readings",
        params={
            "site_id": site_id,
            "start_time": start_time.isoformat(),
            "end_time": end_time.isoformat(),
            "limit": limit,
        },
    )
    response.raise_for_status()
    payload = response.json()
    if not isinstance(payload, list):
        raise ValueError("La réponse /api/v1/readings doit être une liste.")
    if len(payload) > limit:
        raise ValueError(f"La réponse /api/v1/readings dépasse la limite demandée de {limit}.")
    return payload
 def build_reading_row(
    reading: dict[str, Any],
 ) -> dict[str, Any]:
    measures: dict[str, float | None] = {}
    rejected: list[str] = []
    for name, bounds in PHYSICAL_BOUNDS.items():
        received = reading.get(name)
        measures[name] = coerce_measure(received, bounds)
        if received is not None and measures[name] is None:
            rejected.append(f"out_of_physical_bounds:{name}")
    return {
        "site_id": read_text(reading, "site_id"),
        "timestamp": parse_datetime(read_text(reading, "timestamp")),
        "source": SOURCE_HISTORY,
        "dataset_id": None,
        **measures,
        "consumption_euros": None,
        "solar_irradiance_wm2": None,
        "is_working_hours": None,
        "data_quality": resolve_quality(reading.get("data_quality"), rejected),
        "null_reasons": resolve_null_reasons(reading.get("null_reasons"), rejected),
        "imputed_values": None,
        "imputation_method": None,
        "raw_data": json.dumps(
            reading,
            ensure_ascii=False,
        ),
    }
 # Le conflit vise l'index unique uq_reading_source plutôt que la table entière : sans cible
 # nommée, DO NOTHING avalerait aussi une violation de clé primaire.
 READING_INSERT = text(
    """
    INSERT INTO reading (
        site_id,
        timestamp,
        source,
        dataset_id,
        consumption_kw,
        consumption_kwh,
        consumption_euros,
        voltage_v,
        current_a,
        power_factor,
        temperature_celsius,
        humidity_percent,
        solar_irradiance_wm2,
        is_working_hours,
        data_quality,
        null_reasons,
        imputed_values,
        imputation_method,
        raw_data
    )
    VALUES (
        :site_id,
        :timestamp,
        :source,
        :dataset_id,
        :consumption_kw,
        :consumption_kwh,
        :consumption_euros,
        :voltage_v,
        :current_a,
        :power_factor,
        :temperature_celsius,
        :humidity_percent,
        :solar_irradiance_wm2,
        :is_working_hours,
        :data_quality,
        :null_reasons,
        CAST(:imputed_values AS jsonb),
        :imputation_method,
        CAST(:raw_data AS jsonb)
    )
    ON CONFLICT (site_id, timestamp, source, (coalesce(dataset_id, 0)))
    DO NOTHING
    """
 )
 def build_reading_batch(
    readings: list[dict[str, Any]],
 ) -> list[dict[str, Any]]:
    return [build_reading_row(reading) for reading in readings]
 async def import_mock_api_history(
    start_time: datetime,
    end_time: datetime,
    limit: int,
    dry_run: bool,
 ) -> None:
    settings = get_settings()
    async with create_mock_api_client() as client:
        sites = await fetch_sites(client)
        print(f"Sites récupérés : {len(sites)}")
        all_readings: list[dict[str, Any]] = []
        for site in sites:
            site_id = read_text(site, "site_id")
            readings = await fetch_readings(
                client=client,
                site_id=site_id,
                start_time=start_time,
                end_time=end_time,
                limit=limit,
            )
            print(f"{site_id}: {len(readings)} lectures")
            all_readings.extend(readings)
    print(f"Lectures récupérées : {len(all_readings)}")
    if dry_run:
        print("Dry-run terminé : aucune donnée écrite.")
        return
    engine = create_async_engine(
        str(settings.database_url),
        pool_pre_ping=True,
    )
    try:
        async with engine.begin() as connection:
            await upsert_sites(
                connection,
                sites,
            )
            rows = build_reading_batch(all_readings)
            if rows:
                await connection.execute(
                    READING_INSERT,
                    rows,
                )
    finally:
        await engine.dispose()
    print("Import API Mock terminé.")
 def parse_datetime(value: str) -> datetime:
    return datetime.fromisoformat(value.replace("Z", "+00:00"))
 def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(description=("Import historique depuis l'API Mock EnerVision"))
    parser.add_argument(
        "--start-time",
        required=True,
        type=parse_datetime,
    )
    parser.add_argument(
        "--end-time",
        required=True,
        type=parse_datetime,
    )
    parser.add_argument(
        "--limit",
        type=int,
        default=MAX_LIMIT,
    )
    parser.add_argument(
        "--dry-run",
        action="store_true",
    )
    return parser.parse_args()
 def main() -> None:
    args = parse_args()
    if args.limit < 1 or args.limit > MAX_LIMIT:
        raise ValueError(f"--limit doit être compris entre 1 et {MAX_LIMIT}.")
    if args.start_time >= args.end_time:
        raise ValueError("--start-time doit être antérieur à --end-time.")
    asyncio.run(
        import_mock_api_history(
            start_time=args.start_time,
            end_time=args.end_time,
            limit=args.limit,
            dry_run=args.dry_run,
        )
    )
 if __name__ == "__main__":
    main()
@@ -1,7 +1,6 @@
 from collections.abc import Sequence
 from sqlalchemy import select
 from sqlalchemy.dialects.postgresql import insert
 from sqlalchemy.ext.asyncio import AsyncSession
 from app.models.energy import Alert
@@ -20,36 +19,3 @@ class AlertRepository:
        if severity is not None:
            requete = requete.where(Alert.severity == severity)
        return (await self._session.scalars(requete)).all()
    async def create_many(self, alerts: Sequence[Alert]) -> Sequence[Alert]:
        # `ON CONFLICT DO NOTHING` sur `uq_alert_source_reference` : rejouer la détection sur une
        # fenêtre qui recouvre une exécution précédente ne doit pas dupliquer une alerte déjà
        # enregistrée. `RETURNING` ne renvoie donc que les lignes effectivement insérées.
        if not alerts:
            return []
        valeurs = [
            {
                "source_alert_id": alerte.source_alert_id,
                "site_id": alerte.site_id,
                "source": alerte.source,
                "timestamp": alerte.timestamp,
                "type": alerte.type,
                "severity": alerte.severity,
                "message": alerte.message,
                "value": alerte.value,
                "threshold": alerte.threshold,
                "metric": alerte.metric,
                "prediction_id": alerte.prediction_id,
                "raw_data": alerte.raw_data,
            }
            for alerte in alerts
        ]
        requete = (
            insert(Alert)
            .values(valeurs)
            .on_conflict_do_nothing(constraint="uq_alert_source_reference")
            .returning(Alert)
        )
        resultat = await self._session.execute(requete)
        await self._session.flush()
        return resultat.scalars().all()
@@ -1,49 +0,0 @@
 from collections.abc import Sequence
 from datetime import datetime
 from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
 from app.models.energy import Prediction
 class PredictionRepository:
    def __init__(self, session: AsyncSession) -> None:
        self._session = session
    async def list_since(
        self, *, since: datetime, site_id: str | None = None
    ) -> Sequence[Prediction]:
        # Restreint à `available` : une prévision `insufficient_data`/`error` n'a pas de
        # `predicted_value` à comparer à une lecture réelle (détection d'anomalie).
        # Piège : `prediction` n'a pas d'unicité sur `(site_id, target_at)` (cf.
        # `enervision_ml.score`, qui insère toujours une nouvelle ligne plutôt que d'écraser la
        # précédente). `prediction_id` en dernier départage donc les égalités de `target_at` par
        # ordre croissant : `_detect_anomaly` construit un dict qui garde le dernier rencontré,
        # c'est-à-dire le run le plus récent plutôt qu'une ligne choisie au hasard par le plan
        # d'exécution.
        requete = (
            select(Prediction)
            .where(Prediction.target_at >= since, Prediction.status == "available")
            .order_by(Prediction.site_id, Prediction.target_at, Prediction.prediction_id)
        )
        if site_id is not None:
            requete = requete.where(Prediction.site_id == site_id)
        return (await self._session.scalars(requete)).all()
    async def latest_by_site(self) -> Sequence[Prediction]:
        # `.distinct(site_id)` compile en `DISTINCT ON (site_id)` sous PostgreSQL : une seule
        # ligne par site, la plus récente grâce à l'ordre composite qui suit. Même mécanisme que
        # `ReadingRepository.latest_by_site`. Trié sur `target_at` (couvert par
        # `ix_prediction_site_target`) plutôt que `created_at` : c'est la prévision la plus
        # récente qui compte pour un tableau de bord, pas forcément le dernier run de scoring.
        requete = (
            select(Prediction)
            .distinct(Prediction.site_id)
            .order_by(
                Prediction.site_id,
                Prediction.target_at.desc(),
                Prediction.prediction_id.desc(),
            )
        )
        return (await self._session.scalars(requete)).all()
@@ -34,21 +34,6 @@ class ReadingRepository:
        lecture: Reading | None = await self._session.scalar(requete)
        return lecture
    async def list_since(self, *, since: datetime, site_id: str | None = None) -> Sequence[Reading]:
        # Trié par site puis par heure croissante : la détection d'alertes (spike) a besoin de
        # comparer chaque lecture à celle qui la précède immédiatement pour le même site.
        # `reading_id` en dernier départage : `uq_reading_source` autorise deux lignes au même
        # `site_id`+`timestamp` quand la `source` diffère (même piège que `latest_for_site`), sans
        # quoi l'ordre entre elles ne serait pas garanti d'un appel à l'autre.
        requete = (
            select(Reading)
            .where(Reading.timestamp >= since)
            .order_by(Reading.site_id, Reading.timestamp, Reading.reading_id)
        )
        if site_id is not None:
            requete = requete.where(Reading.site_id == site_id)
        return (await self._session.scalars(requete)).all()
    async def list_history(
        self,
        *,
@@ -1,24 +1,11 @@
 from collections.abc import Sequence
 from dataclasses import asdict, dataclass
 from sqlalchemy import select
 from sqlalchemy.dialects.postgresql import insert
 from sqlalchemy.ext.asyncio import AsyncSession
 from app.models.energy import Recommendation
@dataclass(frozen=True, slots=True)
 class NouvelleRecommandation:
    alert_id: int
    action: str
    explanation: str
    rule_reference: str
 TAILLE_DE_LOT = 1000
 class RecommendationRepository:
    def __init__(self, session: AsyncSession) -> None:
        self._session = session
@@ -33,19 +20,3 @@ class RecommendationRepository:
        )
        recommendation: Recommendation | None = await self._session.scalar(requete)
        return recommendation
    # Pourquoi : l'idempotence est déléguée à `uq_recommendation_alert_rule` plutôt qu'à une
    # lecture préalable, qui laisserait une fenêtre entre le contrôle et l'insertion.
    async def create_missing(self, nouvelles: Sequence[NouvelleRecommandation]) -> int:
        creees = 0
        # Piège : asyncpg plafonne une requête à 32 767 paramètres, soit 8 191 lignes de quatre
        # colonnes. Au-delà de ce seuil un `INSERT` d'un seul tenant échouerait.
        for debut in range(0, len(nouvelles), TAILLE_DE_LOT):
            requete = (
                insert(Recommendation)
                .values([asdict(nouvelle) for nouvelle in nouvelles[debut : debut + TAILLE_DE_LOT]])
                .on_conflict_do_nothing(constraint="uq_recommendation_alert_rule")
                .returning(Recommendation.recommendation_id)
            )
            creees += len((await self._session.scalars(requete)).all())
        return creees
@@ -1,43 +0,0 @@
 from datetime import datetime
 from enum import StrEnum
 from pydantic import BaseModel, ConfigDict
 class PredictionTargetMetric(StrEnum):
    CONSUMPTION_KWH = "consumption_kwh"
    CONSUMPTION_KW = "consumption_kw"
 class PredictionStatus(StrEnum):
    AVAILABLE = "available"
    INSUFFICIENT_DATA = "insufficient_data"
    ERROR = "error"
 class SitePredictionResponse(BaseModel):
    model_config = ConfigDict(from_attributes=True)
    target_at: datetime
    target_metric: PredictionTargetMetric
    period_minutes: int | None
    predicted_value: float | None
    status: PredictionStatus
    failure_reason: str | None
    model_reference: str
    created_at: datetime
 class SitePredictionSummaryResponse(BaseModel):
    model_config = ConfigDict(from_attributes=True)
    site_id: str
    site_name: str
    prediction: SitePredictionResponse | None
 class PredictionSummaryResponse(BaseModel):
    model_config = ConfigDict(from_attributes=True)
    timestamp: datetime
    sites: list[SitePredictionSummaryResponse]
@@ -12,9 +12,3 @@ class RecommendationResponse(BaseModel):
    explanation: str
    rule_reference: str
    created_at: datetime
 class RecommendationGenerationResponse(BaseModel):
    alerts_examined: int
    recommendations_created: int
    already_present: int
@@ -1,323 +1,14 @@
 from collections.abc import Sequence
 from datetime import UTC, datetime, timedelta
-from app.models.energy import Alert, Prediction, Reading, Site
+from app.models.energy import Alert
 from app.repositories.alert import AlertRepository
 from app.repositories.prediction import PredictionRepository
 from app.repositories.reading import ReadingRepository
 from app.repositories.site import SiteRepository
 # Fenêtre de lectures/prédictions analysée à chaque exécution : assez large pour couvrir une paire
 # de lectures consécutives (spike) et une coupure prolongée (outage), sans réanalyser tout
 # l'historique à chaque lancement manuel du script de détection.
 LOOKBACK = timedelta(hours=48)
 # Cadence nominale d'une lecture : le CSV historique comme l'API Mock livrent un pas horaire.
 EXPECTED_INTERVAL = timedelta(hours=1)
 # Au-delà de trois pas manqués, on parle de coupure plutôt que d'un simple retard d'ingestion.
 OUTAGE_THRESHOLD = EXPECTED_INTERVAL * 3
 # +/-50% entre deux lectures consécutives du même site.
 SPIKE_RELATIVE_THRESHOLD = 0.5
 # 30% d'écart entre la consommation réelle et la prévision du même site/instant.
 ANOMALY_RELATIVE_THRESHOLD = 0.3
 # Une prévision quasi nulle rend l'écart relatif ininterprétable ; on l'ignore plutôt.
 ANOMALY_MINIMUM_PREDICTED_VALUE = 1e-6
 THRESHOLD_METRIC = "consumption_kw"
 ANOMALY_METRIC = "consumption_kwh"
 # `data_quality` -> sévérité du capteur défaillant. `good` est volontairement absent : il ne
 # déclenche jamais d'alerte.
 QUALITE_VERS_SEVERITE: dict[str, str] = {
    "partial": "low",
    "degraded": "medium",
    "critical": "critical",
 }
 class AlertService:
-    def __init__(
+    def __init__(self, *, alerts: AlertRepository) -> None:
        self,
        *,
        alerts: AlertRepository,
        readings: ReadingRepository,
        predictions: PredictionRepository,
        sites: SiteRepository,
    ) -> None:
        self._alerts = alerts
        self._readings = readings
        self._predictions = predictions
        self._sites = sites
    async def list_all(
        self, *, site_id: str | None = None, severity: str | None = None
    ) -> Sequence[Alert]:
        return await self._alerts.list_all(site_id=site_id, severity=severity)
    async def detect(
        self, *, now: datetime | None = None, site_id: str | None = None
    ) -> Sequence[Alert]:
        """Compare les lectures/prévisions récentes aux cinq règles internes et enregistre les
        alertes déclenchées (`source='enervision'`). Idempotent grâce à `source_alert_id` :
        rejouer sur une fenêtre déjà analysée ne recrée pas les mêmes lignes."""
        instant = now or datetime.now(UTC)
        depuis = instant - LOOKBACK
        sites = await self._sites.list_all()
        if site_id is not None:
            sites = [site for site in sites if site.site_id == site_id]
        sites_par_id = {site.site_id: site for site in sites}
        if not sites_par_id:
            return []
        lectures = [
            lecture
            for lecture in await self._readings.list_since(since=depuis, site_id=site_id)
            if lecture.site_id in sites_par_id
        ]
        predictions = [
            prediction
            for prediction in await self._predictions.list_since(since=depuis, site_id=site_id)
            if prediction.site_id in sites_par_id
        ]
        dernieres_lectures = {
            lecture.site_id: lecture
            for lecture in await self._readings.latest_by_site()
            if lecture.site_id in sites_par_id
        }
        candidates = [
            *_detect_threshold(lectures, sites_par_id),
            *_detect_spike(lectures),
            *_detect_anomaly(lectures, predictions),
            *_detect_outage(sites, dernieres_lectures, instant),
            *_detect_sensor(lectures),
        ]
        if not candidates:
            return []
        return await self._alerts.create_many(candidates)
 def _severity_from_ratio(ratio: float) -> str:
    if ratio >= 2.0:
        return "critical"
    if ratio >= 1.5:
        return "high"
    if ratio >= 1.2:
        return "medium"
    return "low"
 def _detect_threshold(lectures: Sequence[Reading], sites_par_id: dict[str, Site]) -> list[Alert]:
    # Seuil fixe = la capacité déclarée du site : dépasser `capacity_kw` est un dépassement
    # matériel, pas une simple variation, et évite un seuil arbitraire non fourni par le domaine.
    alertes = []
    for lecture in lectures:
        site = sites_par_id[lecture.site_id]
        valeur = lecture.consumption_kw
        if site.capacity_kw is None or site.capacity_kw <= 0 or valeur is None:
            continue
        if valeur <= site.capacity_kw:
            continue
        alertes.append(
            Alert(
                source_alert_id=f"threshold:{THRESHOLD_METRIC}:{lecture.timestamp.isoformat()}",
                site_id=lecture.site_id,
                source="enervision",
                timestamp=lecture.timestamp,
                type="threshold",
                severity=_severity_from_ratio(valeur / site.capacity_kw),
                message=(
                    f"Puissance appelée {valeur:.1f} kW au-dessus de la capacité du site "
                    f"({site.capacity_kw:.1f} kW)"
                ),
                value=valeur,
                threshold=site.capacity_kw,
                metric=THRESHOLD_METRIC,
                prediction_id=None,
                raw_data={},
            )
        )
    return alertes
 def _detect_spike(lectures: Sequence[Reading]) -> list[Alert]:
    # `lectures` est triée par site, heure puis `reading_id` (cf. `ReadingRepository.list_since`) :
    # deux lignes consécutives du même site sont donc deux mesures consécutives dans le temps,
    # sauf lorsqu'elles partagent le même horodatage (deux `source` différentes pour le même
    # instant, permises par `uq_reading_source`) : ce n'est alors pas une variation réelle, on
    # l'ignore plutôt que de générer une fausse alerte figée par son `source_alert_id`.
    alertes = []
    precedente: Reading | None = None
    for lecture in lectures:
        if (
            precedente is None
            or precedente.site_id != lecture.site_id
            or precedente.timestamp == lecture.timestamp
        ):
            precedente = lecture
            continue
        avant, apres = precedente.consumption_kw, lecture.consumption_kw
        precedente = lecture
        if avant is None or apres is None:
            continue
        if avant == 0:
            # Une variation relative n'a pas de sens depuis zéro, mais un redémarrage direct à
            # une consommation positive reste le signal le plus alarmant du lot : `critical`
            # plutôt qu'un ratio indéfini.
            if apres > 0:
                alertes.append(_spike_alert(lecture, avant, apres, severity="critical"))
            continue
        variation = abs(apres - avant) / abs(avant)
        if variation < SPIKE_RELATIVE_THRESHOLD:
            continue
        alertes.append(
            _spike_alert(
                lecture,
                avant,
                apres,
                severity=_severity_from_ratio(variation / SPIKE_RELATIVE_THRESHOLD),
            )
        )
    return alertes
 def _spike_alert(lecture: Reading, avant: float, apres: float, *, severity: str) -> Alert:
    return Alert(
        source_alert_id=f"spike:{THRESHOLD_METRIC}:{lecture.timestamp.isoformat()}",
        site_id=lecture.site_id,
        source="enervision",
        timestamp=lecture.timestamp,
        type="spike",
        severity=severity,
        message=(
            f"Variation brutale entre deux lectures consécutives ({avant:.1f} kW -> {apres:.1f} kW)"
        ),
        value=apres,
        threshold=avant,
        metric=THRESHOLD_METRIC,
        prediction_id=None,
        raw_data={},
    )
 def _detect_anomaly(lectures: Sequence[Reading], predictions: Sequence[Prediction]) -> list[Alert]:
    # Alignement strict (site_id, target_at == timestamp) : `enervision_ml.score` produit une
    # cible à l'heure pile suivant la dernière lecture, sur la même grille horaire que `reading`.
    predictions_par_cle = {
        (prediction.site_id, prediction.target_at): prediction
        for prediction in predictions
        if prediction.target_metric == ANOMALY_METRIC
    }
    alertes = []
    for lecture in lectures:
        prediction = predictions_par_cle.get((lecture.site_id, lecture.timestamp))
        reel = lecture.consumption_kwh
        if prediction is None or reel is None or prediction.predicted_value is None:
            continue
        predite = prediction.predicted_value
        if abs(predite) < ANOMALY_MINIMUM_PREDICTED_VALUE:
            continue
        ecart = abs(reel - predite) / abs(predite)
        if ecart < ANOMALY_RELATIVE_THRESHOLD:
            continue
        alertes.append(
            Alert(
                source_alert_id=f"anomaly:{ANOMALY_METRIC}:{lecture.timestamp.isoformat()}",
                site_id=lecture.site_id,
                source="enervision",
                timestamp=lecture.timestamp,
                type="anomaly",
                severity=_severity_from_ratio(ecart / ANOMALY_RELATIVE_THRESHOLD),
                message=(
                    f"Écart de {ecart * 100:.0f}% entre la consommation mesurée ({reel:.1f} kWh) "
                    f"et la prévision ({predite:.1f} kWh)"
                ),
                value=reel,
                threshold=predite,
                metric=ANOMALY_METRIC,
                prediction_id=prediction.prediction_id,
                raw_data={},
            )
        )
    return alertes
 def _detect_outage(
    sites: Sequence[Site], dernieres_lectures: dict[str, Reading], now: datetime
 ) -> list[Alert]:
    alertes = []
    for site in sites:
        derniere = dernieres_lectures.get(site.site_id)
        if derniere is None:
            alertes.append(
                _outage_alert(
                    site.site_id,
                    now,
                    reference=None,
                    message="Aucune lecture n'a jamais été reçue pour ce site",
                    severity="critical",
                )
            )
            continue
        absence = now - derniere.timestamp
        if absence < OUTAGE_THRESHOLD:
            continue
        alertes.append(
            _outage_alert(
                site.site_id,
                now,
                reference=derniere.timestamp,
                message=(
                    f"Aucune lecture depuis {absence} (dernière lecture : "
                    f"{derniere.timestamp.isoformat()})"
                ),
                severity=_severity_from_ratio(absence / OUTAGE_THRESHOLD),
            )
        )
    return alertes
 def _outage_alert(
    site_id: str, now: datetime, *, reference: datetime | None, message: str, severity: str
 ) -> Alert:
    return Alert(
        source_alert_id=f"outage:{reference.isoformat() if reference is not None else 'jamais'}",
        site_id=site_id,
        source="enervision",
        timestamp=now,
        type="outage",
        severity=severity,
        message=message,
        value=None,
        threshold=None,
        metric=None,
        prediction_id=None,
        raw_data={},
    )
 def _detect_sensor(lectures: Sequence[Reading]) -> list[Alert]:
    alertes = []
    for lecture in lectures:
        severite = QUALITE_VERS_SEVERITE.get(lecture.data_quality or "")
        if severite is None:
            continue
        raisons = ", ".join(lecture.null_reasons or []) or "raison non précisée"
        alertes.append(
            Alert(
                source_alert_id=f"sensor:{lecture.timestamp.isoformat()}",
                site_id=lecture.site_id,
                source="enervision",
                timestamp=lecture.timestamp,
                type="sensor",
                severity=severite,
                message=f"Qualité de mesure {lecture.data_quality} ({raisons})",
                value=None,
                threshold=None,
                metric=None,
                prediction_id=None,
                raw_data={},
            )
        )
    return alertes
@@ -1,68 +0,0 @@
 from dataclasses import dataclass
 from datetime import UTC, datetime
 from app.models.energy import Prediction, Site
 from app.repositories.prediction import PredictionRepository
 from app.repositories.site import SiteRepository
@dataclass(frozen=True, slots=True)
 class SitePrediction:
    target_at: datetime
    target_metric: str
    period_minutes: int | None
    predicted_value: float | None
    status: str
    failure_reason: str | None
    model_reference: str
    created_at: datetime
@dataclass(frozen=True, slots=True)
 class SitePredictionSummary:
    site_id: str
    site_name: str
    prediction: SitePrediction | None
@dataclass(frozen=True, slots=True)
 class PredictionSummary:
    timestamp: datetime
    sites: list[SitePredictionSummary]
 class PredictionService:
    def __init__(self, sites: SiteRepository, predictions: PredictionRepository) -> None:
        self._sites = sites
        self._predictions = predictions
    async def summary(self) -> PredictionSummary:
        sites = await self._sites.list_all()
        dernieres = {p.site_id: p for p in await self._predictions.latest_by_site()}
        return PredictionSummary(
            timestamp=datetime.now(UTC),
            sites=[_resume_site(site, dernieres.get(site.site_id)) for site in sites],
        )
 def _resume_site(site: Site, derniere: Prediction | None) -> SitePredictionSummary:
    # Piège : l'absence de ligne signifie « jamais scoré », pas une valeur pseudo-statut, qui
    # n'existe pas dans la contrainte de la table. `prediction` reste `None` plutôt que de
    # fabriquer un statut absent du domaine `available`/`insufficient_data`/`error`.
    prediction = None
    if derniere is not None:
        prediction = SitePrediction(
            target_at=derniere.target_at,
            target_metric=derniere.target_metric,
            period_minutes=derniere.period_minutes,
            predicted_value=derniere.predicted_value,
            status=derniere.status,
            failure_reason=derniere.failure_reason,
            model_reference=derniere.model_reference,
            created_at=derniere.created_at,
        )
    return SitePredictionSummary(
        site_id=site.site_id, site_name=site.site_name, prediction=prediction
    )
@@ -1,15 +1,7 @@
 from collections.abc import Sequence
 from dataclasses import dataclass
 from typing import Protocol
 from app.models.energy import Recommendation
 from app.repositories.alert import AlertRepository
 from app.repositories.recommendation import RecommendationRepository
 from app.services.recommendation_rules import applique_les_regles
 class Transaction(Protocol):
    async def commit(self) -> None: ...
 class RecommendationError(Exception):
@@ -20,24 +12,9 @@ class RecommendationNotFoundError(RecommendationError):
    pass
@dataclass(frozen=True, slots=True)
 class RapportGeneration:
    alertes_examinees: int
    recommandations_creees: int
    deja_presentes: int
 class RecommendationService:
-    def __init__(
+    def __init__(self, *, recommendations: RecommendationRepository) -> None:
        self,
        *,
        recommendations: RecommendationRepository,
        alerts: AlertRepository,
        transaction: Transaction,
    ) -> None:
        self._recommendations = recommendations
        self._alerts = alerts
        self._transaction = transaction
    async def list_all(self) -> Sequence[Recommendation]:
        return await self._recommendations.list_all()
@@ -47,16 +24,3 @@ class RecommendationService:
        if recommendation is None:
            raise RecommendationNotFoundError(recommendation_id)
        return recommendation
    async def generate(self, *, site_id: str | None = None) -> RapportGeneration:
        alertes = await self._alerts.list_all(site_id=site_id)
        nouvelles = [nouvelle for alerte in alertes for nouvelle in applique_les_regles(alerte)]
        creees = await self._recommendations.create_missing(nouvelles)
        await self._transaction.commit()
        return RapportGeneration(
            alertes_examinees=len(alertes),
            recommandations_creees=creees,
            deja_presentes=len(nouvelles) - creees,
        )
@@ -1,117 +0,0 @@
 # Piège : `rule_reference` est la clé d'idempotence en base, portée par la contrainte
 # `uq_recommendation_alert_rule`. Renommer une référence déjà livrée ne remplace pas les
 # recommandations existantes, il en crée de nouvelles à côté. Une règle qui change de sens
 # prend donc une référence suffixée `-v2` - REGLES.
 from collections.abc import Callable
 from dataclasses import dataclass
 from typing import Final
 from app.models.energy import Alert
 from app.repositories.recommendation import NouvelleRecommandation
 from app.schemas.alert import AlertSeverity, AlertType
 FACTEUR_DEPASSEMENT_MAJEUR: Final = 1.2
 POURCENTAGE_DEPASSEMENT_MAJEUR: Final = round((FACTEUR_DEPASSEMENT_MAJEUR - 1) * 100)
@dataclass(frozen=True, slots=True)
 class Regle:
    reference: str
    action: str
    declencheur: Callable[[Alert], bool]
    motif: Callable[[Alert], str]
 def _du_type(attendu: AlertType) -> Callable[[Alert], bool]:
    return lambda alerte: alerte.type == attendu
 def _de_severite(attendue: AlertSeverity) -> Callable[[Alert], bool]:
    return lambda alerte: alerte.severity == attendue
 # Un seuil nul ou négatif rendrait le rapport `value / threshold` arbitraire : l'alerte ne
 # renseigne alors aucun dépassement exploitable, et la règle ne se déclenche pas.
 def _depasse_largement_le_seuil(alerte: Alert) -> bool:
    if alerte.value is None or alerte.threshold is None or alerte.threshold <= 0:
        return False
    return alerte.value >= alerte.threshold * FACTEUR_DEPASSEMENT_MAJEUR
 REGLES: Final[tuple[Regle, ...]] = (
    Regle(
        reference="spike-delestage-v1",
        action="Délester les équipements non prioritaires sur le créneau du pic",
        declencheur=_du_type(AlertType.SPIKE),
        motif=lambda alerte: f"Pic de consommation signalé sur le site {alerte.site_id}",
    ),
    Regle(
        reference="threshold-reduction-v1",
        action="Ramener la puissance appelée sous le seuil contractuel",
        declencheur=_du_type(AlertType.THRESHOLD),
        motif=lambda alerte: f"Seuil de consommation dépassé sur le site {alerte.site_id}",
    ),
    Regle(
        reference="outage-secours-v1",
        action="Basculer sur l'alimentation de secours et prévenir l'exploitant",
        declencheur=_du_type(AlertType.OUTAGE),
        motif=lambda alerte: (
            f"Risque de surcharge ou de coupure imminente sur le site {alerte.site_id}"
        ),
    ),
    Regle(
        reference="sensor-maintenance-v1",
        action="Planifier une intervention de maintenance sur le capteur",
        declencheur=_du_type(AlertType.SENSOR),
        motif=lambda alerte: (
            f"Capteur défaillant sur le site {alerte.site_id}, les mesures ne sont plus fiables"
        ),
    ),
    Regle(
        reference="anomaly-verification-v1",
        action="Confronter la mesure à la prévision et vérifier le paramétrage du site",
        declencheur=_du_type(AlertType.ANOMALY),
        motif=lambda alerte: (
            f"Écart anormal entre la mesure et le comportement attendu du site {alerte.site_id}"
        ),
    ),
    Regle(
        reference="escalade-astreinte-v1",
        action="Escalader à l'astreinte sous une heure",
        declencheur=_de_severite(AlertSeverity.CRITICAL),
        motif=lambda alerte: f"Alerte de sévérité critique sur le site {alerte.site_id}",
    ),
    Regle(
        reference="contrat-puissance-v1",
        action="Réévaluer la puissance souscrite au contrat",
        declencheur=_depasse_largement_le_seuil,
        motif=lambda alerte: (
            f"Dépassement d'au moins {POURCENTAGE_DEPASSEMENT_MAJEUR} % du seuil "
            f"sur le site {alerte.site_id}"
        ),
    ),
 )
 def applique_les_regles(alerte: Alert) -> list[NouvelleRecommandation]:
    contexte = _contexte_de_mesure(alerte)
    return [
        NouvelleRecommandation(
            alert_id=alerte.alert_id,
            action=regle.action,
            explanation=f"{regle.motif(alerte)}{contexte}.",
            rule_reference=regle.reference,
        )
        for regle in REGLES
        if regle.declencheur(alerte)
    ]
 def _contexte_de_mesure(alerte: Alert) -> str:
    if alerte.value is None:
        return ""
    grandeur = alerte.metric or "valeur"
    if alerte.threshold is None:
        return f" ({grandeur} mesurée à {alerte.value})"
    return f" ({grandeur} mesurée à {alerte.value}, seuil {alerte.threshold})"
@@ -1453,90 +1453,6 @@
        }
      }
    },
    "/api/v1/recommendations/generate": {
      "post": {
        "tags": [
          "recommendations"
        ],
        "summary": "Génère les recommandations à partir des alertes",
        "operationId": "generate_recommendations_api_v1_recommendations_generate_post",
        "security": [
          {
            "Jeton d'accès": []
          }
        ],
        "parameters": [
          {
            "name": "site_id",
            "in": "query",
            "required": false,
            "schema": {
              "anyOf": [
                {
                  "type": "string"
                },
                {
                  "type": "null"
                }
              ],
              "title": "Site Id"
            }
          }
        ],
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/RecommendationGenerationResponse"
                }
              }
            }
          },
          "500": {
            "description": "Erreur interne. `correlation` identifie la trace côté serveur, qui n'est pas renvoyée au client.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/InternalErrorResponse"
                }
              }
            }
          },
          "401": {
            "description": "Jeton absent, illisible, périmé, ou rendu caduc par un changement de rôle ou une désactivation. L'en-tête `WWW-Authenticate` porte la cause dans `error=`.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            }
          },
          "403": {
            "description": "Droits insuffisants, ou mot de passe provisoire à changer quand `detail` vaut `password_change_required`.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            }
          },
          "422": {
            "description": "Corps invalide. Le détail nomme le champ fautif et le type d'erreur, jamais la valeur envoyée.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ValidationErrorResponse"
                }
              }
            }
          }
        }
      }
    },
    "/api/v1/stats/summary": {
      "get": {
        "tags": [
@@ -1803,62 +1719,6 @@
          }
        ]
      }
    },
    "/api/v1/predictions": {
      "get": {
        "tags": [
          "predictions"
        ],
        "summary": "Dernière prédiction de consommation par site",
        "operationId": "get_predictions_api_v1_predictions_get",
        "responses": {
          "200": {
            "description": "Successful Response",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionSummaryResponse"
                }
              }
            }
          },
          "500": {
            "description": "Erreur interne. `correlation` identifie la trace côté serveur, qui n'est pas renvoyée au client.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/InternalErrorResponse"
                }
              }
            }
          },
          "401": {
            "description": "Jeton absent, illisible, périmé, ou rendu caduc par un changement de rôle ou une désactivation. L'en-tête `WWW-Authenticate` porte la cause dans `error=`.",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            }
          },
          "403": {
            "description": "Mot de passe provisoire à changer (`detail` vaut `password_change_required`).",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/ErrorResponse"
                }
              }
            }
          }
        },
        "security": [
          {
            "Jeton d'accès": []
          }
        ]
      }
    }
  },
  "components": {
@@ -2112,45 +1972,6 @@
        ],
        "title": "PasswordChangeRequest"
      },
      "PredictionStatus": {
        "type": "string",
        "enum": [
          "available",
          "insufficient_data",
          "error"
        ],
        "title": "PredictionStatus"
      },
      "PredictionSummaryResponse": {
        "properties": {
          "timestamp": {
            "type": "string",
            "format": "date-time",
            "title": "Timestamp"
          },
          "sites": {
            "items": {
              "$ref": "#/components/schemas/SitePredictionSummaryResponse"
            },
            "type": "array",
            "title": "Sites"
          }
        },
        "type": "object",
        "required": [
          "timestamp",
          "sites"
        ],
        "title": "PredictionSummaryResponse"
      },
      "PredictionTargetMetric": {
        "type": "string",
        "enum": [
          "consumption_kwh",
          "consumption_kw"
        ],
        "title": "PredictionTargetMetric"
      },
      "PrincipalResponse": {
        "properties": {
          "id": {
@@ -2428,29 +2249,6 @@
        ],
        "title": "ReadingSource"
      },
      "RecommendationGenerationResponse": {
        "properties": {
          "alerts_examined": {
            "type": "integer",
            "title": "Alerts Examined"
          },
          "recommendations_created": {
            "type": "integer",
            "title": "Recommendations Created"
          },
          "already_present": {
            "type": "integer",
            "title": "Already Present"
          }
        },
        "type": "object",
        "required": [
          "alerts_examined",
          "recommendations_created",
          "already_present"
        ],
        "title": "RecommendationGenerationResponse"
      },
      "RecommendationResponse": {
        "properties": {
          "recommendation_id": {
@@ -2720,104 +2518,6 @@
        ],
        "title": "SiteCurrentResponse"
      },
      "SitePredictionResponse": {
        "properties": {
          "target_at": {
            "type": "string",
            "format": "date-time",
            "title": "Target At"
          },
          "target_metric": {
            "$ref": "#/components/schemas/PredictionTargetMetric"
          },
          "period_minutes": {
            "anyOf": [
              {
                "type": "integer"
              },
              {
                "type": "null"
              }
            ],
            "title": "Period Minutes"
          },
          "predicted_value": {
            "anyOf": [
              {
                "type": "number"
              },
              {
                "type": "null"
              }
            ],
            "title": "Predicted Value"
          },
          "status": {
            "$ref": "#/components/schemas/PredictionStatus"
          },
          "failure_reason": {
            "anyOf": [
              {
                "type": "string"
              },
              {
                "type": "null"
              }
            ],
            "title": "Failure Reason"
          },
          "model_reference": {
            "type": "string",
            "title": "Model Reference"
          },
          "created_at": {
            "type": "string",
            "format": "date-time",
            "title": "Created At"
          }
        },
        "type": "object",
        "required": [
          "target_at",
          "target_metric",
          "period_minutes",
          "predicted_value",
          "status",
          "failure_reason",
          "model_reference",
          "created_at"
        ],
        "title": "SitePredictionResponse"
      },
      "SitePredictionSummaryResponse": {
        "properties": {
          "site_id": {
            "type": "string",
            "title": "Site Id"
          },
          "site_name": {
            "type": "string",
            "title": "Site Name"
          },
          "prediction": {
            "anyOf": [
              {
                "$ref": "#/components/schemas/SitePredictionResponse"
              },
              {
                "type": "null"
              }
            ]
          }
        },
        "type": "object",
        "required": [
          "site_id",
          "site_name",
          "prediction"
        ],
        "title": "SitePredictionSummaryResponse"
      },
      "SiteResponse": {
        "properties": {
          "site_id": {
@@ -3260,7 +2960,7 @@
    },
    {
      "name": "recommendations",
-      "description": "Consultation des recommandations issues des alertes. Accessible à partir du rôle `lecteur`. Leur génération par le moteur de règles est réservée au rôle `admin`."
+      "description": "Consultation des recommandations issues des alertes. Accessible à partir du rôle `lecteur`."
    },
    {
      "name": "stats",
@@ -3273,10 +2973,6 @@
    {
      "name": "sensors",
      "description": "État de santé des capteurs par site. Réservé au rôle `admin`."
    },
    {
      "name": "predictions",
      "description": "Dernière prévision de consommation par site, calculée hors ligne par le pipeline de scoring (`ml/`) et simplement lue ici. Accessible à partir du rôle `lecteur`."
    }
  ]
 }
@@ -17,7 +17,6 @@ dependencies = [
    "argon2-cffi>=23.1",
    "anyio>=4.0",
    "aiosmtplib>=5.1.3",
    "httpx>=0.28.1",
    "pandas>=3.0.5",
 ]
@@ -28,6 +27,7 @@ dev = [
    "pytest>=9.1.1",
    "pytest-asyncio>=1.4.0",
    "pytest-cov>=7.1.0",
    "httpx>=0.28.1",
    "pandas-stubs>=3.0.5.260914",
 ]
@@ -1,88 +0,0 @@
 # Pourquoi : classification unique des routes du contrat, lue par test_route_protection.py,
 # test_openapi.py et test_matrice_acces.py. Trois listes séparées dérivaient auparavant chacune
 # de leur côté, et deux entrées de ROUTES_A_ROLE ne correspondaient plus à aucune route sans que
 # rien ne le signale.
 # Piège : les trois ensembles doivent rester disjoints et couvrir tout le schéma. C'est
 # `test_every_declared_route_is_classified` qui le vérifie, pas la relecture.
 from typing import Final
 from app.core.roles import Role
 Route = tuple[str, str]
 ROUTES_PUBLIQUES: Final[frozenset[Route]] = frozenset(
    {
        ("GET", "/api/v1/health/live"),
        ("GET", "/api/v1/health/ready"),
        ("POST", "/api/v1/auth/login"),
        # Sans cookie, la déconnexion ne fait rien et répond 204 : elle est idempotente.
        ("POST", "/api/v1/auth/logout"),
        ("POST", "/api/v1/auth/forgot-password"),
        # Protégée par le jeton dans le corps de la requête, pas par un `Principal` : aucune
        # authentification préalable ne s'applique, c'est la validité du jeton qui tranche.
        ("POST", "/api/v1/auth/reset-password"),
        # Même raison : lecture seule, protégée par le jeton passé en paramètre, pas par un
        # `Principal`. Le jeton est un secret de 256 bits, non brute-forçable.
        ("GET", "/api/v1/auth/reset-password/validate"),
        ("GET", "/metrics"),
    }
 )
 # Le cookie opaque porte seul l'autorisation : sans lui la route rend 401, mais aucun `Principal`
 # n'est construit et `require_role` n'entre jamais en jeu.
 ROUTE_COOKIE: Final[frozenset[Route]] = frozenset({("POST", "/api/v1/auth/refresh")})
 # Authentifiées par `CurrentPrincipalDep` nu, donc hors de `require_role` et, avec lui, hors du
 # refus `password_change_required`. Volontaire pour `/auth/password`, qui est la sortie de l'état
 # provisoire ; subi pour `/auth/logout-all`, cf. test_matrice_acces.py.
 ROUTES_SANS_ROLE: Final[frozenset[Route]] = frozenset(
    {
        ("GET", "/api/v1/auth/me"),
        ("POST", "/api/v1/auth/password"),
        ("POST", "/api/v1/auth/logout-all"),
    }
 )
 ROLE_MINIMUM: Final[dict[Route, Role]] = {
    ("GET", "/api/v1/sites"): Role.LECTEUR,
    ("GET", "/api/v1/sites/{site_id}"): Role.LECTEUR,
    ("GET", "/api/v1/sites/{site_id}/current"): Role.LECTEUR,
    ("GET", "/api/v1/alerts"): Role.LECTEUR,
    ("GET", "/api/v1/recommendations"): Role.LECTEUR,
    ("GET", "/api/v1/recommendations/{recommendation_id}"): Role.LECTEUR,
    ("POST", "/api/v1/recommendations/generate"): Role.ADMIN,
    ("GET", "/api/v1/stats/summary"): Role.LECTEUR,
    ("GET", "/api/v1/readings"): Role.LECTEUR,
    ("GET", "/api/v1/predictions"): Role.LECTEUR,
    ("GET", "/api/v1/sensors/status"): Role.ADMIN,
    ("GET", "/api/v1/users"): Role.ADMIN,
    ("POST", "/api/v1/users"): Role.ADMIN,
    ("PATCH", "/api/v1/users/{user_id}"): Role.ADMIN,
    ("POST", "/api/v1/users/{user_id}/password-reset"): Role.ADMIN,
 }
 # Piège : `{recommendation_id}` est typé `int` et `{user_id}` est un UUID. Une substitution
 # uniforme par une chaîne quelconque rendrait 422 avant d'atteindre la garde de rôle, et le test
 # passerait en prouvant autre chose que ce qu'il annonce.
 SUBSTITUTIONS: Final[dict[str, str]] = {
    "{user_id}": "00000000-0000-0000-0000-000000000000",
    "{site_id}": "site-absent-du-jeu-de-donnees",
    "{recommendation_id}": "999999999",
 }
 def chemin_concret(chemin: str) -> str:
    for gabarit, valeur in SUBSTITUTIONS.items():
        chemin = chemin.replace(gabarit, valeur)
    return chemin
 def routes_du_schema(schema: dict[str, object]) -> list[Route]:
    chemins: dict[str, dict[str, object]] = schema["paths"]  # type: ignore[assignment]
    return [
        (methode.upper(), chemin)
        for chemin, operations in chemins.items()
        for methode in operations
        if methode.upper() in {"GET", "POST", "PATCH", "PUT", "DELETE"}
    ]
@@ -1,279 +0,0 @@
 # Pourquoi : la matrice rôle x route sur les routes réelles. `test_authorization.py` la joue déjà,
 # mais contre une route jetable montée par une fixture, ce qui ne dit rien du niveau effectivement
 # posé sur `/sites` ou `/users`. `ROLE_MINIMUM` (tests/api/acces.py) est la référence, et ce
 # fichier est ce qui la confronte au comportement observé.
 # Piège : l'assertion porte sur le refus de la garde, pas sur un 200. Un rôle suffisant peut
 # légitimement recevoir 404 ou 422 selon les données ; ce qui compte est qu'il ne reçoive pas le
 # 403 `Droits insuffisants`. Sans cette nuance, le test dépendrait du contenu de la base.
 # Les tests `integration` en fin de fichier rejouent la même matrice avec de vrais jetons, donc en
 # traversant le décodage du JWT et la relecture du compte, ce que l'override court-circuite.
 import uuid
 from collections.abc import AsyncIterator, Callable, Iterator
 import pytest
 from fastapi import FastAPI
 from httpx import AsyncClient, Response
 from sqlalchemy import text
 from app.api.deps import get_current_principal
 from app.core.hashing import build_hasher
 from app.core.principal import Principal
 from app.core.roles import AccountKind, Role, has_at_least
 from app.db.session import get_session, get_session_factory
 from app.repositories.user import UserRepository
 from tests.api.acces import ROLE_MINIMUM, chemin_concret
 ROLES = [Role.LECTEUR, Role.OPERATEUR, Role.ADMIN]
 IDS_DE_ROLE = ["lecteur", "operateur", "admin"]
 REFUS_DE_DROITS = "Droits insuffisants"
 REFUS_DE_MOT_DE_PASSE = "password_change_required"
 MOT_DE_PASSE = "un-mot-de-passe-de-recette"
 # `FakeSession` de tests/factories.py rend un unique objet pour les trois formes d'appel, ce qui
 # suffit à un test d'endpoint ciblé mais pas à balayer 13 routes qui interrogent chacune la base
 # à sa façon. Ce double rend un résultat vide quelle que soit la forme demandée, pour que la
 # réponse observée vienne de la garde de rôle et jamais d'un double mal ajusté.
 class ResultatVide:
    def scalars(self) -> ResultatVide:
        return self
    def all(self) -> list[object]:
        return []
    def first(self) -> None:
        return None
    def one_or_none(self) -> None:
        return None
    def scalar_one_or_none(self) -> None:
        return None
    def mappings(self) -> ResultatVide:
        return self
    def __iter__(self) -> Iterator[object]:
        return iter(())
 class SessionMuette:
    async def scalar(self, *_: object, **__: object) -> None:
        return None
    async def execute(self, *_: object, **__: object) -> ResultatVide:
        return ResultatVide()
    async def scalars(self, *_: object, **__: object) -> ResultatVide:
        return ResultatVide()
    async def get(self, *_: object, **__: object) -> None:
        return None
    async def flush(self) -> None:
        return None
    async def commit(self) -> None:
        return None
    async def rollback(self) -> None:
        return None
    def add(self, *_: object, **__: object) -> None:
        return None
@pytest.fixture
 def base_muette(app: FastAPI) -> None:
    async def override() -> AsyncIterator[SessionMuette]:
        yield SessionMuette()
    app.dependency_overrides[get_session] = override
 def principal(role: Role, *, must_change_password: bool = False) -> Principal:
    return Principal(
        id=uuid.uuid4(),
        email=f"matrice-{role.value}@enervision.fr",
        role=role,
        kind=AccountKind.HUMAIN,
        must_change_password=must_change_password,
    )
@pytest.fixture
 def connecte(app: FastAPI) -> Iterator[Callable[[Principal], None]]:
    def installe(acteur: Principal) -> None:
        app.dependency_overrides[get_current_principal] = lambda: acteur
    yield installe
    app.dependency_overrides.pop(get_current_principal, None)
 async def appelle(client: AsyncClient, methode: str, chemin: str, **kwargs: object) -> Response:
    return await client.request(methode, chemin_concret(chemin), json={}, **kwargs)  # type: ignore[arg-type]
 def motif_du_refus(response: Response) -> str | None:
    if response.status_code != 403:
        return None
    detail = response.json().get("detail")
    return detail if isinstance(detail, str) else None
@pytest.mark.parametrize("role", ROLES, ids=IDS_DE_ROLE)
 async def test_a_role_below_the_minimum_is_refused_on_every_guarded_route(
    connecte: Callable[[Principal], None],
    client: AsyncClient,
    base_muette: None,
    role: Role,
 ) -> None:
    connecte(principal(role))
    laissees_passer: list[tuple[str, str, int]] = []
    for (methode, chemin), minimum in ROLE_MINIMUM.items():
        if has_at_least(role, minimum):
            continue
        response = await appelle(client, methode, chemin)
        if motif_du_refus(response) != REFUS_DE_DROITS:
            laissees_passer.append((methode, chemin, response.status_code))
    assert laissees_passer == []
 # Le pendant du test précédent : sans lui, une garde posée trop haut, par exemple `AdminDep` sur
 # `/sites`, ne ferait échouer aucun test du dépôt.
@pytest.mark.parametrize("role", ROLES, ids=IDS_DE_ROLE)
 async def test_a_role_at_or_above_the_minimum_is_never_refused_by_the_guard(
    connecte: Callable[[Principal], None],
    client: AsyncClient,
    base_muette: None,
    role: Role,
 ) -> None:
    connecte(principal(role))
    refusees: list[tuple[str, str]] = []
    for (methode, chemin), minimum in ROLE_MINIMUM.items():
        if not has_at_least(role, minimum):
            continue
        response = await appelle(client, methode, chemin)
        if motif_du_refus(response) == REFUS_DE_DROITS:
            refusees.append((methode, chemin))
    assert refusees == []
 async def test_a_pending_password_change_is_refused_on_every_guarded_route(
    connecte: Callable[[Principal], None],
    client: AsyncClient,
    base_muette: None,
 ) -> None:
    connecte(principal(Role.ADMIN, must_change_password=True))
    laissees_passer: list[tuple[str, str, int]] = []
    for methode, chemin in ROLE_MINIMUM:
        response = await appelle(client, methode, chemin)
        if motif_du_refus(response) != REFUS_DE_MOT_DE_PASSE:
            laissees_passer.append((methode, chemin, response.status_code))
    assert laissees_passer == []
@pytest.fixture
 async def comptes_par_role() -> AsyncIterator[dict[Role, str]]:
    marque = uuid.uuid4().hex[:12]
    hacheur = build_hasher(time_cost=1, memory_cost_kib=8192, parallelism=1, max_concurrency=2)
    empreinte = await hacheur.hash(MOT_DE_PASSE)
    adresses = {role: f"matrice-{marque}-{role.value}@enervision.fr" for role in ROLES}
    async with get_session_factory()() as session:
        depot = UserRepository(session)
        for role, email in adresses.items():
            await depot.create(email=email, password_hash=empreinte, role=role)
        await session.commit()
    yield adresses
    async with get_session_factory()() as session:
        await session.execute(
            text("delete from app_user where email like :motif"), {"motif": f"matrice-{marque}-%"}
        )
        await session.commit()
 async def authentifie(client: AsyncClient, email: str) -> dict[str, str]:
    reponse = await client.post(
        "/api/v1/auth/login", json={"email": email, "password": MOT_DE_PASSE}
    )
    assert reponse.status_code == 200, reponse.text
    return {"Authorization": f"Bearer {reponse.json()['access_token']}"}
@pytest.mark.integration
@pytest.mark.parametrize("role", ROLES, ids=IDS_DE_ROLE)
 async def test_a_real_token_reaches_exactly_the_routes_of_its_rank(
    comptes_par_role: dict[Role, str], client: AsyncClient, role: Role
 ) -> None:
    entetes = await authentifie(client, comptes_par_role[role])
    ecarts: list[tuple[str, str, int, str]] = []
    for (methode, chemin), minimum in ROLE_MINIMUM.items():
        response = await appelle(client, methode, chemin, headers=entetes)
        refuse = motif_du_refus(response) == REFUS_DE_DROITS
        if refuse is has_at_least(role, minimum):
            ecarts.append((methode, chemin, response.status_code, response.text[:120]))
    assert ecarts == []
 # Contrainte : `operateur` n'ouvre aujourd'hui aucune route de plus que `lecteur`, faute d'écriture
 # métier dans l'API. Figer l'égalité rend la régression visible le jour où une route d'opérateur
 # arrive sans que `ROLE_MINIMUM` soit mis à jour.
@pytest.mark.integration
 async def test_the_operator_rank_opens_nothing_more_than_the_reader_rank(
    comptes_par_role: dict[Role, str], client: AsyncClient
 ) -> None:
    lecteur = await authentifie(client, comptes_par_role[Role.LECTEUR])
    operateur = await authentifie(client, comptes_par_role[Role.OPERATEUR])
    divergences: list[tuple[str, str]] = []
    for methode, chemin in ROLE_MINIMUM:
        cote_lecteur = await appelle(client, methode, chemin, headers=lecteur)
        cote_operateur = await appelle(client, methode, chemin, headers=operateur)
        if cote_lecteur.status_code != cote_operateur.status_code:
            divergences.append((methode, chemin))
    assert divergences == []
 # Piège : `/auth/logout-all` prend un `CurrentPrincipalDep` nu, donc elle échappe au gate
 # `must_change_password` que seul `require_role` applique. Comportement figé ici, pas corrigé.
@pytest.mark.integration
 async def test_a_temporary_password_blocks_the_business_routes_but_not_logout_all(
    client: AsyncClient,
 ) -> None:
    marque = uuid.uuid4().hex[:12]
    email = f"matrice-{marque}-provisoire@enervision.fr"
    hacheur = build_hasher(time_cost=1, memory_cost_kib=8192, parallelism=1, max_concurrency=2)
    empreinte = await hacheur.hash(MOT_DE_PASSE)
    async with get_session_factory()() as session:
        await UserRepository(session).create(
            email=email, password_hash=empreinte, role=Role.ADMIN, must_change_password=True
        )
        await session.commit()
    try:
        entetes = await authentifie(client, email)
        sites = await client.get("/api/v1/sites", headers=entetes)
        identite = await client.get("/api/v1/auth/me", headers=entetes)
        fermeture = await client.post("/api/v1/auth/logout-all", headers=entetes)
        assert motif_du_refus(sites) == REFUS_DE_MOT_DE_PASSE
        assert identite.status_code == 200
        assert fermeture.status_code == 204
    finally:
        async with get_session_factory()() as session:
            await session.execute(text("delete from app_user where email = :e"), {"e": email})
            await session.commit()
@@ -8,7 +8,6 @@ from typing import Any
 import pytest
 from app import cli
 from tests.api.acces import ROLE_MINIMUM
 METHODES = {"get", "post", "patch", "put", "delete"}
@@ -25,11 +24,21 @@ ORIGINE_VERIFIEE = {
 # Toute route derrière `require_role` (LecteurDep, OperateurDep, AdminDep) peut rendre 403 pour
 # `password_change_required`, pas seulement les routes `admin`.
-# Piège : cette liste était recopiée ici, et deux de ses entrées portaient `{id}` là où le contrat
+ROUTES_A_ROLE = {
-# expose `{user_id}`. Elles ne correspondaient donc à aucune opération, et le test ci-dessous
+    ("GET", "/api/v1/users"),
-# passait au vert sans rien vérifier sur ces deux routes. Elle est maintenant dérivée, et
+    ("POST", "/api/v1/users"),
-# `test_every_declared_route_is_classified` interdit l'entrée morte.
+    ("PATCH", "/api/v1/users/{id}"),
-ROUTES_A_ROLE = frozenset(ROLE_MINIMUM)
+    ("POST", "/api/v1/users/{id}/password-reset"),
    ("GET", "/api/v1/sites"),
    ("GET", "/api/v1/sites/{site_id}"),
    ("GET", "/api/v1/sites/{site_id}/current"),
    ("GET", "/api/v1/alerts"),
    ("GET", "/api/v1/recommendations"),
    ("GET", "/api/v1/recommendations/{recommendation_id}"),
    ("GET", "/api/v1/stats/summary"),
    ("GET", "/api/v1/readings"),
    ("GET", "/api/v1/sensors/status"),
 }
@pytest.fixture(scope="module")
@@ -1,85 +0,0 @@
 from collections.abc import Callable, Iterator
 from datetime import UTC, datetime
 from uuid import uuid4
 import pytest
 from fastapi import FastAPI
 from httpx import AsyncClient
 from app.api.deps import get_current_principal, get_prediction_service
 from app.core.principal import Principal
 from app.core.roles import AccountKind, Role
 from app.services.prediction import PredictionSummary, SitePrediction, SitePredictionSummary
 TARGET_AT = datetime(2026, 9, 16, 13, 0, tzinfo=UTC)
 CREATED_AT = datetime(2026, 9, 16, 12, 0, tzinfo=UTC)
 def lecteur() -> Principal:
    # Le garde-fou de rôle (`lecteur` minimum) est déjà couvert par l'ensemble `ROUTES_A_ROLE`
    # de `tests/api/test_openapi.py` : pas besoin ici d'un paramètre de rôle jamais appelé avec
    # autre chose que sa valeur par défaut.
    return Principal(
        id=uuid4(),
        email="lecteur@enervision.fr",
        role=Role.LECTEUR,
        kind=AccountKind.HUMAIN,
        must_change_password=False,
    )
 class FauxService:
    def __init__(self) -> None:
        self.resume = PredictionSummary(
            timestamp=datetime.now(UTC),
            sites=[
                SitePredictionSummary(
                    site_id="SITE001",
                    site_name="Bureau Paris La Défense",
                    prediction=SitePrediction(
                        target_at=TARGET_AT,
                        target_metric="consumption_kwh",
                        period_minutes=60,
                        predicted_value=812.5,
                        status="available",
                        failure_reason=None,
                        model_reference="lightgbm-abc123",
                        created_at=CREATED_AT,
                    ),
                ),
                SitePredictionSummary(site_id="SITE002", site_name="Usine Lyon", prediction=None),
            ],
        )
    async def summary(self) -> PredictionSummary:
        return self.resume
@pytest.fixture
 def servi(app: FastAPI) -> Iterator[Callable[[], FauxService]]:
    def installe() -> FauxService:
        service = FauxService()
        app.dependency_overrides[get_prediction_service] = lambda: service
        app.dependency_overrides[get_current_principal] = lambda: lecteur()
        return service
    yield installe
    app.dependency_overrides.pop(get_prediction_service, None)
    app.dependency_overrides.pop(get_current_principal, None)
 async def test_get_predictions_returns_the_service_result(
    servi: Callable[[], FauxService], client: AsyncClient
 ) -> None:
    servi()
    response = await client.get("/api/v1/predictions")
    assert response.status_code == 200
    corps = response.json()
    premier, second = corps["sites"]
    assert premier["site_id"] == "SITE001"
    assert premier["prediction"]["predicted_value"] == 812.5
    assert premier["prediction"]["status"] == "available"
    assert second["site_id"] == "SITE002"
    assert second["prediction"] is None
@@ -10,7 +10,7 @@ from app.api.deps import get_current_principal, get_recommendation_service
 from app.core.principal import Principal
 from app.core.roles import AccountKind, Role
 from app.models.energy import Recommendation
-from app.services.recommendation import RapportGeneration, RecommendationNotFoundError
+from app.services.recommendation import RecommendationNotFoundError
 MOMENT = datetime(2024, 1, 1, tzinfo=UTC)
@@ -40,7 +40,6 @@ class FauxService:
    def __init__(self, erreur: Exception | None = None) -> None:
        self._erreur = erreur
        self.recommendation = recommendation()
        self.site_demande: str | None = None
    async def list_all(self) -> list[Recommendation]:
        return [self.recommendation]
@@ -50,10 +49,6 @@ class FauxService:
            raise self._erreur
        return self.recommendation
    async def generate(self, *, site_id: str | None = None) -> RapportGeneration:
        self.site_demande = site_id
        return RapportGeneration(alertes_examinees=2, recommandations_creees=3, deja_presentes=1)
@pytest.fixture
 def lecteur_connecte(app: FastAPI) -> Iterator[None]:
@@ -147,56 +142,3 @@ async def test_get_recommendation_returns_404_when_the_session_finds_nothing(
    response = await client.get("/api/v1/recommendations/404")
    assert response.status_code == 404
@pytest.fixture
 def admin_connecte(app: FastAPI) -> Iterator[None]:
    app.dependency_overrides[get_current_principal] = lambda: principal(Role.ADMIN)
    yield
    app.dependency_overrides.pop(get_current_principal, None)
@pytest.fixture
 def servi_en_admin(app: FastAPI, admin_connecte: None) -> Iterator[Callable[[], FauxService]]:
    def installe() -> FauxService:
        service = FauxService()
        app.dependency_overrides[get_recommendation_service] = lambda: service
        return service
    yield installe
    app.dependency_overrides.pop(get_recommendation_service, None)
 async def test_generate_recommendations_returns_the_generation_report(
    servi_en_admin: Callable[[], FauxService], client: AsyncClient
 ) -> None:
    servi_en_admin()
    response = await client.post("/api/v1/recommendations/generate")
    assert response.status_code == 200
    assert response.json() == {
        "alerts_examined": 2,
        "recommendations_created": 3,
        "already_present": 1,
    }
 async def test_generate_recommendations_forwards_the_requested_site(
    servi_en_admin: Callable[[], FauxService], client: AsyncClient
 ) -> None:
    service = servi_en_admin()
    await client.post("/api/v1/recommendations/generate", params={"site_id": "SITE002"})
    assert service.site_demande == "SITE002"
 async def test_generate_recommendations_refuses_a_reader(
    servi: Callable[..., FauxService], client: AsyncClient
 ) -> None:
    servi()
    response = await client.post("/api/v1/recommendations/generate")
    assert response.status_code == 403
@@ -1,6 +1,6 @@
 # Ce test est le garde-fou de l'autorisation : rendre une route publique oblige à modifier
-# `ROUTES_PUBLIQUES` dans `tests/api/acces.py`, ce qui apparaît en clair dans la diff d'une pull
+# `ROUTES_PUBLIQUES` ci-dessous, ce qui apparaît en clair dans la diff d'une pull request et
-# request et demande une justification au relecteur.
+# demande une justification au relecteur.
 # Pourquoi : il interroge réellement chaque route sans jeton au lieu d'inspecter l'arbre de
 # dépendances. L'arbre n'est accessible que par l'API privée de FastAPI, et surtout une route
 # peut porter la bonne dépendance tout en répondant quand même.
@@ -11,64 +11,58 @@ import pytest
 from fastapi import FastAPI
 from httpx import AsyncClient
-from tests.api.acces import (
+ROUTES_PUBLIQUES = frozenset(
-    ROLE_MINIMUM,
+    {
-    ROUTE_COOKIE,
+        ("GET", "/api/v1/health/live"),
-    ROUTES_PUBLIQUES,
+        ("GET", "/api/v1/health/ready"),
-    ROUTES_SANS_ROLE,
+        ("POST", "/api/v1/auth/login"),
-    Route,
+        # Sans cookie, la déconnexion ne fait rien et répond 204 : elle est idempotente.
-    chemin_concret,
+        ("POST", "/api/v1/auth/logout"),
-    routes_du_schema,
+        ("POST", "/api/v1/auth/forgot-password"),
        # Protégée par le jeton dans le corps de la requête, pas par un `Principal` : aucune
        # authentification préalable ne s'applique, c'est la validité du jeton qui tranche.
        ("POST", "/api/v1/auth/reset-password"),
        # Même raison : lecture seule, protégée par le jeton passé en paramètre, pas par un
        # `Principal`. Le jeton est un secret de 256 bits, non brute-forçable.
        ("GET", "/api/v1/auth/reset-password/validate"),
        ("GET", "/metrics"),
    }
 )
 VALEURS_DE_SUBSTITUTION = "00000000-0000-0000-0000-000000000000"
 STATUTS_DE_REFUS = {401, 403}
 HORS_SCHEMA = {("GET", "/metrics")}
-def routes_declarees(app: FastAPI) -> list[Route]:
+def routes_declarees(app: FastAPI) -> list[tuple[str, str]]:
    schema: dict[str, Any] = app.openapi()
-    return routes_du_schema(schema)
+    return [
        (methode.upper(), chemin)
        for chemin, operations in schema["paths"].items()
        for methode in operations
        if methode.upper() in {"GET", "POST", "PATCH", "PUT", "DELETE"}
    ]
-def routes_protegees(app: FastAPI) -> list[Route]:
+def routes_protegees(app: FastAPI) -> list[tuple[str, str]]:
    return [route for route in routes_declarees(app) if route not in ROUTES_PUBLIQUES]
 def test_the_public_allow_list_has_no_stale_entry(app: FastAPI) -> None:
-    declarees = set(routes_declarees(app)) | HORS_SCHEMA
+    declarees = set(routes_declarees(app)) | {("GET", "/metrics")}
    inconnues = ROUTES_PUBLIQUES - declarees
    assert inconnues == set()
 # Sans lui, une route ajoutée sans être classée n'est vue par aucun test de rôle : elle hérite
 # du seul contrôle anonyme, et une garde posée au mauvais niveau passe inaperçue.
 def test_every_declared_route_is_classified(app: FastAPI) -> None:
    classees = ROUTES_PUBLIQUES | ROUTE_COOKIE | ROUTES_SANS_ROLE | set(ROLE_MINIMUM)
    non_classees = set(routes_declarees(app)) - classees
    fantomes = classees - set(routes_declarees(app)) - HORS_SCHEMA
    assert non_classees == set(), "classer la route dans tests/api/acces.py"
    assert fantomes == set(), "entrée morte : la route n'existe plus sous ce chemin"
 def test_the_four_classes_of_routes_stay_disjoint() -> None:
    classes = [ROUTES_PUBLIQUES, ROUTE_COOKIE, ROUTES_SANS_ROLE, frozenset(ROLE_MINIMUM)]
    for rang, classe in enumerate(classes):
        for autre in classes[rang + 1 :]:
            assert classe & autre == frozenset()
 async def test_every_route_rejects_an_anonymous_caller_unless_explicitly_public(
    app: FastAPI, client: AsyncClient
 ) -> None:
    ouvertes: list[tuple[str, str, int]] = []
    for methode, chemin in routes_protegees(app):
-        response = await client.request(methode, chemin_concret(chemin), json={})
+        concret = chemin.replace("{user_id}", VALEURS_DE_SUBSTITUTION)
        response = await client.request(methode, concret, json={})
        if response.status_code not in STATUTS_DE_REFUS:
            ouvertes.append((methode, chemin, response.status_code))
@@ -101,5 +95,4 @@ async def test_the_documentation_routes_are_public_by_design(
    app: FastAPI, client: AsyncClient, chemin: str
 ) -> None:
    response = await client.get(chemin)
    assert response.status_code == 200
@@ -112,10 +112,8 @@ async def test_duplicate_reading_is_rejected_when_key_matches(
    )
    await data_connection.execute(statement)
    savepoint = data_connection.begin_nested()
    with pytest.raises(IntegrityError):
-        async with savepoint:
+        async with data_connection.begin_nested():
            await data_connection.execute(statement)
@@ -149,12 +147,9 @@ async def test_invalid_reading_is_rejected_when_constraints_fail(
    }
    values.update(changes)
    statement = insert(Reading).values(**values)
    savepoint = data_connection.begin_nested()
    with pytest.raises(IntegrityError):
-        async with savepoint:
+        async with data_connection.begin_nested():
-            await data_connection.execute(statement)
+            await data_connection.execute(insert(Reading).values(**values))
 async def test_prediction_requires_period_when_energy_is_predicted(
@@ -169,10 +164,8 @@ async def test_prediction_requires_period_when_energy_is_predicted(
        model_reference="test-model/1",
    )
    savepoint = data_connection.begin_nested()
    with pytest.raises(IntegrityError):
-        async with savepoint:
+        async with data_connection.begin_nested():
            await data_connection.execute(statement)
@@ -219,22 +212,21 @@ async def test_alert_rejects_prediction_when_site_differs(
        )
    ).scalar_one()
    statement = insert(Alert).values(
        source_alert_id=str(uuid4()),
        site_id=other_site,
        source="enervision",
        timestamp=MOMENT,
        type="spike",
        severity="high",
        message="Test",
        prediction_id=prediction_id,
        raw_data={},
    )
    savepoint = data_connection.begin_nested()
    with pytest.raises(IntegrityError):
-        async with savepoint:
+        async with data_connection.begin_nested():
-            await data_connection.execute(statement)
+            await data_connection.execute(
                insert(Alert).values(
                    source_alert_id=str(uuid4()),
                    site_id=other_site,
                    source="enervision",
                    timestamp=MOMENT,
                    type="spike",
                    severity="high",
                    message="Test",
                    prediction_id=prediction_id,
                    raw_data={},
                )
            )
 async def test_recommendation_is_unique_when_alert_and_rule_match(
@@ -264,8 +256,6 @@ async def test_recommendation_is_unique_when_alert_and_rule_match(
    )
    await data_connection.execute(statement)
    savepoint = data_connection.begin_nested()
    with pytest.raises(IntegrityError):
-        async with savepoint:
+        async with data_connection.begin_nested():
            await data_connection.execute(statement)
@@ -1,245 +1,239 @@
-import hashlib
+import hashlib
-import json
+import json
-
+
-import pandas as pd
+import pandas as pd
-import pytest
+import pytest
-
+
-from app.etl.historical_import import (
+from app.etl.historical_import import (
-    SOURCE_NAME,
+    SOURCE_NAME,
-    build_reading_batch,
+    build_reading_batch,
-    classify_quality,
+    classify_quality,
-    compute_sha256,
+    compute_sha256,
-    load_metadata,
+    load_metadata,
-    normalize_timestamps,
+    normalize_timestamps,
-    validate_source,
+    validate_source,
-)
+)
-
+
-
+
-def make_metadata() -> dict:
+def make_metadata() -> dict:
-    return {
+    return {
-        "total_records": 2,
+        "total_records": 2,
-        "sites": {
+        "sites": {
-            "SITE001": {},
+            "SITE001": {},
-        },
+        },
-    }
+    }
-
+
-
+
-def make_dataframe() -> pd.DataFrame:
+def make_dataframe() -> pd.DataFrame:
-    return pd.DataFrame(
+    return pd.DataFrame(
-        [
+        [
-            {
+            {
-                "timestamp": "2023-01-01 00:00:00",
+                "timestamp": "2023-01-01 00:00:00",
-                "site_id": "SITE001",
+                "site_id": "SITE001",
-                "site_type": "office",
+                "site_type": "office",
-                "site_name": "Site 1",
+                "site_name": "Site 1",
-                "consumption_kwh": 10.5,
+                "consumption_kwh": 10.5,
-                "consumption_euros": 2.5,
+                "consumption_euros": 2.5,
-                "temperature_celsius": 20.0,
+                "temperature_celsius": 20.0,
-                "humidity_percent": 50.0,
+                "humidity_percent": 50.0,
-                "solar_irradiance_wm2": 0.0,
+                "solar_irradiance_wm2": 0.0,
-                "hour": 0,
+                "hour": 0,
-                "day_of_week": 6,
+                "day_of_week": 6,
-                "day_name": "Sunday",
+                "day_name": "Sunday",
-                "month": 1,
+                "month": 1,
-                "is_weekend": True,
+                "is_weekend": True,
-                "is_working_hours": False,
+                "is_working_hours": False,
-            },
+            },
-            {
+            {
-                "timestamp": "2023-01-01 01:00:00",
+                "timestamp": "2023-01-01 01:00:00",
-                "site_id": "SITE001",
+                "site_id": "SITE001",
-                "site_type": "office",
+                "site_type": "office",
-                "site_name": "Site 1",
+                "site_name": "Site 1",
-                "consumption_kwh": 11.0,
+                "consumption_kwh": 11.0,
-                "consumption_euros": 2.7,
+                "consumption_euros": 2.7,
-                "temperature_celsius": 19.5,
+                "temperature_celsius": 19.5,
-                "humidity_percent": 52.0,
+                "humidity_percent": 52.0,
-                "solar_irradiance_wm2": 0.0,
+                "solar_irradiance_wm2": 0.0,
-                "hour": 1,
+                "hour": 1,
-                "day_of_week": 6,
+                "day_of_week": 6,
-                "day_name": "Sunday",
+                "day_name": "Sunday",
-                "month": 1,
+                "month": 1,
-                "is_weekend": True,
+                "is_weekend": True,
-                "is_working_hours": False,
+                "is_working_hours": False,
-            },
+            },
-        ]
+        ]
-    )
+    )
-
+
-
+
-def test_compute_sha256(tmp_path):
+def test_compute_sha256(tmp_path):
-    file_path = tmp_path / "dataset.csv"
+    file_path = tmp_path / "dataset.csv"
-    content = b"hello-enervision"
+    content = b"hello-enervision"
-
+
-    file_path.write_bytes(content)
+    file_path.write_bytes(content)
-
+
-    expected = hashlib.sha256(content).hexdigest()
+    expected = hashlib.sha256(content).hexdigest()
-
+
-    assert compute_sha256(file_path) == expected
+    assert compute_sha256(file_path) == expected
-
+
-
+
-def test_load_metadata(tmp_path):
+def test_load_metadata(tmp_path):
-    metadata_path = tmp_path / "metadata.json"
+    metadata_path = tmp_path / "metadata.json"
-
+
-    metadata = {
+    metadata = {
-        "total_records": 2,
+        "total_records": 2,
-        "sites": {
+        "sites": {
-            "SITE001": {},
+            "SITE001": {},
-        },
+        },
-    }
+    }
-
+
-    metadata_path.write_text(
+    metadata_path.write_text(
-        json.dumps(metadata),
+        json.dumps(metadata),
-        encoding="utf-8",
+        encoding="utf-8",
-    )
+    )
-
+
-    assert load_metadata(metadata_path) == metadata
+    assert load_metadata(metadata_path) == metadata
-
+
-
+
-def test_validate_source_accepts_valid_dataset():
+def test_validate_source_accepts_valid_dataset():
-    frame = make_dataframe()
+    frame = make_dataframe()
-
+
-    validate_source(
+    validate_source(
-        frame,
+        frame,
-        make_metadata(),
+        make_metadata(),
-    )
+    )
-
+
-
+
-def test_validate_source_rejects_missing_column():
+def test_validate_source_rejects_missing_column():
-    frame = make_dataframe().drop(columns=["consumption_kwh"])
+    frame = make_dataframe().drop(columns=["consumption_kwh"])
-
+
-    metadata = make_metadata()
+    with pytest.raises(
-
+        ValueError,
-    with pytest.raises(
+        match="Colonnes obligatoires absentes",
-        ValueError,
+    ):
-        match="Colonnes obligatoires absentes",
+        validate_source(
-    ):
+            frame,
-        validate_source(
+            make_metadata(),
-            frame,
+        )
-            metadata,
+
-        )
+
-
+def test_validate_source_rejects_duplicates():
-
+    frame = make_dataframe()
-def test_validate_source_rejects_duplicates():
+
-    frame = make_dataframe()
+    frame.loc[1, "timestamp"] = frame.loc[
-
+        0,
-    frame.loc[1, "timestamp"] = frame.loc[
+        "timestamp",
-        0,
+    ]
-        "timestamp",
+
-    ]
+    with pytest.raises(
-
+        ValueError,
-    metadata = make_metadata()
+        match="doublons",
-
+    ):
-    with pytest.raises(
+        validate_source(
-        ValueError,
+            frame,
-        match="doublons",
+            make_metadata(),
-    ):
+        )
-        validate_source(
+
-            frame,
+
-            metadata,
+def test_validate_source_rejects_unknown_site():
-        )
+    frame = make_dataframe()
-
+
-
+    frame.loc[1, "site_id"] = "SITE999"
-def test_validate_source_rejects_unknown_site():
+
-    frame = make_dataframe()
+    with pytest.raises(
-
+        ValueError,
-    frame.loc[1, "site_id"] = "SITE999"
+        match="Sites incohérents",
-
+    ):
-    metadata = make_metadata()
+        validate_source(
-
+            frame,
-    with pytest.raises(
+            make_metadata(),
-        ValueError,
+        )
-        match="Sites incohérents",
+
-    ):
+
-        validate_source(
+def test_normalize_timestamps_adds_timezone():
-            frame,
+    frame = make_dataframe()
-            metadata,
+
-        )
+    normalized = normalize_timestamps(
-
+        frame,
-
+        "UTC",
-def test_normalize_timestamps_adds_timezone():
+    )
-    frame = make_dataframe()
+
-
+    assert normalized["timestamp"].dt.tz is not None
-    normalized = normalize_timestamps(
+
-        frame,
+    assert "_source_timestamp" in normalized.columns
-        "UTC",
+
-    )
+
-
+def test_classify_quality_good():
-    assert normalized["timestamp"].dt.tz is not None
+    row = make_dataframe().iloc[0].to_dict()
-
+
-    assert "_source_timestamp" in normalized.columns
+    quality, reasons = classify_quality(row)
-
+
-
+    assert quality == "good"
-def test_classify_quality_good():
+    assert reasons == []
-    row = make_dataframe().iloc[0].to_dict()
+
-
+
-    quality, reasons = classify_quality(row)
+def test_classify_quality_degraded_when_consumption_missing():
-
+    row = make_dataframe().iloc[0].to_dict()
-    assert quality == "good"
+    row["consumption_kwh"] = None
-    assert reasons == []
+
-
+    quality, reasons = classify_quality(row)
-
+
-def test_classify_quality_degraded_when_consumption_missing():
+    assert quality == "degraded"
-    row = make_dataframe().iloc[0].to_dict()
+
-    row["consumption_kwh"] = None
+    assert "missing:consumption_kwh" in reasons
-
+
-    quality, reasons = classify_quality(row)
+
-
+def test_build_reading_batch_respects_database_contract():
-    assert quality == "degraded"
+    frame = normalize_timestamps(
-
+        make_dataframe(),
-    assert "missing:consumption_kwh" in reasons
+        "UTC",
-
+    )
-
+
-def test_build_reading_batch_respects_database_contract():
+    rows = build_reading_batch(
-    frame = normalize_timestamps(
+        frame.iloc[:1],
-        make_dataframe(),
+        dataset_id=3,
-        "UTC",
+    )
-    )
+
-
+    assert len(rows) == 1
-    rows = build_reading_batch(
+
-        frame.iloc[:1],
+    row = rows[0]
-        dataset_id=3,
+
-    )
+    assert row["dataset_id"] == 3
-
+
-    assert len(rows) == 1
+    # Important :
-
+    # contrainte ck_reading_dataset_source.
-    row = rows[0]
+    assert row["source"] == "csv"
-
+    assert SOURCE_NAME == "csv"
-    assert row["dataset_id"] == 3
+
-
+    # Important :
-    # Important :
+    # contrainte ck_reading_imputation.
-    # contrainte ck_reading_dataset_source.
+    assert row["imputed_values"] is None
-    assert row["source"] == "csv"
+    assert row["imputation_method"] is None
-    assert SOURCE_NAME == "csv"
+
-
+    assert row["data_quality"] == "good"
-    # Important :
+    assert row["null_reasons"] == []
-    # contrainte ck_reading_imputation.
+
-    assert row["imputed_values"] is None
+
-    assert row["imputation_method"] is None
+def test_build_reading_batch_keeps_missing_values():
-
+    frame = make_dataframe()
-    assert row["data_quality"] == "good"
+
-    assert row["null_reasons"] == []
+    frame.loc[0, "temperature_celsius"] = None
-
+
-
+    frame = normalize_timestamps(
-def test_build_reading_batch_keeps_missing_values():
+        frame,
-    frame = make_dataframe()
+        "UTC",
-
+    )
-    frame.loc[0, "temperature_celsius"] = None
+
-
+    rows = build_reading_batch(
-    frame = normalize_timestamps(
+        frame.iloc[:1],
-        frame,
+        dataset_id=3,
-        "UTC",
+    )
-    )
+
-
+    row = rows[0]
-    rows = build_reading_batch(
+
-        frame.iloc[:1],
+    assert row["temperature_celsius"] is None
-        dataset_id=3,
+
-    )
+    assert "missing:temperature_celsius" in row["null_reasons"]
-
+
-    row = rows[0]
+    # RAW ingestion : aucune imputation.
-
+    assert row["imputed_values"] is None
-    assert row["temperature_celsius"] is None
+    assert row["imputation_method"] is None
    assert "missing:temperature_celsius" in row["null_reasons"]
    # RAW ingestion : aucune imputation.
    assert row["imputed_values"] is None
    assert row["imputation_method"] is None
@@ -1,834 +0,0 @@
 import json
 import sys
 from datetime import datetime
 from types import SimpleNamespace
 from typing import Any
 from unittest.mock import AsyncMock, MagicMock
 import httpx
 import pytest
 from httpx import AsyncClient, MockTransport, Request, Response
 from sqlalchemy import text
 from sqlalchemy.ext.asyncio import AsyncSession
 import app.etl.mock_api_import as mock_api_import
 from app.etl.mock_api_import import (
    MAX_SITES,
    READING_INSERT,
    SOURCE_HISTORY,
    build_reading_batch,
    build_reading_row,
    build_site_row,
    fetch_readings,
    fetch_sites,
    upsert_sites,
 )
 def make_site() -> dict[str, Any]:
    return {
        "site_id": "SITE001",
        "site_type": "office",
        "site_name": "Bureau Paris La Défense",
        "location": "Paris, France",
        "capacity_kw": 200,
        "status": "active",
    }
 def make_reading() -> dict[str, Any]:
    return {
        "timestamp": "2024-06-15T12:00:00Z",
        "site_id": "SITE001",
        "site_type": "office",
        "consumption_kw": 87.34,
        "consumption_kwh": 87.34,
        "voltage_v": 401.2,
        "current_a": 132.5,
        "power_factor": 0.923,
        "temperature_celsius": 22.1,
        "humidity_percent": 58.4,
        "null_reasons": [],
        "data_quality": "good",
    }
 async def test_fetch_sites_returns_sites() -> None:
    def handler(request: Request) -> Response:
        assert request.url.path == "/api/v1/sites"
        return Response(
            status_code=200,
            json=[make_site()],
        )
    transport = MockTransport(handler)
    async with AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    ) as client:
        sites = await fetch_sites(client)
    assert len(sites) == 1
    assert sites[0]["site_id"] == "SITE001"
    assert sites[0]["site_type"] == "office"
 async def test_fetch_sites_rejects_non_list_response() -> None:
    def handler(request: Request) -> Response:
        return Response(
            status_code=200,
            json={"unexpected": "payload"},
        )
    transport = MockTransport(handler)
    async with AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    ) as client:
        with pytest.raises(
            ValueError,
            match="La réponse /api/v1/sites doit être une liste",
        ):
            await fetch_sites(client)
 async def test_fetch_readings_sends_expected_query_parameters() -> None:
    captured_params: dict[str, str] = {}
    def handler(request: Request) -> Response:
        nonlocal captured_params
        captured_params = dict(request.url.params)
        return Response(
            status_code=200,
            json=[make_reading()],
        )
    transport = MockTransport(handler)
    start_time = datetime.fromisoformat("2024-06-15T12:00:00")
    end_time = datetime.fromisoformat("2024-06-15T13:00:00")
    async with AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    ) as client:
        readings = await fetch_readings(
            client=client,
            site_id="SITE001",
            start_time=start_time,
            end_time=end_time,
            limit=60,
        )
    assert len(readings) == 1
    assert captured_params["site_id"] == "SITE001"
    assert captured_params["start_time"] == "2024-06-15T12:00:00"
    assert captured_params["end_time"] == "2024-06-15T13:00:00"
    assert captured_params["limit"] == "60"
 async def test_fetch_readings_rejects_non_list_response() -> None:
    def handler(request: Request) -> Response:
        return Response(
            status_code=200,
            json={"unexpected": "payload"},
        )
    transport = MockTransport(handler)
    async with AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    ) as client:
        with pytest.raises(
            ValueError,
            match="La réponse /api/v1/readings doit être une liste",
        ):
            await fetch_readings(
                client=client,
                site_id="SITE001",
                start_time=datetime.fromisoformat("2024-06-15T12:00:00"),
                end_time=datetime.fromisoformat("2024-06-15T13:00:00"),
                limit=60,
            )
 async def test_fetch_readings_raises_on_http_error() -> None:
    def handler(request: Request) -> Response:
        return Response(
            status_code=404,
            json={"detail": "Site non trouvé"},
        )
    transport = MockTransport(handler)
    async with AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    ) as client:
        with pytest.raises(httpx.HTTPStatusError):
            await fetch_readings(
                client=client,
                site_id="SITE999",
                start_time=datetime.fromisoformat("2024-06-15T12:00:00"),
                end_time=datetime.fromisoformat("2024-06-15T13:00:00"),
                limit=60,
            )
 def test_build_reading_row_respects_database_contract() -> None:
    reading = make_reading()
    row = build_reading_row(reading)
    assert row["site_id"] == "SITE001"
    assert row["source"] == SOURCE_HISTORY
    assert row["source"] == "api_history"
    assert row["dataset_id"] is None
    assert row["timestamp"] == datetime.fromisoformat("2024-06-15T12:00:00+00:00")
    assert row["consumption_kw"] == 87.34
    assert row["consumption_kwh"] == 87.34
    assert row["data_quality"] == "good"
    assert row["null_reasons"] == []
    assert row["imputed_values"] is None
    assert row["imputation_method"] is None
 def test_build_reading_row_keeps_null_values_and_quality() -> None:
    reading = make_reading()
    reading["consumption_kw"] = None
    reading["consumption_kwh"] = None
    reading["voltage_v"] = None
    reading["current_a"] = None
    reading["power_factor"] = None
    reading["data_quality"] = "degraded"
    reading["null_reasons"] = [
        "consumption_sensor_failure",
        "electrical_sensor_failure",
    ]
    row = build_reading_row(reading)
    assert row["consumption_kw"] is None
    assert row["consumption_kwh"] is None
    assert row["voltage_v"] is None
    assert row["current_a"] is None
    assert row["power_factor"] is None
    assert row["data_quality"] == "degraded"
    assert row["null_reasons"] == [
        "consumption_sensor_failure",
        "electrical_sensor_failure",
    ]
    assert row["imputed_values"] is None
    assert row["imputation_method"] is None
 def test_build_reading_row_keeps_raw_source_data() -> None:
    reading = make_reading()
    row = build_reading_row(reading)
    raw_data = json.loads(row["raw_data"])
    assert raw_data == reading
 def test_build_reading_batch_transforms_all_readings() -> None:
    first = make_reading()
    second = make_reading()
    second["timestamp"] = "2024-06-15T12:01:00Z"
    second["consumption_kw"] = 90.5
    rows = build_reading_batch([first, second])
    assert len(rows) == 2
    assert rows[0]["site_id"] == "SITE001"
    assert rows[0]["consumption_kw"] == 87.34
    assert rows[1]["site_id"] == "SITE001"
    assert rows[1]["consumption_kw"] == 90.5
 def test_create_mock_api_client_requires_credentials(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    settings = SimpleNamespace(
        mock_api_username=None,
        mock_api_password=None,
    )
    monkeypatch.setattr(
        mock_api_import,
        "get_settings",
        lambda: settings,
    )
    with pytest.raises(
        ValueError,
        match="Les identifiants de l'API Mock ne sont pas configurés",
    ):
        mock_api_import.create_mock_api_client()
 async def test_create_mock_api_client_uses_configuration(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    password = MagicMock()
    password.get_secret_value.return_value = "test-password"
    settings = SimpleNamespace(
        mock_api_base_url="https://mock.test/",
        mock_api_username="test-user",
        mock_api_password=password,
        mock_api_timeout_seconds=10.0,
    )
    monkeypatch.setattr(
        mock_api_import,
        "get_settings",
        lambda: settings,
    )
    client = mock_api_import.create_mock_api_client()
    try:
        assert str(client.base_url) == "https://mock.test"
        assert client.timeout.connect == 10.0
    finally:
        await client.aclose()
 async def test_upsert_sites_with_empty_list_does_nothing() -> None:
    connection = AsyncMock()
    await upsert_sites(
        connection,
        [],
    )
    connection.execute.assert_not_awaited()
 async def test_import_mock_api_history_dry_run_does_not_write(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    def handler(request: Request) -> Response:
        if request.url.path == "/api/v1/sites":
            return Response(
                status_code=200,
                json=[make_site()],
            )
        if request.url.path == "/api/v1/readings":
            return Response(
                status_code=200,
                json=[make_reading()],
            )
        return Response(status_code=404)
    transport = MockTransport(handler)
    client = AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    )
    monkeypatch.setattr(
        mock_api_import,
        "create_mock_api_client",
        lambda: client,
    )
    monkeypatch.setattr(
        mock_api_import,
        "get_settings",
        lambda: SimpleNamespace(
            database_url="postgresql+asyncpg://unused",
        ),
    )
    create_engine_mock = MagicMock()
    monkeypatch.setattr(
        mock_api_import,
        "create_async_engine",
        create_engine_mock,
    )
    await mock_api_import.import_mock_api_history(
        start_time=datetime.fromisoformat("2024-06-15T12:00:00"),
        end_time=datetime.fromisoformat("2024-06-15T13:00:00"),
        limit=60,
        dry_run=True,
    )
    create_engine_mock.assert_not_called()
 async def test_import_mock_api_history_loads_data(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    def handler(request: Request) -> Response:
        if request.url.path == "/api/v1/sites":
            return Response(
                status_code=200,
                json=[make_site()],
            )
        if request.url.path == "/api/v1/readings":
            return Response(
                status_code=200,
                json=[make_reading()],
            )
        return Response(status_code=404)
    transport = MockTransport(handler)
    client = AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    )
    monkeypatch.setattr(
        mock_api_import,
        "create_mock_api_client",
        lambda: client,
    )
    monkeypatch.setattr(
        mock_api_import,
        "get_settings",
        lambda: SimpleNamespace(
            database_url="postgresql+asyncpg://test:test@localhost/test",
        ),
    )
    connection = AsyncMock()
    transaction_context = MagicMock()
    transaction_context.__aenter__ = AsyncMock(
        return_value=connection,
    )
    transaction_context.__aexit__ = AsyncMock(
        return_value=None,
    )
    engine = MagicMock()
    engine.begin.return_value = transaction_context
    engine.dispose = AsyncMock()
    create_engine_mock = MagicMock(
        return_value=engine,
    )
    upsert_sites_mock = AsyncMock()
    monkeypatch.setattr(
        mock_api_import,
        "create_async_engine",
        create_engine_mock,
    )
    monkeypatch.setattr(
        mock_api_import,
        "upsert_sites",
        upsert_sites_mock,
    )
    await mock_api_import.import_mock_api_history(
        start_time=datetime.fromisoformat("2024-06-15T12:00:00"),
        end_time=datetime.fromisoformat("2024-06-15T13:00:00"),
        limit=60,
        dry_run=False,
    )
    create_engine_mock.assert_called_once_with(
        "postgresql+asyncpg://test:test@localhost/test",
        pool_pre_ping=True,
    )
    upsert_sites_mock.assert_awaited_once_with(
        connection,
        [make_site()],
    )
    connection.execute.assert_awaited_once()
    engine.dispose.assert_awaited_once()
 def test_parse_datetime_accepts_z_suffix() -> None:
    result = mock_api_import.parse_datetime(
        "2024-06-15T12:00:00Z",
    )
    assert result == datetime.fromisoformat(
        "2024-06-15T12:00:00+00:00",
    )
 def test_parse_args_reads_cli_parameters(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    monkeypatch.setattr(
        sys,
        "argv",
        [
            "mock_api_import",
            "--start-time",
            "2024-06-15T12:00:00Z",
            "--end-time",
            "2024-06-15T13:00:00Z",
            "--limit",
            "60",
            "--dry-run",
        ],
    )
    args = mock_api_import.parse_args()
    assert args.start_time == datetime.fromisoformat(
        "2024-06-15T12:00:00+00:00",
    )
    assert args.end_time == datetime.fromisoformat(
        "2024-06-15T13:00:00+00:00",
    )
    assert args.limit == 60
    assert args.dry_run is True
 def test_main_rejects_limit_out_of_bounds(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    monkeypatch.setattr(
        sys,
        "argv",
        [
            "mock_api_import",
            "--start-time",
            "2024-06-15T12:00:00Z",
            "--end-time",
            "2024-06-15T13:00:00Z",
            "--limit",
            "0",
        ],
    )
    with pytest.raises(
        ValueError,
        match="--limit doit être compris entre 1 et 1000",
    ):
        mock_api_import.main()
 def test_main_rejects_invalid_period(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    monkeypatch.setattr(
        sys,
        "argv",
        [
            "mock_api_import",
            "--start-time",
            "2024-06-15T14:00:00Z",
            "--end-time",
            "2024-06-15T13:00:00Z",
            "--limit",
            "60",
        ],
    )
    with pytest.raises(
        ValueError,
        match="--start-time doit être antérieur à --end-time",
    ):
        mock_api_import.main()
 def test_main_runs_import(
    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
    start_time = datetime.fromisoformat(
        "2024-06-15T12:00:00+00:00",
    )
    end_time = datetime.fromisoformat(
        "2024-06-15T13:00:00+00:00",
    )
    import_mock = AsyncMock()
    monkeypatch.setattr(
        mock_api_import,
        "parse_args",
        lambda: SimpleNamespace(
            start_time=start_time,
            end_time=end_time,
            limit=60,
            dry_run=True,
        ),
    )
    monkeypatch.setattr(
        mock_api_import,
        "import_mock_api_history",
        import_mock,
    )
    mock_api_import.main()
    import_mock.assert_awaited_once_with(
        start_time=start_time,
        end_time=end_time,
        limit=60,
        dry_run=True,
    )
 async def test_fetch_sites_rejects_a_response_above_the_cap() -> None:
    def handler(request: Request) -> Response:
        return Response(
            status_code=200,
            json=[make_site() for _ in range(MAX_SITES + 1)],
        )
    transport = MockTransport(handler)
    async with AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    ) as client:
        with pytest.raises(
            ValueError,
            match=f"dépasse le plafond de {MAX_SITES} sites",
        ):
            await fetch_sites(client)
 async def test_fetch_readings_rejects_a_response_above_the_requested_limit() -> None:
    def handler(request: Request) -> Response:
        return Response(
            status_code=200,
            json=[make_reading(), make_reading(), make_reading()],
        )
    transport = MockTransport(handler)
    async with AsyncClient(
        transport=transport,
        base_url="https://mock.test",
    ) as client:
        with pytest.raises(
            ValueError,
            match="dépasse la limite demandée de 2",
        ):
            await fetch_readings(
                client=client,
                site_id="SITE001",
                start_time=datetime.fromisoformat("2024-06-15T12:00:00"),
                end_time=datetime.fromisoformat("2024-06-15T13:00:00"),
                limit=2,
            )
 def test_build_reading_row_neutralises_values_outside_physical_bounds() -> None:
    reading = make_reading()
    reading["power_factor"] = 42.0
    reading["temperature_celsius"] = 1e30
    reading["humidity_percent"] = -1.0
    row = build_reading_row(reading)
    assert row["power_factor"] is None
    assert row["temperature_celsius"] is None
    assert row["humidity_percent"] is None
    assert row["null_reasons"] == [
        "out_of_physical_bounds:power_factor",
        "out_of_physical_bounds:temperature_celsius",
        "out_of_physical_bounds:humidity_percent",
    ]
    assert row["data_quality"] == "degraded"
    assert json.loads(row["raw_data"])["power_factor"] == 42.0
 def test_build_reading_row_rejects_a_measure_that_is_not_a_number() -> None:
    reading = make_reading()
    reading["consumption_kw"] = "87.34"
    row = build_reading_row(reading)
    assert row["consumption_kw"] is None
    assert "out_of_physical_bounds:consumption_kw" in row["null_reasons"]
 def test_build_reading_row_drops_a_quality_the_database_refuses() -> None:
    reading = make_reading()
    reading["data_quality"] = "unknown"
    row = build_reading_row(reading)
    assert row["data_quality"] is None
 def test_build_reading_row_requires_an_identifier() -> None:
    reading = make_reading()
    del reading["site_id"]
    with pytest.raises(
        ValueError,
        match="Champ site_id absent ou invalide",
    ):
        build_reading_row(reading)
 def test_build_site_row_keeps_only_the_expected_columns() -> None:
    site = make_site()
    site["unexpected"] = "valeur hostile"
    site["capacity_kw"] = -5.0
    site["status"] = 12
    row = build_site_row(site)
    assert set(row) == {
        "site_id",
        "site_type",
        "site_name",
        "location",
        "capacity_kw",
        "status",
    }
    assert row["capacity_kw"] is None
    assert row["status"] is None
 async def test_upsert_sites_sends_only_the_expected_columns() -> None:
    connection = AsyncMock()
    site = make_site()
    site["unexpected"] = "valeur hostile"
    await upsert_sites(
        connection,
        [site],
    )
    rows = connection.execute.await_args.args[1]
    assert "unexpected" not in rows[0]
    assert rows[0]["site_id"] == "SITE001"
@pytest.mark.integration
 async def test_reading_insert_is_idempotent(
    session: AsyncSession,
 ) -> None:
    reading = make_reading()
    row = build_reading_row(reading)
    connection = await session.connection()
    await upsert_sites(
        connection,
        [make_site()],
    )
    await session.execute(
        READING_INSERT,
        [row],
    )
    await session.execute(
        READING_INSERT,
        [row],
    )
    result = await session.execute(
        text(
            """
            SELECT COUNT(*)
            FROM reading
            WHERE site_id = :site_id
              AND timestamp = :timestamp
              AND source = :source
            """
        ),
        {
            "site_id": row["site_id"],
            "timestamp": row["timestamp"],
            "source": row["source"],
        },
    )
    assert result.scalar_one() == 1
    await session.rollback()
@pytest.mark.integration
 async def test_out_of_bounds_reading_is_stored_neutralised(
    session: AsyncSession,
 ) -> None:
    reading = make_reading()
    reading["power_factor"] = 42.0
    row = build_reading_row(reading)
    connection = await session.connection()
    await upsert_sites(
        connection,
        [make_site()],
    )
    await session.execute(
        READING_INSERT,
        [row],
    )
    result = await session.execute(
        text(
            """
            SELECT power_factor, data_quality, null_reasons, raw_data ->> 'power_factor'
            FROM reading
            WHERE site_id = :site_id
              AND timestamp = :timestamp
              AND source = :source
            """
        ),
        {
            "site_id": row["site_id"],
            "timestamp": row["timestamp"],
            "source": row["source"],
        },
    )
    stored = result.one()
    await session.rollback()
    assert stored[0] is None
    assert stored[1] == "degraded"
    assert stored[2] == ["out_of_physical_bounds:power_factor"]
    assert stored[3] == "42.0"
@@ -89,60 +89,3 @@ async def test_list_all_returns_an_empty_list_when_there_is_nothing(
    alertes = await depot.list_all(site_id=identifiant_site())
    assert list(alertes) == []
 def _alerte_a_inserer(*, site_id: str, source_alert_id: str) -> Alert:
    return Alert(
        source_alert_id=source_alert_id,
        site_id=site_id,
        source="enervision",
        timestamp=datetime(2026, 9, 16, tzinfo=UTC),
        type="threshold",
        severity="high",
        message="Dépassement du seuil configuré",
        value=812.5,
        threshold=720.0,
        metric="consumption_kw",
        prediction_id=None,
        raw_data={},
    )
 async def test_create_many_inserts_every_alert(session: AsyncSession) -> None:
    site = await creer_site(session)
    depot = AlertRepository(session)
    creees = await depot.create_many(
        [
            _alerte_a_inserer(site_id=site.site_id, source_alert_id="threshold:a"),
            _alerte_a_inserer(site_id=site.site_id, source_alert_id="threshold:b"),
        ]
    )
    identifiants = [a.alert_id for a in creees]
    await session.rollback()
    assert len(identifiants) == 2
    assert all(identifiant is not None for identifiant in identifiants)
 async def test_create_many_skips_a_duplicate_source_alert_id(session: AsyncSession) -> None:
    site = await creer_site(session)
    depot = AlertRepository(session)
    await depot.create_many(
        [_alerte_a_inserer(site_id=site.site_id, source_alert_id="threshold:rejouee")]
    )
    rejouees = await depot.create_many(
        [_alerte_a_inserer(site_id=site.site_id, source_alert_id="threshold:rejouee")]
    )
    await session.rollback()
    assert rejouees == []
 async def test_create_many_does_nothing_for_an_empty_list(session: AsyncSession) -> None:
    depot = AlertRepository(session)
    creees = await depot.create_many([])
    assert creees == []
@@ -49,10 +49,8 @@ async def test_the_database_refuses_to_mutate_the_audit_log(
 ) -> None:
    await une_ligne(session)
    requete = text(instruction)
    with pytest.raises(DBAPIError, match="ajout seul"):
-        await session.execute(requete)
+        await session.execute(text(instruction))
    await session.rollback()
@@ -131,14 +131,11 @@ async def test_the_database_refuses_two_tokens_sharing_a_fingerprint(
        user_agent=None,
    )
    empreinte = fingerprint_refresh(secret)
    expiration = datetime.now(UTC) + DUREE
    with pytest.raises(IntegrityError):
        await depot.create(
            user_id=compte,
-            token_hash=empreinte,
+            token_hash=fingerprint_refresh(secret),
-            expires_at=expiration,
+            expires_at=datetime.now(UTC) + DUREE,
            client_ip=None,
            user_agent=None,
        )
@@ -1,171 +0,0 @@
 from datetime import UTC, datetime
 import pytest
 from sqlalchemy.ext.asyncio import AsyncSession
 from app.models.energy import Prediction
 from app.repositories.prediction import PredictionRepository
 from tests.repositories.test_site import creer as creer_site
 from tests.repositories.test_site import identifiant as identifiant_site
 pytestmark = pytest.mark.integration
 async def creer_prediction(
    session: AsyncSession, *, site_id: str, **overrides: object
 ) -> Prediction:
    prediction = Prediction(
        site_id=site_id,
        target_at=overrides.get("target_at", datetime(2026, 9, 16, tzinfo=UTC)),
        target_metric=overrides.get("target_metric", "consumption_kwh"),
        period_minutes=overrides.get("period_minutes", 60),
        predicted_value=overrides.get("predicted_value", 42.0),
        model_reference=overrides.get("model_reference", "lightgbm-test"),
        status=overrides.get("status", "available"),
        failure_reason=overrides.get("failure_reason"),
    )
    session.add(prediction)
    await session.flush()
    return prediction
 async def test_list_since_excludes_predictions_before_the_cutoff(session: AsyncSession) -> None:
    site = await creer_site(session)
    depot = PredictionRepository(session)
    dedans = await creer_prediction(
        session, site_id=site.site_id, target_at=datetime(2026, 9, 16, tzinfo=UTC)
    )
    await creer_prediction(
        session, site_id=site.site_id, target_at=datetime(2026, 9, 1, tzinfo=UTC)
    )
    resultats = await depot.list_since(
        since=datetime(2026, 9, 10, tzinfo=UTC), site_id=site.site_id
    )
    identifiants = [p.prediction_id for p in resultats]
    await session.rollback()
    assert identifiants == [dedans.prediction_id]
 async def test_list_since_excludes_predictions_that_are_not_available(
    session: AsyncSession,
 ) -> None:
    site = await creer_site(session)
    depot = PredictionRepository(session)
    await creer_prediction(
        session,
        site_id=site.site_id,
        target_at=datetime(2026, 9, 16, tzinfo=UTC),
        status="insufficient_data",
        predicted_value=None,
        failure_reason="pas assez d'historique",
    )
    resultats = await depot.list_since(since=datetime(2026, 9, 1, tzinfo=UTC), site_id=site.site_id)
    await session.rollback()
    assert list(resultats) == []
 async def test_list_since_breaks_a_target_at_tie_by_ascending_prediction_id(
    session: AsyncSession,
 ) -> None:
    # `prediction` n'a pas d'unicité sur `(site_id, target_at)` : deux runs de scoring sans
    # nouvelle lecture entre-temps produisent deux lignes `available` à la même cible. Sans ce
    # départage, `_detect_anomaly` retiendrait une ligne au hasard plutôt que le run le plus
    # récent.
    site = await creer_site(session)
    depot = PredictionRepository(session)
    cible = datetime(2026, 9, 16, tzinfo=UTC)
    premier_run = await creer_prediction(
        session, site_id=site.site_id, target_at=cible, predicted_value=10.0
    )
    second_run = await creer_prediction(
        session, site_id=site.site_id, target_at=cible, predicted_value=20.0
    )
    resultats = await depot.list_since(since=datetime(2026, 9, 1, tzinfo=UTC), site_id=site.site_id)
    identifiants = [p.prediction_id for p in resultats]
    await session.rollback()
    assert identifiants == [premier_run.prediction_id, second_run.prediction_id]
 async def test_list_since_filters_by_site_id(session: AsyncSession) -> None:
    premier = await creer_site(session)
    second = await creer_site(session)
    depot = PredictionRepository(session)
    voulue = await creer_prediction(session, site_id=premier.site_id)
    await creer_prediction(session, site_id=second.site_id)
    resultats = await depot.list_since(
        since=datetime(2026, 8, 1, tzinfo=UTC), site_id=premier.site_id
    )
    identifiants = [p.prediction_id for p in resultats]
    await session.rollback()
    assert identifiants == [voulue.prediction_id]
 async def test_latest_by_site_keeps_only_the_most_recent_target(session: AsyncSession) -> None:
    site = await creer_site(session)
    depot = PredictionRepository(session)
    ancienne = await creer_prediction(
        session, site_id=site.site_id, target_at=datetime(2026, 9, 1, tzinfo=UTC)
    )
    recente = await creer_prediction(
        session, site_id=site.site_id, target_at=datetime(2026, 9, 15, tzinfo=UTC)
    )
    resultats = await depot.latest_by_site()
    identifiants = [
        p.prediction_id
        for p in resultats
        if p.prediction_id in (ancienne.prediction_id, recente.prediction_id)
    ]
    await session.rollback()
    assert identifiants == [recente.prediction_id]
 async def test_latest_by_site_returns_one_row_per_site(session: AsyncSession) -> None:
    premier = await creer_site(session)
    second = await creer_site(session)
    depot = PredictionRepository(session)
    voulue_premier = await creer_prediction(session, site_id=premier.site_id)
    voulue_second = await creer_prediction(session, site_id=second.site_id)
    resultats = await depot.latest_by_site()
    identifiants = {p.site_id for p in resultats if p.site_id in (premier.site_id, second.site_id)}
    await session.rollback()
    assert identifiants == {voulue_premier.site_id, voulue_second.site_id}
 async def test_latest_by_site_keeps_an_insufficient_data_prediction(session: AsyncSession) -> None:
    site = await creer_site(session)
    depot = PredictionRepository(session)
    voulue = await creer_prediction(
        session,
        site_id=site.site_id,
        status="insufficient_data",
        predicted_value=None,
        failure_reason="pas assez d'historique",
    )
    resultats = await depot.latest_by_site()
    identifiants = [p.prediction_id for p in resultats if p.site_id == site.site_id]
    await session.rollback()
    assert identifiants == [voulue.prediction_id]
 async def test_latest_by_site_returns_an_empty_list_when_there_is_nothing(
    session: AsyncSession,
 ) -> None:
    depot = PredictionRepository(session)
    resultats = [p for p in await depot.latest_by_site() if p.site_id == identifiant_site()]
    assert resultats == []
@@ -155,79 +155,6 @@ async def test_latest_for_site_ignores_the_readings_of_the_other_sites(
    assert trouvee is None
 async def test_list_since_orders_by_site_then_by_time_ascending(session: AsyncSession) -> None:
    site = await creer_site(session)
    depot = ReadingRepository(session)
    plus_recente = await creer_lecture(
        session, site_id=site.site_id, timestamp=datetime(2026, 9, 16, tzinfo=UTC)
    )
    plus_ancienne = await creer_lecture(
        session, site_id=site.site_id, timestamp=datetime(2026, 9, 15, tzinfo=UTC)
    )
    resultats = await depot.list_since(since=datetime(2026, 9, 1, tzinfo=UTC), site_id=site.site_id)
    identifiants = [r.reading_id for r in resultats]
    await session.rollback()
    assert identifiants == [plus_ancienne.reading_id, plus_recente.reading_id]
 async def test_list_since_excludes_readings_before_the_cutoff(session: AsyncSession) -> None:
    site = await creer_site(session)
    depot = ReadingRepository(session)
    dedans = await creer_lecture(
        session, site_id=site.site_id, timestamp=datetime(2026, 9, 16, tzinfo=UTC)
    )
    await creer_lecture(session, site_id=site.site_id, timestamp=datetime(2026, 9, 1, tzinfo=UTC))
    resultats = await depot.list_since(
        since=datetime(2026, 9, 10, tzinfo=UTC), site_id=site.site_id
    )
    identifiants = [r.reading_id for r in resultats]
    await session.rollback()
    assert identifiants == [dedans.reading_id]
 async def test_list_since_breaks_a_timestamp_tie_by_ascending_reading_id(
    session: AsyncSession,
 ) -> None:
    # `uq_reading_source` autorise deux lignes au même `site_id`+`timestamp` quand la `source`
    # diffère (même piège que `latest_for_site`). Sans ce départage, `_detect_spike` traiterait
    # cette paire comme une variation réelle selon un ordre non garanti par le plan d'exécution.
    site = await creer_site(session)
    depot = ReadingRepository(session)
    horodatage = datetime(2026, 9, 16, tzinfo=UTC)
    premiere = await creer_lecture(
        session, site_id=site.site_id, timestamp=horodatage, source="api_history", consumption_kw=10
    )
    seconde = await creer_lecture(
        session, site_id=site.site_id, timestamp=horodatage, source="api_current", consumption_kw=42
    )
    resultats = await depot.list_since(since=datetime(2026, 9, 1, tzinfo=UTC), site_id=site.site_id)
    identifiants = [r.reading_id for r in resultats]
    await session.rollback()
    assert identifiants == [premiere.reading_id, seconde.reading_id]
 async def test_list_since_filters_by_site_id(session: AsyncSession) -> None:
    premier = await creer_site(session)
    second = await creer_site(session)
    depot = ReadingRepository(session)
    voulue = await creer_lecture(session, site_id=premier.site_id)
    await creer_lecture(session, site_id=second.site_id)
    resultats = await depot.list_since(
        since=datetime(2026, 8, 1, tzinfo=UTC), site_id=premier.site_id
    )
    identifiants = [r.reading_id for r in resultats]
    await session.rollback()
    assert identifiants == [voulue.reading_id]
 async def test_list_history_orders_the_readings_by_timestamp_descending(
    session: AsyncSession,
 ) -> None:
@@ -5,8 +5,7 @@ import pytest
 from sqlalchemy.ext.asyncio import AsyncSession
 from app.models.energy import Alert, Recommendation, Site
-from app.repositories import recommendation as module_recommendation
+from app.repositories.recommendation import RecommendationRepository
 from app.repositories.recommendation import NouvelleRecommandation, RecommendationRepository
 pytestmark = pytest.mark.integration
@@ -84,59 +83,3 @@ async def test_list_all_returns_the_recommendations_sorted_by_identifier(
    await session.rollback()
    assert identifiants == sorted(identifiants)
 def nouvelle(alert_id: int, reference: str = "spike-delestage-v1") -> NouvelleRecommandation:
    return NouvelleRecommandation(
        alert_id=alert_id,
        action="Délester les équipements non prioritaires",
        explanation="Pic de consommation signalé.",
        rule_reference=reference,
    )
 async def test_create_missing_inserts_the_proposals(session: AsyncSession) -> None:
    depot = RecommendationRepository(session)
    alert_id = await creer_alerte(session)
    creees = await depot.create_missing(
        [nouvelle(alert_id), nouvelle(alert_id, "escalade-astreinte-v1")]
    )
    await session.rollback()
    assert creees == 2
 async def test_create_missing_ignores_a_rule_already_held_for_the_alert(
    session: AsyncSession,
 ) -> None:
    depot = RecommendationRepository(session)
    alert_id = await creer_alerte(session)
    await depot.create_missing([nouvelle(alert_id)])
    creees = await depot.create_missing([nouvelle(alert_id)])
    await session.rollback()
    assert creees == 0
 async def test_create_missing_returns_zero_without_any_proposal(session: AsyncSession) -> None:
    creees = await RecommendationRepository(session).create_missing([])
    assert creees == 0
 async def test_create_missing_inserts_every_proposal_across_several_batches(
    session: AsyncSession, monkeypatch: pytest.MonkeyPatch
 ) -> None:
    monkeypatch.setattr(module_recommendation, "TAILLE_DE_LOT", 2)
    depot = RecommendationRepository(session)
    alert_id = await creer_alerte(session)
    propositions = [nouvelle(alert_id, f"regle-{index}-v1") for index in range(5)]
    creees = await depot.create_missing(propositions)
    enregistrees = [r for r in await depot.list_all() if r.alert_id == alert_id]
    await session.rollback()
    assert creees == 5
    assert len(enregistrees) == 5
@@ -178,16 +178,12 @@ async def test_the_database_refuses_two_tokens_sharing_a_fingerprint(
        user_agent=None,
    )
    famille = uuid.uuid4()
    empreinte = fingerprint_refresh(secret)
    expiration = datetime.now(UTC) + DUREE
    with pytest.raises(IntegrityError):
        await depot.create(
            user_id=compte,
-            family_id=famille,
+            family_id=uuid.uuid4(),
-            token_hash=empreinte,
+            token_hash=fingerprint_refresh(secret),
-            expires_at=expiration,
+            expires_at=datetime.now(UTC) + DUREE,
            client_ip=None,
            user_agent=None,
        )
@@ -31,12 +31,14 @@ async def test_the_database_refuses_an_email_written_in_upper_case(
 ) -> None:
    saisie = adresse().upper()
    requete = text(
        "insert into app_user (email, password_hash, role) values (:e, '$argon2id$x', 'lecteur')"
    )
    with pytest.raises(IntegrityError):
-        await session.execute(requete, {"e": saisie})
+        await session.execute(
            text(
                "insert into app_user (email, password_hash, role) "
                "values (:e, '$argon2id$x', 'lecteur')"
            ),
            {"e": saisie},
        )
    await session.rollback()
@@ -1,10 +1,7 @@
-from dataclasses import dataclass, field
+from datetime import UTC, datetime
 from datetime import UTC, datetime, timedelta
 from app.models.energy import Alert
-from app.services.alert import OUTAGE_THRESHOLD, AlertService, _severity_from_ratio
+from app.services.alert import AlertService
 NOW = datetime(2026, 9, 16, 12, 0, tzinfo=UTC)
 def alert(
@@ -29,36 +26,10 @@ def alert(
    )
@dataclass
 class FauxSite:
    site_id: str
    capacity_kw: float | None = None
@dataclass
 class FauxLecture:
    site_id: str
    timestamp: datetime
    consumption_kw: float | None = None
    consumption_kwh: float | None = None
    data_quality: str | None = None
    null_reasons: list[str] | None = None
@dataclass
 class FauxPrediction:
    site_id: str
    target_at: datetime
    predicted_value: float | None
    target_metric: str = "consumption_kwh"
    prediction_id: int = 1
 class FakeRepository:
    def __init__(self, alerts: list[Alert]) -> None:
        self._alerts = alerts
        self.appels: list[tuple[str | None, str | None]] = []
        self.crees: list[Alert] = []
    async def list_all(
        self, *, site_id: str | None = None, severity: str | None = None
@@ -66,392 +37,19 @@ class FakeRepository:
        self.appels.append((site_id, severity))
        return self._alerts
    async def create_many(self, alerts: list[Alert]) -> list[Alert]:
        self.crees = list(alerts)
        return self.crees
@dataclass
 class FauxDepotLectures:
    depuis: list[FauxLecture] = field(default_factory=list)
    dernieres: list[FauxLecture] = field(default_factory=list)
    async def list_since(self, *, since: datetime, site_id: str | None = None) -> list[FauxLecture]:
        return [lecture for lecture in self.depuis if site_id is None or lecture.site_id == site_id]
    async def latest_by_site(self) -> list[FauxLecture]:
        return self.dernieres
@dataclass
 class FauxDepotPredictions:
    predictions: list[FauxPrediction] = field(default_factory=list)
    async def list_since(
        self, *, since: datetime, site_id: str | None = None
    ) -> list[FauxPrediction]:
        return [p for p in self.predictions if site_id is None or p.site_id == site_id]
@dataclass
 class FauxDepotSites:
    sites: list[FauxSite]
    async def list_all(self) -> list[FauxSite]:
        return self.sites
 def service(
    *,
    sites: list[FauxSite],
    lectures: list[FauxLecture] | None = None,
    dernieres: list[FauxLecture] | None = None,
    predictions: list[FauxPrediction] | None = None,
    alerts: FakeRepository | None = None,
 ) -> tuple[AlertService, FakeRepository]:
    depot_alertes = alerts or FakeRepository([])
    dernieres_lectures = dernieres if dernieres is not None else (lectures or [])
    return (
        AlertService(
            alerts=depot_alertes,  # type: ignore[arg-type]
            readings=FauxDepotLectures(depuis=lectures or [], dernieres=dernieres_lectures),  # type: ignore[arg-type]
            predictions=FauxDepotPredictions(predictions or []),  # type: ignore[arg-type]
            sites=FauxDepotSites(sites),  # type: ignore[arg-type]
        ),
        depot_alertes,
    )
 async def test_list_all_returns_the_repository_alerts() -> None:
-    svc, _ = service(sites=[], alerts=FakeRepository([alert(1), alert(2)]))
+    service = AlertService(alerts=FakeRepository([alert(1), alert(2)]))
-    alertes = await svc.list_all()
+    alertes = await service.list_all()
    assert [a.alert_id for a in alertes] == [1, 2]
 async def test_list_all_relays_the_filters_to_the_repository() -> None:
    depot = FakeRepository([])
-    svc, _ = service(sites=[], alerts=depot)
+    service = AlertService(alerts=depot)
-    await svc.list_all(site_id="site-1", severity="critical")
+    await service.list_all(site_id="site-1", severity="critical")
    assert depot.appels == [("site-1", "critical")]
 async def test_detect_raises_a_threshold_alert_above_site_capacity() -> None:
    svc, depot = service(
        sites=[FauxSite("A", capacity_kw=100.0)],
        lectures=[FauxLecture("A", NOW, consumption_kw=150.0)],
    )
    await svc.detect(now=NOW)
    (candidate,) = depot.crees
    assert candidate.type == "threshold"
    assert candidate.severity == "high"
    assert candidate.value == 150.0
    assert candidate.threshold == 100.0
    assert candidate.metric == "consumption_kw"
 async def test_detect_ignores_a_reading_within_capacity() -> None:
    svc, depot = service(
        sites=[FauxSite("A", capacity_kw=100.0)],
        lectures=[FauxLecture("A", NOW, consumption_kw=80.0)],
    )
    await svc.detect(now=NOW)
    assert depot.crees == []
 async def test_detect_ignores_threshold_when_the_site_has_no_declared_capacity() -> None:
    svc, depot = service(
        sites=[FauxSite("A", capacity_kw=None)],
        lectures=[FauxLecture("A", NOW, consumption_kw=9999.0)],
    )
    await svc.detect(now=NOW)
    assert depot.crees == []
 async def test_detect_raises_a_spike_alert_on_a_brutal_consecutive_variation() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[
            FauxLecture("A", NOW - timedelta(hours=1), consumption_kw=100.0),
            FauxLecture("A", NOW, consumption_kw=160.0),
        ],
    )
    await svc.detect(now=NOW)
    (candidate,) = [a for a in depot.crees if a.type == "spike"]
    assert candidate.value == 160.0
    assert candidate.threshold == 100.0
    assert candidate.timestamp == NOW
 async def test_detect_ignores_a_moderate_consecutive_variation() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[
            FauxLecture("A", NOW - timedelta(hours=1), consumption_kw=100.0),
            FauxLecture("A", NOW, consumption_kw=110.0),
        ],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "spike"] == []
 async def test_detect_never_compares_consecutive_readings_across_two_sites() -> None:
    svc, depot = service(
        sites=[FauxSite("A"), FauxSite("B")],
        lectures=[
            FauxLecture("A", NOW - timedelta(hours=1), consumption_kw=10.0),
            FauxLecture("B", NOW, consumption_kw=1000.0),
        ],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "spike"] == []
 async def test_detect_raises_an_anomaly_alert_far_from_the_matching_prediction() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[FauxLecture("A", NOW, consumption_kwh=100.0)],
        predictions=[FauxPrediction("A", target_at=NOW, predicted_value=70.0)],
    )
    await svc.detect(now=NOW)
    (candidate,) = [a for a in depot.crees if a.type == "anomaly"]
    assert candidate.value == 100.0
    assert candidate.threshold == 70.0
    assert candidate.metric == "consumption_kwh"
    assert candidate.prediction_id == 1
 async def test_detect_ignores_a_reading_close_to_its_prediction() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[FauxLecture("A", NOW, consumption_kwh=100.0)],
        predictions=[FauxPrediction("A", target_at=NOW, predicted_value=95.0)],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "anomaly"] == []
 async def test_detect_ignores_a_prediction_whose_target_at_does_not_match_the_reading() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[FauxLecture("A", NOW, consumption_kwh=100.0)],
        predictions=[FauxPrediction("A", target_at=NOW - timedelta(hours=1), predicted_value=1.0)],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "anomaly"] == []
 async def test_detect_keeps_the_most_recent_run_when_two_predictions_share_the_same_target() -> (
    None
 ):
    # `PredictionRepository.list_since` départage les égalités de `target_at` par `prediction_id`
    # croissant : le repository fait donc déjà passer le run le plus récent en dernier dans la
    # liste, et c'est ce dernier que le dict de `_detect_anomaly` doit retenir.
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[FauxLecture("A", NOW, consumption_kwh=100.0)],
        predictions=[
            FauxPrediction("A", target_at=NOW, predicted_value=100.0, prediction_id=1),
            FauxPrediction("A", target_at=NOW, predicted_value=70.0, prediction_id=2),
        ],
    )
    await svc.detect(now=NOW)
    (candidate,) = [a for a in depot.crees if a.type == "anomaly"]
    assert candidate.threshold == 70.0
    assert candidate.prediction_id == 2
 async def test_detect_raises_an_outage_alert_past_the_threshold() -> None:
    derniere = NOW - OUTAGE_THRESHOLD - timedelta(minutes=1)
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[],
        dernieres=[FauxLecture("A", derniere)],
    )
    await svc.detect(now=NOW)
    (candidate,) = [a for a in depot.crees if a.type == "outage"]
    assert candidate.severity in {"low", "medium", "high", "critical"}
 async def test_detect_ignores_a_site_still_within_the_outage_threshold() -> None:
    derniere = NOW - OUTAGE_THRESHOLD + timedelta(minutes=1)
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[],
        dernieres=[FauxLecture("A", derniere)],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "outage"] == []
 async def test_detect_raises_a_critical_outage_alert_for_a_site_never_read() -> None:
    svc, depot = service(sites=[FauxSite("A")], lectures=[], dernieres=[])
    await svc.detect(now=NOW)
    (candidate,) = [a for a in depot.crees if a.type == "outage"]
    assert candidate.severity == "critical"
    assert candidate.source_alert_id == "outage:jamais"
 async def test_detect_raises_a_sensor_alert_on_a_degraded_reading() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[FauxLecture("A", NOW, data_quality="critical", null_reasons=["missing:x"])],
    )
    await svc.detect(now=NOW)
    (candidate,) = [a for a in depot.crees if a.type == "sensor"]
    assert candidate.severity == "critical"
 async def test_detect_ignores_a_good_quality_reading_for_the_sensor_rule() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[FauxLecture("A", NOW, data_quality="good")],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "sensor"] == []
 async def test_detect_scopes_to_a_single_site_when_asked() -> None:
    svc, depot = service(
        sites=[FauxSite("A", capacity_kw=100.0), FauxSite("B", capacity_kw=100.0)],
        lectures=[
            FauxLecture("A", NOW, consumption_kw=150.0),
            FauxLecture("B", NOW, consumption_kw=150.0),
        ],
    )
    await svc.detect(now=NOW, site_id="A")
    assert {a.site_id for a in depot.crees} == {"A"}
 async def test_detect_returns_early_when_there_is_no_site() -> None:
    svc, depot = service(sites=[])
    resultat = await svc.detect(now=NOW)
    assert resultat == []
    assert depot.crees == []
 async def test_detect_ignores_a_spike_pair_with_a_missing_measurement() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[
            FauxLecture("A", NOW - timedelta(hours=1), consumption_kw=None),
            FauxLecture("A", NOW, consumption_kw=160.0),
        ],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "spike"] == []
 async def test_detect_ignores_a_reading_still_at_zero_after_a_previous_zero() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[
            FauxLecture("A", NOW - timedelta(hours=1), consumption_kw=0.0),
            FauxLecture("A", NOW, consumption_kw=0.0),
        ],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "spike"] == []
 async def test_detect_raises_a_critical_spike_when_a_site_restarts_from_zero() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[
            FauxLecture("A", NOW - timedelta(hours=1), consumption_kw=0.0),
            FauxLecture("A", NOW, consumption_kw=50.0),
        ],
    )
    await svc.detect(now=NOW)
    (candidate,) = [a for a in depot.crees if a.type == "spike"]
    assert candidate.severity == "critical"
    assert candidate.value == 50.0
    assert candidate.threshold == 0.0
 async def test_detect_ignores_a_spike_pair_sharing_the_same_timestamp() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[
            FauxLecture("A", NOW, consumption_kw=100.0),
            FauxLecture("A", NOW, consumption_kw=160.0),
        ],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "spike"] == []
 async def test_detect_ignores_an_anomaly_when_the_prediction_is_near_zero() -> None:
    svc, depot = service(
        sites=[FauxSite("A")],
        lectures=[FauxLecture("A", NOW, consumption_kwh=5.0)],
        predictions=[FauxPrediction("A", target_at=NOW, predicted_value=0.0)],
    )
    await svc.detect(now=NOW)
    assert [a for a in depot.crees if a.type == "anomaly"] == []
 def test_severity_from_ratio_covers_every_band() -> None:
    assert _severity_from_ratio(1.0) == "low"
    assert _severity_from_ratio(1.2) == "medium"
    assert _severity_from_ratio(1.5) == "high"
    assert _severity_from_ratio(2.0) == "critical"
 async def test_detect_does_not_call_create_many_when_nothing_triggers() -> None:
    svc, depot = service(
        sites=[FauxSite("A", capacity_kw=100.0)],
        lectures=[FauxLecture("A", NOW, consumption_kw=10.0, data_quality="good")],
    )
    resultat = await svc.detect(now=NOW)
    assert resultat == []
    assert depot.crees == []
@@ -1,121 +0,0 @@
 from dataclasses import dataclass
 from datetime import UTC, datetime
 from app.services.prediction import PredictionService
 TARGET_AT = datetime(2026, 9, 16, 13, 0, tzinfo=UTC)
 CREATED_AT = datetime(2026, 9, 16, 12, 0, tzinfo=UTC)
@dataclass
 class FauxSite:
    site_id: str
    site_name: str
@dataclass
 class FauxPrediction:
    site_id: str
    target_at: datetime
    target_metric: str
    period_minutes: int | None
    predicted_value: float | None
    status: str
    failure_reason: str | None
    model_reference: str
    created_at: datetime
 class FauxDepotSites:
    def __init__(self, sites: list[FauxSite]) -> None:
        self._sites = sites
    async def list_all(self) -> list[FauxSite]:
        return self._sites
 class FauxDepotPredictions:
    def __init__(self, predictions: list[FauxPrediction]) -> None:
        self._predictions = predictions
    async def latest_by_site(self) -> list[FauxPrediction]:
        return self._predictions
 def prediction_disponible(site_id: str = "A") -> FauxPrediction:
    return FauxPrediction(
        site_id=site_id,
        target_at=TARGET_AT,
        target_metric="consumption_kwh",
        period_minutes=60,
        predicted_value=812.5,
        status="available",
        failure_reason=None,
        model_reference="lightgbm-abc123",
        created_at=CREATED_AT,
    )
 async def test_summary_attaches_the_latest_prediction_to_its_site() -> None:
    service = PredictionService(
        sites=FauxDepotSites([FauxSite("A", "Site A")]),  # type: ignore[arg-type]
        predictions=FauxDepotPredictions([prediction_disponible("A")]),  # type: ignore[arg-type]
    )
    resume = await service.summary()
    site = resume.sites[0]
    assert site.site_id == "A"
    assert site.prediction is not None
    assert site.prediction.predicted_value == 812.5
    assert site.prediction.status == "available"
 async def test_summary_leaves_prediction_none_for_a_site_never_scored() -> None:
    service = PredictionService(
        sites=FauxDepotSites([FauxSite("A", "Site A")]),  # type: ignore[arg-type]
        predictions=FauxDepotPredictions([]),  # type: ignore[arg-type]
    )
    resume = await service.summary()
    assert resume.sites[0].prediction is None
 async def test_summary_carries_an_insufficient_data_prediction_without_a_value() -> None:
    insuffisante = FauxPrediction(
        site_id="A",
        target_at=TARGET_AT,
        target_metric="consumption_kwh",
        period_minutes=60,
        predicted_value=None,
        status="insufficient_data",
        failure_reason="pas assez d'historique",
        model_reference="lightgbm-abc123",
        created_at=CREATED_AT,
    )
    service = PredictionService(
        sites=FauxDepotSites([FauxSite("A", "Site A")]),  # type: ignore[arg-type]
        predictions=FauxDepotPredictions([insuffisante]),  # type: ignore[arg-type]
    )
    resume = await service.summary()
    site = resume.sites[0]
    assert site.prediction is not None
    assert site.prediction.status == "insufficient_data"
    assert site.prediction.predicted_value is None
    assert site.prediction.failure_reason == "pas assez d'historique"
 async def test_summary_covers_every_site_even_with_a_single_prediction_in_the_repository() -> None:
    service = PredictionService(
        sites=FauxDepotSites([FauxSite("A", "Site A"), FauxSite("B", "Site B")]),  # type: ignore[arg-type]
        predictions=FauxDepotPredictions([prediction_disponible("A")]),  # type: ignore[arg-type]
    )
    resume = await service.summary()
    par_site = {site.site_id: site for site in resume.sites}
    assert par_site["A"].prediction is not None
    assert par_site["B"].prediction is None
@@ -116,11 +116,13 @@ async def test_list_history_normalizes_naive_datetimes_to_utc() -> None:
 async def test_list_history_raises_when_start_is_after_end() -> None:
    service = ReadingService(readings=FakeRepository([]))
    debut = datetime(2026, 9, 2, tzinfo=UTC)
    fin = datetime(2026, 9, 1, tzinfo=UTC)
    with pytest.raises(FenetreInverseeError):
-        await service.list_history(start=debut, end=fin, limit=500, offset=0)
+        await service.list_history(
            start=datetime(2026, 9, 2, tzinfo=UTC),
            end=datetime(2026, 9, 1, tzinfo=UTC),
            limit=500,
            offset=0,
        )
 async def test_list_history_raises_when_start_equals_end() -> None:
@@ -1,14 +1,10 @@
 from collections.abc import Sequence
 from datetime import UTC, datetime
 import pytest
-from app.models.energy import Alert, Recommendation
+from app.models.energy import Recommendation
 from app.repositories.recommendation import NouvelleRecommandation
 from app.services.recommendation import RecommendationNotFoundError, RecommendationService
 MOMENT = datetime(2024, 1, 1, tzinfo=UTC)
 def recommendation(recommendation_id: int = 1) -> Recommendation:
    return Recommendation(
@@ -17,33 +13,13 @@ def recommendation(recommendation_id: int = 1) -> Recommendation:
        action="Vérifier la consommation",
        explanation="Pic détecté",
        rule_reference="spike-v1",
-        created_at=MOMENT,
+        created_at=datetime(2024, 1, 1, tzinfo=UTC),
    )
 def alerte(alert_id: int = 1, site_id: str = "SITE001", severity: str = "high") -> Alert:
    return Alert(
        alert_id=alert_id,
        source_alert_id=f"ALR-{alert_id}",
        site_id=site_id,
        source="api_mock",
        timestamp=MOMENT,
        type="spike",
        severity=severity,
        message="Pic de consommation",
        value=None,
        threshold=None,
        metric=None,
        prediction_id=None,
        raw_data={},
    )
 class FakeRepository:
-    def __init__(self, recommendations: list[Recommendation], creees: int | None = None) -> None:
+    def __init__(self, recommendations: list[Recommendation]) -> None:
        self._recommendations = recommendations
        self._creees = creees
        self.recues: list[NouvelleRecommandation] = []
    async def list_all(self) -> list[Recommendation]:
        return self._recommendations
@@ -53,111 +29,27 @@ class FakeRepository:
            (r for r in self._recommendations if r.recommendation_id == recommendation_id), None
        )
    async def create_missing(self, nouvelles: Sequence[NouvelleRecommandation]) -> int:
        self.recues = list(nouvelles)
        return len(self.recues) if self._creees is None else self._creees
 class FakeAlertRepository:
    def __init__(self, alertes: list[Alert]) -> None:
        self._alertes = alertes
        self.site_demande: str | None = None
    async def list_all(
        self, *, site_id: str | None = None, severity: str | None = None
    ) -> list[Alert]:
        self.site_demande = site_id
        if site_id is None:
            return self._alertes
        return [a for a in self._alertes if a.site_id == site_id]
 class FakeTransaction:
    def __init__(self) -> None:
        self.commits = 0
    async def commit(self) -> None:
        self.commits += 1
 def service(
    recommendations: FakeRepository | None = None,
    alerts: FakeAlertRepository | None = None,
    transaction: FakeTransaction | None = None,
 ) -> RecommendationService:
    return RecommendationService(
        recommendations=recommendations or FakeRepository([]),
        alerts=alerts or FakeAlertRepository([]),
        transaction=transaction or FakeTransaction(),
    )
 async def test_list_all_returns_the_repository_recommendations() -> None:
-    depot = FakeRepository([recommendation(1), recommendation(2)])
+    service = RecommendationService(
        recommendations=FakeRepository([recommendation(1), recommendation(2)])
    )
-    recommendations = await service(recommendations=depot).list_all()
+    recommendations = await service.list_all()
    assert [r.recommendation_id for r in recommendations] == [1, 2]
 async def test_get_by_id_returns_the_matching_recommendation() -> None:
-    trouve = await service(recommendations=FakeRepository([recommendation(1)])).get_by_id(1)
+    service = RecommendationService(recommendations=FakeRepository([recommendation(1)]))
    trouve = await service.get_by_id(1)
    assert trouve.recommendation_id == 1
 async def test_get_by_id_raises_when_the_recommendation_is_unknown() -> None:
    service = RecommendationService(recommendations=FakeRepository([]))
    with pytest.raises(RecommendationNotFoundError):
-        await service().get_by_id(404)
+        await service.get_by_id(404)
 async def test_generate_persists_one_proposal_per_triggered_rule() -> None:
    depot = FakeRepository([])
    rapport = await service(
        recommendations=depot, alerts=FakeAlertRepository([alerte(severity="critical")])
    ).generate()
    assert {n.rule_reference for n in depot.recues} == {
        "spike-delestage-v1",
        "escalade-astreinte-v1",
    }
    assert rapport.recommandations_creees == 2
 async def test_generate_commits_once() -> None:
    transaction = FakeTransaction()
    await service(alerts=FakeAlertRepository([alerte()]), transaction=transaction).generate()
    assert transaction.commits == 1
 async def test_generate_restricts_the_alerts_to_the_requested_site() -> None:
    alertes = FakeAlertRepository([alerte(1, site_id="SITE001"), alerte(2, site_id="SITE002")])
    depot = FakeRepository([])
    rapport = await service(recommendations=depot, alerts=alertes).generate(site_id="SITE002")
    assert alertes.site_demande == "SITE002"
    assert rapport.alertes_examinees == 1
    assert {n.alert_id for n in depot.recues} == {2}
 async def test_generate_reports_nothing_when_no_alert_matches() -> None:
    rapport = await service().generate()
    assert rapport.alertes_examinees == 0
    assert rapport.recommandations_creees == 0
    assert rapport.deja_presentes == 0
 async def test_generate_counts_the_proposals_the_database_already_held() -> None:
    depot = FakeRepository([], creees=0)
    rapport = await service(
        recommendations=depot, alerts=FakeAlertRepository([alerte()])
    ).generate()
    assert rapport.recommandations_creees == 0
    assert rapport.deja_presentes == 1
@@ -1,142 +0,0 @@
 from datetime import UTC, datetime
 import pytest
 from app.models.energy import Alert
 from app.services.recommendation_rules import FACTEUR_DEPASSEMENT_MAJEUR, applique_les_regles
 MOMENT = datetime(2024, 1, 1, tzinfo=UTC)
 def alerte(
    *,
    alert_id: int = 1,
    type_alerte: str = "spike",
    severity: str = "high",
    value: float | None = None,
    threshold: float | None = None,
    metric: str | None = None,
    site_id: str = "SITE001",
 ) -> Alert:
    return Alert(
        alert_id=alert_id,
        source_alert_id=f"ALR-{alert_id}",
        site_id=site_id,
        source="api_mock",
        timestamp=MOMENT,
        type=type_alerte,
        severity=severity,
        message="Alerte de test",
        value=value,
        threshold=threshold,
        metric=metric,
        prediction_id=None,
        raw_data={},
    )
@pytest.mark.parametrize(
    ("type_alerte", "attendue"),
    [
        ("spike", "spike-delestage-v1"),
        ("threshold", "threshold-reduction-v1"),
        ("outage", "outage-secours-v1"),
        ("sensor", "sensor-maintenance-v1"),
        ("anomaly", "anomaly-verification-v1"),
    ],
    ids=["pic", "seuil", "coupure", "capteur", "anomalie"],
 )
 def test_each_alert_type_yields_its_own_rule(type_alerte: str, attendue: str) -> None:
    proposees = applique_les_regles(alerte(type_alerte=type_alerte))
    assert [p.rule_reference for p in proposees] == [attendue]
 def test_a_critical_alert_adds_the_escalation_rule() -> None:
    proposees = applique_les_regles(alerte(severity="critical"))
    assert "escalade-astreinte-v1" in {p.rule_reference for p in proposees}
@pytest.mark.parametrize("severity", ["low", "medium", "high"], ids=["faible", "moyenne", "haute"])
 def test_a_non_critical_alert_does_not_escalate(severity: str) -> None:
    proposees = applique_les_regles(alerte(severity=severity))
    assert "escalade-astreinte-v1" not in {p.rule_reference for p in proposees}
 def test_a_large_overshoot_adds_the_contract_rule() -> None:
    proposees = applique_les_regles(
        alerte(value=720.0 * FACTEUR_DEPASSEMENT_MAJEUR, threshold=720.0)
    )
    assert "contrat-puissance-v1" in {p.rule_reference for p in proposees}
 def test_an_overshoot_below_the_factor_does_not_add_the_contract_rule() -> None:
    proposees = applique_les_regles(alerte(value=800.0, threshold=720.0))
    assert "contrat-puissance-v1" not in {p.rule_reference for p in proposees}
@pytest.mark.parametrize(
    ("value", "threshold"),
    [(None, 720.0), (900.0, None), (900.0, 0.0), (900.0, -10.0)],
    ids=["sans mesure", "sans seuil", "seuil nul", "seuil negatif"],
 )
 def test_the_contract_rule_stays_silent_without_an_exploitable_threshold(
    value: float | None, threshold: float | None
 ) -> None:
    proposees = applique_les_regles(alerte(value=value, threshold=threshold))
    assert "contrat-puissance-v1" not in {p.rule_reference for p in proposees}
 def test_the_explanation_quotes_the_measure_and_the_threshold() -> None:
    proposees = applique_les_regles(alerte(value=812.5, threshold=720.0, metric="consumption_kw"))
    assert "(consumption_kw mesurée à 812.5, seuil 720.0)" in proposees[0].explanation
 def test_the_explanation_quotes_the_measure_alone_when_no_threshold_is_known() -> None:
    proposees = applique_les_regles(alerte(value=812.5, metric="consumption_kw"))
    assert "(consumption_kw mesurée à 812.5)" in proposees[0].explanation
 def test_the_explanation_omits_the_measure_when_the_alert_carries_none() -> None:
    proposees = applique_les_regles(alerte())
    assert "(" not in proposees[0].explanation
 def test_the_explanation_names_the_site() -> None:
    proposees = applique_les_regles(alerte(site_id="SITE042"))
    assert "SITE042" in proposees[0].explanation
 def test_every_proposal_carries_the_alert_identifier() -> None:
    proposees = applique_les_regles(alerte(alert_id=77, severity="critical"))
    assert {p.alert_id for p in proposees} == {77}
 def test_an_alert_never_yields_the_same_rule_twice() -> None:
    proposees = applique_les_regles(
        alerte(severity="critical", value=900.0, threshold=720.0, metric="consumption_kw")
    )
    assert len(proposees) == len({p.rule_reference for p in proposees})
 def test_a_critical_alert_over_the_threshold_yields_the_three_rules() -> None:
    proposees = applique_les_regles(
        alerte(severity="critical", value=900.0, threshold=720.0, metric="consumption_kw")
    )
    assert {p.rule_reference for p in proposees} == {
        "spike-delestage-v1",
        "escalade-astreinte-v1",
        "contrat-puissance-v1",
    }
@@ -235,7 +235,5 @@ async def test_every_operation_refuses_an_unknown_account(action: str) -> None:
    if action == "set_active":
        arguments["is_active"] = False
    methode = getattr(attirail.service, action)
    with pytest.raises(UserNotFoundError):
-        await methode(**arguments)
+        await getattr(attirail.service, action)(**arguments)
@@ -19,17 +19,13 @@ def test_build_parser_reads_the_create_admin_arguments() -> None:
 def test_build_parser_requires_a_subcommand() -> None:
    parser = cli.build_parser()
    with pytest.raises(SystemExit):
-        parser.parse_args([])
+        cli.build_parser().parse_args([])
 def test_build_parser_requires_an_email() -> None:
    parser = cli.build_parser()
    with pytest.raises(SystemExit):
-        parser.parse_args(["create-admin"])
+        cli.build_parser().parse_args(["create-admin"])
 def test_read_password_generates_a_long_secret_when_asked(
@@ -122,30 +118,3 @@ def test_main_exports_the_contract_without_asking_for_a_password(
    assert code == 0
    assert destination.exists()
    assert str(destination) in capsys.readouterr().out
 def test_build_parser_reads_the_generate_recommendations_arguments() -> None:
    arguments = cli.build_parser().parse_args(["generate-recommendations", "--site-id", "SITE002"])
    assert arguments.commande == "generate-recommendations"
    assert arguments.site_id == "SITE002"
 def test_build_parser_defaults_the_generation_to_every_site() -> None:
    arguments = cli.build_parser().parse_args(["generate-recommendations"])
    assert arguments.site_id is None
 def test_main_generates_the_recommendations_without_asking_for_a_password(
    monkeypatch: pytest.MonkeyPatch, capsys: pytest.CaptureFixture[str]
 ) -> None:
    async def fausse_generation(*, site_id: str | None) -> str:
        return f"génération lancée pour {site_id}"
    monkeypatch.setattr(cli, "generate_recommendations", fausse_generation)
    code = cli.main(["generate-recommendations", "--site-id", "SITE002"])
    assert code == 0
    assert "SITE002" in capsys.readouterr().out
@@ -1,87 +0,0 @@
 from datetime import UTC, datetime
 import pytest
 from sqlalchemy import text
 from sqlalchemy.ext.asyncio import AsyncSession
 from app.db.session import get_session_factory
 from app.detection import internal_alerts
 from app.repositories.alert import AlertRepository
 from tests.repositories.test_reading import creer_lecture
 from tests.repositories.test_site import creer as creer_site
 def test_parse_args_defaults_to_no_site_and_no_instant() -> None:
    arguments = internal_alerts.parse_args([])
    assert arguments.site_id is None
    assert arguments.now is None
 def test_parse_args_reads_the_site_id() -> None:
    arguments = internal_alerts.parse_args(["--site-id", "site-1"])
    assert arguments.site_id == "site-1"
 def test_parse_args_parses_the_instant_option() -> None:
    arguments = internal_alerts.parse_args(["--now", "2026-09-16T12:00:00+00:00"])
    assert arguments.now == datetime(2026, 9, 16, 12, tzinfo=UTC)
 def test_parse_instant_treats_a_naive_datetime_as_utc() -> None:
    assert internal_alerts._parse_instant("2026-09-16T12:00:00") == datetime(
        2026, 9, 16, 12, tzinfo=UTC
    )
 def test_main_prints_how_many_alerts_were_recorded(
    monkeypatch: pytest.MonkeyPatch, capsys: pytest.CaptureFixture[str]
 ) -> None:
    async def fausse_execution(*, now: datetime | None, site_id: str | None) -> int:
        return 3
    monkeypatch.setattr(internal_alerts, "run_detection", fausse_execution)
    code = internal_alerts.main([])
    assert code == 0
    assert "3 nouvelle" in capsys.readouterr().out
@pytest.mark.integration
 async def test_run_detection_writes_a_threshold_alert_end_to_end(session: AsyncSession) -> None:
    # `run_detection` ouvre sa propre session et commite : `session.rollback()` seul ne défait
    # rien ici (contrairement au reste de la suite), d'où le nettoyage explicite ci-dessous, sur
    # le modèle de `tests/api/test_matrice_acces.py`.
    site = await creer_site(session, capacity_kw=100.0)
    site_id = site.site_id
    instant = datetime(2026, 9, 16, 12, tzinfo=UTC)
    await creer_lecture(session, site_id=site_id, timestamp=instant, consumption_kw=150.0)
    await session.commit()
    try:
        nombre = await internal_alerts.run_detection(now=instant, site_id=site_id)
        alertes = await AlertRepository(session).list_all(site_id=site_id)
        types = [a.type for a in alertes]
        await session.rollback()
        assert nombre == 1
        assert types == ["threshold"]
    finally:
        # `site.site_id` n'est plus sûr après `session.rollback()` : le rollback expire tous les
        # objets de la session (indépendamment d'`expire_on_commit`), et y accéder ici relance une
        # requête hors contexte async. D'où `site_id`, capturé avant.
        async with get_session_factory()() as nettoyage:
            await nettoyage.execute(
                text("delete from alert where site_id = :site_id"), {"site_id": site_id}
            )
            await nettoyage.execute(
                text("delete from reading where site_id = :site_id"), {"site_id": site_id}
            )
            await nettoyage.execute(
                text("delete from site where site_id = :site_id"), {"site_id": site_id}
            )
            await nettoyage.commit()
@@ -326,7 +326,6 @@ dependencies = [
    { name = "argon2-cffi" },
    { name = "asyncpg" },
    { name = "fastapi" },
    { name = "httpx" },
    { name = "pandas" },
    { name = "prometheus-fastapi-instrumentator" },
    { name = "pydantic", extra = ["email"] },
@@ -339,6 +338,7 @@ dependencies = [
 [package.dev-dependencies]
 dev = [
    { name = "httpx" },
    { name = "mypy" },
    { name = "pandas-stubs" },
    { name = "pytest" },
@@ -355,7 +355,6 @@ requires-dist = [
    { name = "argon2-cffi", specifier = ">=23.1" },
    { name = "asyncpg", specifier = ">=0.31.0" },
    { name = "fastapi", specifier = ">=0.141.1" },
    { name = "httpx", specifier = ">=0.28.1" },
    { name = "pandas", specifier = ">=3.0.5" },
    { name = "prometheus-fastapi-instrumentator", specifier = ">=8.1.0" },
    { name = "pydantic", extras = ["email"], specifier = ">=2.13.5" },
@@ -368,6 +367,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
    { name = "httpx", specifier = ">=0.28.1" },
    { name = "mypy", specifier = ">=2.3.1" },
    { name = "pandas-stubs", specifier = ">=3.0.5.260914" },
    { name = "pytest", specifier = ">=9.1.1" },
@@ -34,11 +34,6 @@
          },
          "configurations": {
            "production": {
              "optimization": {
                "styles": {
                  "inlineCritical": false
                }
              },
              "budgets": [
                {
                  "type": "initial",
@@ -1,18 +0,0 @@
 sonar.projectKey=ProjetPiscine_EnerVision
 sonar.organization=groupe3-ener-vision
 sonar.sourceEncoding=UTF-8
 #  Dossier contenant le code source
 sonar.sources=apps/frontend/src,apps/backend/app
 sonar.tests=apps/backend/tests
 #  Liste des fichiers et dossiers à exclure de l'analyse
 #  Liste des fichiers et dossiers à exclure de l'analyse
 sonar.exclusions=**/node_modules/**,**/dist/**,**/*.spec.js,**/*.test.js,github,db,ml,docker-compose.yml,**/**/Dockerfile,**/**/proxy.conf.json,**/**/package.json,**/**/angular.json
 #  Chemin vers le rapport de couverture de code
 #  Fichier généré par Vitest
 #  Chemin vers le rapport de couverture de code
 #  Fichier généré par Vitest
 sonar.javascript.lcov.reportPaths=apps/frontend/coverage/frontend/lcov.info
 sonar.python.coverage.reportPaths=apps/backend/cov.info
@@ -21,13 +21,15 @@ export const routes: Routes = [
    path: 'sites/:siteId',
    canActivate: [authGuard],
    loadComponent: () =>
-      import('./features/sites/site-detail/site-detail').then((m) => m.SiteDetail),
+      import('./features/sites/site-detail-placeholder/site-detail-placeholder').then(
        (m) => m.SiteDetailPlaceholder,
      ),
  },
  {
-    path: 'monitoring/sensors',
+  path: 'monitoring/sensors',
-    canActivate: [authGuard],
+  canActivate: [authGuard],
-    data: { role: 'admin' },
+  data: { role: 'admin' },
-    loadComponent: () =>
+  loadComponent: () =>
-      import('./features/monitoring/sensor-status/sensor-status').then((m) => m.SensorStatusView),
+    import('./features/monitoring/sensor-status/sensor-status').then((m) => m.SensorStatusView),
-  },
+},
 ];
@@ -64,13 +64,4 @@ describe('mockApiInterceptor', () => {
    httpMock.expectNone(`${environment.apiUrl}/alerts`);
    expect((result as unknown[]).length).toBeGreaterThan(0);
  });
  it('laisse toujours passer /predictions vers le réseau, même avec useMockFixtures activé', () => {
    environment.useMockFixtures = true;
    http.get(`${environment.apiUrl}/predictions`).subscribe();
    const req = httpMock.expectOne(`${environment.apiUrl}/predictions`);
    req.flush({ timestamp: '2026-09-18T09:00:00Z', sites: [] });
  });
 });
@@ -26,7 +26,5 @@ export const mockApiInterceptor: HttpInterceptorFn = (req, next) => {
  if (req.url.endsWith(`${environment.apiUrl}/alerts`)) {
    return of(new HttpResponse({ status: 200, body: ALERTS_FIXTURE }));
  }
  // Volontairement jamais mocké, contrairement à `stats`/`alerts` : les prévisions sont servies
  // par l'API réelle dès maintenant (au même titre que `/auth/*`, déjà toujours réel).
  return next(req);
 };
@@ -1,35 +0,0 @@
 import { TestBed } from '@angular/core/testing';
 import { provideHttpClient } from '@angular/common/http';
 import { provideHttpClientTesting, HttpTestingController } from '@angular/common/http/testing';
 import { PredictionsService } from './predictions.service';
 import { environment } from '../../../environments/environment';
 describe('PredictionsService', () => {
  let service: PredictionsService;
  let httpMock: HttpTestingController;
  beforeEach(() => {
    TestBed.configureTestingModule({
      providers: [provideHttpClient(), provideHttpClientTesting()],
    });
    service = TestBed.inject(PredictionsService);
    httpMock = TestBed.inject(HttpTestingController);
  });
  afterEach(() => httpMock.verify());
  it('appelle le bon endpoint et retourne un résumé de prévisions', () => {
    let result: unknown;
    service.getPredictions().subscribe((r) => (result = r));
    const req = httpMock.expectOne(`${environment.apiUrl}/predictions`);
    expect(req.request.method).toBe('GET');
    req.flush({
      timestamp: '2026-09-18T09:00:00Z',
      sites: [{ site_id: 'SITE001', site_name: 'Test', prediction: null }],
    });
    expect((result as { sites: unknown[] }).sites.length).toBe(1);
  });
 });
@@ -1,13 +0,0 @@
 import { Service, inject } from '@angular/core';
 import { HttpClient } from '@angular/common/http';
 import { environment } from '../../../environments/environment';
 import { PredictionSummary } from '../../shared/models/prediction.model';
@Service()
 export class PredictionsService {
  private http = inject(HttpClient);
  getPredictions() {
    return this.http.get<PredictionSummary>(`${environment.apiUrl}/predictions`);
  }
 }
@@ -1,50 +0,0 @@
 import { TestBed } from '@angular/core/testing';
 import { provideHttpClient } from '@angular/common/http';
 import { provideHttpClientTesting, HttpTestingController } from '@angular/common/http/testing';
 import { ReadingsService } from './readings.service';
 import { environment } from '../../../environments/environment';
 describe('ReadingsService', () => {
  let service: ReadingsService;
  let httpMock: HttpTestingController;
  beforeEach(() => {
    TestBed.configureTestingModule({
      providers: [provideHttpClient(), provideHttpClientTesting()],
    });
    service = TestBed.inject(ReadingsService);
    httpMock = TestBed.inject(HttpTestingController);
  });
  afterEach(() => httpMock.verify());
  it("demande l'historique du site avec la fenêtre temporelle donnée", () => {
    let result: unknown;
    service
      .getHistory('SITE001', '2026-09-16T00:00:00Z', '2026-09-17T00:00:00Z')
      .subscribe((r) => (result = r));
    const req = httpMock.expectOne(
      (r) => r.url === `${environment.apiUrl}/readings` && r.method === 'GET',
    );
    expect(req.request.params.get('site_id')).toBe('SITE001');
    expect(req.request.params.get('start')).toBe('2026-09-16T00:00:00Z');
    expect(req.request.params.get('end')).toBe('2026-09-17T00:00:00Z');
    req.flush([{ reading_id: 1, site_id: 'SITE001', consumption_kw: 12.5 }]);
    expect((result as unknown[]).length).toBe(1);
  });
  it('ne pose pas de paramètres start/end quand ils sont omis', () => {
    service.getHistory('SITE001').subscribe();
    const req = httpMock.expectOne(
      (r) => r.url === `${environment.apiUrl}/readings` && r.method === 'GET',
    );
    expect(req.request.params.has('start')).toBe(false);
    expect(req.request.params.has('end')).toBe(false);
    req.flush([]);
  });
 });
@@ -1,20 +0,0 @@
 import { Service, inject } from '@angular/core';
 import { HttpClient, HttpParams } from '@angular/common/http';
 import { environment } from '../../../environments/environment';
 import { Reading } from '../../shared/models/reading.model';
@Service()
 export class ReadingsService {
  private http = inject(HttpClient);
  getHistory(siteId: string, start?: string, end?: string) {
    let params = new HttpParams().set('site_id', siteId);
    if (start) {
      params = params.set('start', start);
    }
    if (end) {
      params = params.set('end', end);
    }
    return this.http.get<Reading[]>(`${environment.apiUrl}/readings`, { params });
  }
 }
@@ -38,50 +38,4 @@ describe('SitesService', () => {
    expect((result as { site_id: string }[])[0].site_id).toBe('SITE001');
  });
  it('appelle le bon endpoint et retourne un site', () => {
    let result: unknown;
    service.getSite('SITE001').subscribe((r) => (result = r));
    const req = httpMock.expectOne(`${environment.apiUrl}/sites/SITE001`);
    expect(req.request.method).toBe('GET');
    req.flush({
      site_id: 'SITE001',
      site_name: 'Site 1',
      site_type: 'industriel',
      location: 'Nantes',
      capacity_kw: 500,
      status: 'actif',
    });
    expect((result as { site_id: string }).site_id).toBe('SITE001');
  });
  it('appelle le bon endpoint et retourne la mesure courante du site', () => {
    let result: unknown;
    service.getCurrent('SITE001').subscribe((r) => (result = r));
    const req = httpMock.expectOne(`${environment.apiUrl}/sites/SITE001/current`);
    expect(req.request.method).toBe('GET');
    req.flush({
      timestamp: '2026-09-17T10:00:00Z',
      site_id: 'SITE001',
      site_type: 'industriel',
      consumption_kw: 120,
      consumption_kwh: null,
      voltage_v: null,
      current_a: null,
      power_factor: null,
      temperature_celsius: 22,
      humidity_percent: 55,
      null_reasons: ['electrical_sensor_failure'],
      data_quality: 'partial',
    });
    expect((result as { null_reasons: string[] }).null_reasons).toEqual([
      'electrical_sensor_failure',
    ]);
  });
 });
@@ -2,7 +2,6 @@ import { Service, inject } from '@angular/core';
 import { HttpClient } from '@angular/common/http';
 import { environment } from '../../../environments/environment';
 import { Site } from '../../shared/models/site.model';
 import { SiteCurrent } from '../../shared/models/site-current.model';
@Service()
 export class SitesService {
@@ -11,12 +10,4 @@ export class SitesService {
  getSites() {
    return this.http.get<Site[]>(`${environment.apiUrl}/sites`);
  }
  getSite(siteId: string) {
    return this.http.get<Site>(`${environment.apiUrl}/sites/${siteId}`);
  }
  getCurrent(siteId: string) {
    return this.http.get<SiteCurrent>(`${environment.apiUrl}/sites/${siteId}/current`);
  }
 }
@@ -12,7 +12,7 @@
    <div class="dashboard__actions">
      @if (auth.principal()?.role === 'admin') {
        <a routerLink="/monitoring/sensors" class="ev-link">Supervision des capteurs</a>
-      }
+       }
      <a routerLink="/sites" class="ev-link">Voir les sites</a>
      <ev-button
        class="logout-button"
@@ -24,13 +24,7 @@
    </div>
  </header>
-  @if (statsError(); as message) {
+  @if (error(); as message) {
    <ev-alert severity="danger" class="banner-error">{{ message }}</ev-alert>
  }
  @if (alertsError(); as message) {
    <ev-alert severity="danger" class="banner-error">{{ message }}</ev-alert>
  }
  @if (predictionsError(); as message) {
    <ev-alert severity="danger" class="banner-error">{{ message }}</ev-alert>
  }
@@ -81,33 +75,4 @@
      </ul>
    </section>
  }
  @if (predictions().length > 0) {
    <section class="predictions-section">
      <h2>Prévisions de consommation</h2>
      <ul class="predictions-list">
        @for (site of predictions(); track site.site_id) {
          <li class="prediction-item">
            <span class="prediction-item__site">{{ site.site_name }}</span>
            @if (site.prediction; as prediction) {
              @if (prediction.status === 'available') {
                <span class="prediction-item__value">
                  {{ prediction.predicted_value | number: '1.0-1' }} kWh
                  <span class="prediction-item__target"
                    >{{ prediction.target_at | date: "dd/MM 'à' HH:mm" }}</span
                  >
                </span>
              } @else {
                <ev-badge [tone]="badgeToneForPredictionStatus(prediction.status)">{{
                  prediction.status === 'insufficient_data' ? 'Historique insuffisant' : 'Erreur'
                }}</ev-badge>
              }
            } @else {
              <ev-badge tone="neutral">Pas encore de prévision</ev-badge>
            }
          </li>
        }
      </ul>
    </section>
  }
 </div>
@@ -130,40 +130,3 @@ h2 {
 .alert-item__message {
  font-size: 0.9rem;
 }
 .predictions-list {
  list-style: none;
  margin: 0;
  padding: 0;
  display: flex;
  flex-direction: column;
  gap: 0.5rem;
 }
 .prediction-item {
  display: flex;
  align-items: center;
  justify-content: space-between;
  gap: 0.75rem;
  padding: 0.7rem 1rem;
  border-radius: var(--radius-md);
  background: var(--color-surface);
  border: 1px solid var(--color-border-light);
 }
 .prediction-item__site {
  font-size: 0.9rem;
  font-weight: 600;
 }
 .prediction-item__value {
  font-size: 0.9rem;
  font-weight: 600;
 }
 .prediction-item__target {
  margin-left: 0.35rem;
  font-size: 0.8rem;
  font-weight: 400;
  color: var(--color-text-muted);
 }
@@ -4,7 +4,6 @@ import { of, throwError } from 'rxjs';
 import { Dashboard } from './dashboard';
 import { StatsService } from '../../core/services/stats.service';
 import { AlertsService } from '../../core/services/alerts.service';
 import { PredictionsService } from '../../core/services/predictions.service';
 import {AuthService} from '../../core/services/auth.service';
 import {Router, provideRouter} from '@angular/router';
@@ -18,24 +17,18 @@ vi.mock('chart.js', () => {
  return { Chart: ChartMock, registerables: [] };
 });
 function predictionsMock(sites: unknown[] = []) {
  return { getPredictions: vi.fn().mockReturnValue(of({ timestamp: '2026-09-18T09:00:00Z', sites })) };
 }
 describe('Dashboard', () => {
  afterEach(() => vi.useRealTimers());
-  it('charge les stats, les alertes et les prévisions au démarrage', async () => {
+  it('charge les stats et les alertes au démarrage', async () => {
    const statsMock = { getSummary: vi.fn().mockReturnValue(of({ total_sites: 7, sites: [] })) };
    const alertsMock = { getAlerts: vi.fn().mockReturnValue(of([{ alert_id: 'A1' }])) };
    const predictions = predictionsMock([{ site_id: 'SITE001', site_name: 'Test', prediction: null }]);
    TestBed.configureTestingModule({
      imports: [Dashboard],
      providers: [
        { provide: StatsService, useValue: statsMock },
        { provide: AlertsService, useValue: alertsMock },
        { provide: PredictionsService, useValue: predictions },
        provideRouter([]),
      ],
    });
@@ -49,12 +42,8 @@ describe('Dashboard', () => {
    expect(statsMock.getSummary).toHaveBeenCalled();
    expect(alertsMock.getAlerts).toHaveBeenCalled();
    expect(predictions.getPredictions).toHaveBeenCalled();
    expect(fixture.componentInstance.alerts().length).toBe(1);
-    expect(fixture.componentInstance.predictions().length).toBe(1);
+    expect(fixture.componentInstance.error()).toBeNull();
    expect(fixture.componentInstance.statsError()).toBeNull();
    expect(fixture.componentInstance.alertsError()).toBeNull();
    expect(fixture.componentInstance.predictionsError()).toBeNull();
  });
  it("signale l'indisponibilité puis repart au rafraîchissement suivant", () => {
@@ -72,7 +61,6 @@ describe('Dashboard', () => {
      providers: [
        { provide: StatsService, useValue: statsMock },
        { provide: AlertsService, useValue: alertsMock },
        { provide: PredictionsService, useValue: predictionsMock() },
        provideRouter([]),
      ],
    });
@@ -82,13 +70,13 @@ describe('Dashboard', () => {
    vi.advanceTimersByTime(1);
    expect(statsMock.getSummary).toHaveBeenCalledTimes(1);
-    expect(fixture.componentInstance.statsError()).not.toBeNull();
+    expect(fixture.componentInstance.error()).not.toBeNull();
    expect(fixture.componentInstance.stats()).toBeNull();
    vi.advanceTimersByTime(10000);
    expect(statsMock.getSummary).toHaveBeenCalledTimes(2);
    expect(fixture.componentInstance.stats()).not.toBeNull();
-    expect(fixture.componentInstance.statsError()).toBeNull();
+    expect(fixture.componentInstance.error()).toBeNull();
  });
  it("n'interrompt pas la page quand le chargement des alertes échoue", () => {
@@ -100,7 +88,6 @@ describe('Dashboard', () => {
      providers: [
        { provide: StatsService, useValue: statsMock },
        { provide: AlertsService, useValue: alertsMock },
        { provide: PredictionsService, useValue: predictionsMock() },
        provideRouter([]),
      ],
    });
@@ -109,62 +96,6 @@ describe('Dashboard', () => {
    fixture.detectChanges();
    expect(fixture.componentInstance.alerts().length).toBe(0);
    expect(fixture.componentInstance.alertsError()).not.toBeNull();
  });
  it("n'interrompt pas la page quand le chargement des prévisions échoue", () => {
    const statsMock = { getSummary: vi.fn().mockReturnValue(of({ total_sites: 7, sites: [] })) };
    const alertsMock = { getAlerts: vi.fn().mockReturnValue(of([])) };
    const predictions = {
      getPredictions: vi.fn().mockReturnValue(throwError(() => new Error('nope'))),
    };
    TestBed.configureTestingModule({
      imports: [Dashboard],
      providers: [
        { provide: StatsService, useValue: statsMock },
        { provide: AlertsService, useValue: alertsMock },
        { provide: PredictionsService, useValue: predictions },
        provideRouter([]),
      ],
    });
    const fixture = TestBed.createComponent(Dashboard);
    fixture.detectChanges();
    expect(fixture.componentInstance.predictions().length).toBe(0);
    expect(fixture.componentInstance.predictionsError()).not.toBeNull();
  });
  it("un rafraîchissement de stats n'efface pas une erreur de prévisions en attente", () => {
    vi.useFakeTimers();
    const statsMock = { getSummary: vi.fn().mockReturnValue(of({ total_sites: 7, sites: [] })) };
    const alertsMock = { getAlerts: vi.fn().mockReturnValue(of([])) };
    const predictions = {
      getPredictions: vi.fn().mockReturnValue(throwError(() => new Error('nope'))),
    };
    TestBed.configureTestingModule({
      imports: [Dashboard],
      providers: [
        { provide: StatsService, useValue: statsMock },
        { provide: AlertsService, useValue: alertsMock },
        { provide: PredictionsService, useValue: predictions },
        provideRouter([]),
      ],
    });
    const fixture = TestBed.createComponent(Dashboard);
    fixture.detectChanges();
    expect(fixture.componentInstance.predictionsError()).not.toBeNull();
    // Plusieurs cycles de `timer(0, 10_000)` (stats) plus tard, l'erreur des prévisions doit
    // toujours être visible : rien ne vient la rafraîchir tant que la section n'est pas rechargée.
    vi.advanceTimersByTime(30000);
    expect(fixture.componentInstance.predictionsError()).not.toBeNull();
    expect(fixture.componentInstance.statsError()).toBeNull();
  });
  it('appelle logout et redirige vers /login au clic sur le bouton de déconnexion', () => {
@@ -180,7 +111,6 @@ describe('Dashboard', () => {
    providers: [
      { provide: StatsService, useValue: statsMock },
      { provide: AlertsService, useValue: alertsMock },
      { provide: PredictionsService, useValue: predictionsMock() },
      { provide: AuthService, useValue: authMock },
      provideRouter([]),
    ],
@@ -211,7 +141,6 @@ describe('Dashboard', () => {
    providers: [
      { provide: StatsService, useValue: statsMock },
      { provide: AlertsService, useValue: alertsMock },
      { provide: PredictionsService, useValue: predictionsMock() },
      { provide: AuthService, useValue: authMock },
      provideRouter([]),
    ],
@@ -239,7 +168,6 @@ describe('Dashboard', () => {
      providers: [
        { provide: StatsService, useValue: statsMock },
        { provide: AlertsService, useValue: alertsMock },
        { provide: PredictionsService, useValue: predictionsMock() },
        provideRouter([]),
      ],
    });
@@ -255,26 +183,4 @@ describe('Dashboard', () => {
      dashboard.badgeToneForSeverity('critical'),
    );
  });
  it('distingue le ton des statuts de prévision', () => {
    const statsMock = { getSummary: vi.fn().mockReturnValue(of({ total_sites: 7, sites: [] })) };
    const alertsMock = { getAlerts: vi.fn().mockReturnValue(of([])) };
    TestBed.configureTestingModule({
      imports: [Dashboard],
      providers: [
        { provide: StatsService, useValue: statsMock },
        { provide: AlertsService, useValue: alertsMock },
        { provide: PredictionsService, useValue: predictionsMock() },
        provideRouter([]),
      ],
    });
    const fixture = TestBed.createComponent(Dashboard);
    const dashboard = fixture.componentInstance;
    expect(dashboard.badgeToneForPredictionStatus('available')).toBe('success');
    expect(dashboard.badgeToneForPredictionStatus('insufficient_data')).toBe('warning');
    expect(dashboard.badgeToneForPredictionStatus('error')).toBe('danger');
  });
 });
@@ -1,17 +1,15 @@
-import { Component, OnInit, inject, signal, DestroyRef, WritableSignal } from '@angular/core';
+import { Component, OnInit, inject, signal, DestroyRef } from '@angular/core';
 import { takeUntilDestroyed } from '@angular/core/rxjs-interop';
 import { timer, switchMap, catchError, EMPTY, Observable } from 'rxjs';
-import { DecimalPipe, DatePipe } from '@angular/common';
+import { DecimalPipe } from '@angular/common';
 import { Router, RouterLink } from '@angular/router';
 import { StatsService } from '../../core/services/stats.service';
 import { ConsumptionGauge } from '../../shared/components/consumption-gauge/consumption-gauge';
 import { SiteLoadChart } from '../../shared/components/site-load-chart/site-load-chart';
 import { AlertsService } from '../../core/services/alerts.service';
 import { PredictionsService } from '../../core/services/predictions.service';
 import { AuthService } from '../../core/services/auth.service';
 import { StatsSummary } from '../../shared/models/stats.model';
 import { Alert, AlertSeverity } from '../../shared/models/alert.model';
 import { PredictionStatus, SitePredictionSummary } from '../../shared/models/prediction.model';
 import { Card } from '../../shared/components/ui/card/card';
 import { Alert as EvAlert } from '../../shared/components/ui/alert/alert';
 import { Badge, BadgeTone } from '../../shared/components/ui/badge/badge';
@@ -29,21 +27,11 @@ const TON_PAR_SEVERITE: Record<AlertSeverity, BadgeTone> = {
  critical: 'critical',
 };
 // `error` n'a pas de précédent dans les fixtures ou l'API à ce jour, mais figure dans le
 // domaine du schéma backend (`ck_prediction_status`) : mieux vaut une couleur définie que
 // tomber sur `undefined` si ce statut apparaît un jour.
 const TON_PAR_STATUT_PREDICTION: Record<PredictionStatus, BadgeTone> = {
  available: 'success',
  insufficient_data: 'warning',
  error: 'danger',
 };
@Component({
  selector: 'app-dashboard',
  standalone: true,
  imports: [
    DecimalPipe,
    DatePipe,
    RouterLink,
    ConsumptionGauge,
    SiteLoadChart,
@@ -60,51 +48,30 @@ export class Dashboard implements OnInit {
  private statsService = inject(StatsService);
  private alertsService = inject(AlertsService);
  public auth = inject(AuthService);
  private predictionsService = inject(PredictionsService);
  private router = inject(Router);
  private destroyRef = inject(DestroyRef);
  stats = signal<StatsSummary | null>(null);
  alerts = signal<Alert[]>([]);
-  predictions = signal<SitePredictionSummary[]>([]);
+  error = signal<string | null>(null);
  // Un signal par flux, pas un seul `error` partagé : sinon le tick suivant de `timer` (stats)
  // efface silencieusement un message d'échec des prévisions ou des alertes après 10s au plus,
  // sans retry ni indication pour l'utilisateur que la section correspondante est restée vide.
  statsError = signal<string | null>(null);
  alertsError = signal<string | null>(null);
  predictionsError = signal<string | null>(null);
  ngOnInit(): void {
    this.alertsService
      .getAlerts()
-      .pipe(catchError(() => this.reportUnavailable(this.alertsError)))
+      .pipe(catchError(() => this.reportUnavailable()))
-      .subscribe((alerts) => {
+      .subscribe((alerts) => this.alerts.set(alerts));
        this.alertsError.set(null);
        this.alerts.set(alerts);
      });
    // Les prévisions viennent d'un scoring hors ligne, pas d'un calcul à la demande : un seul
    // chargement au démarrage suffit, pas besoin du rafraîchissement périodique de `stats`.
    this.predictionsService
      .getPredictions()
      .pipe(catchError(() => this.reportUnavailable(this.predictionsError)))
      .subscribe((summary) => {
        this.predictionsError.set(null);
        this.predictions.set(summary.sites);
      });
    // Piège : le catchError porte sur l'observable interne. Sur le flux externe il
    // terminerait le timer, et le rafraîchissement ne repartirait jamais.
    timer(0, REFRESH_INTERVAL_MS)
      .pipe(
        switchMap(() =>
-          this.statsService.getSummary().pipe(catchError(() => this.reportUnavailable(this.statsError))),
+          this.statsService.getSummary().pipe(catchError(() => this.reportUnavailable())),
        ),
        takeUntilDestroyed(this.destroyRef),
      )
      .subscribe((stats) => {
-        this.statsError.set(null);
+        this.error.set(null);
        this.stats.set(stats);
      });
  }
@@ -113,10 +80,6 @@ export class Dashboard implements OnInit {
    return TON_PAR_SEVERITE[severity];
  }
  badgeToneForPredictionStatus(status: PredictionStatus): BadgeTone {
    return TON_PAR_STATUT_PREDICTION[status];
  }
  onLogout(): void {
    this.auth.logout().subscribe({
      next: () => this.router.navigate(['/login']),
@@ -128,8 +91,8 @@ export class Dashboard implements OnInit {
    });
  }
-  private reportUnavailable(target: WritableSignal<string | null>): Observable<never> {
+  private reportUnavailable(): Observable<never> {
-    target.set(UNAVAILABLE_MESSAGE);
+    this.error.set(UNAVAILABLE_MESSAGE);
    return EMPTY;
  }
 }
@@ -28,17 +28,15 @@
          <ul class="sensor-list">
            @for (entry of sensorEntries; track entry[0]) {
              @let diagnostic = sensorOf(site.sensors, entry[0]);
              <li class="sensor-item">
-                <span class="sensor-dot" [class]="'sensor-dot--' + diagnostic.status"></span>
+                <span
                  class="sensor-dot"
                  [class]="'sensor-dot--' + sensorOf(site.sensors, entry[0]).status"
                ></span>
                <span class="sensor-item__label">{{ entry[1] }}</span>
-                @if (diagnostic.status === 'failing') {
+                @if (sensorOf(site.sensors, entry[0]).status === 'failing') {
                  <span class="sensor-item__since">
-                    @if (diagnostic.since; as since) {
+                    depuis {{ sensorOf(site.sensors, entry[0]).since | date: 'short' }}
                      dernière lecture le {{ since | date: 'dd/MM/yyyy HH:mm' }}
                    } @else {
                      aucune lecture reçue
                    }
                  </span>
                }
              </li>
@@ -79,44 +79,21 @@ describe('SensorStatusView', () => {
    expect(component.sensorOf(OK_SENSORS, 'temperature')).toEqual({ status: 'ok', since: null });
  });
-  it('affiche la date de la dernière lecture reçue pour un capteur en panne', () => {
+  it('affiche la date depuis quand un capteur est en panne', () => {
-    const sensors: SiteSensors = {
+  const sensors: SiteSensors = {
-      ...OK_SENSORS,
+    ...OK_SENSORS,
-      temperature: { status: 'failing', since: '2026-09-18T08:00:00' },
+    temperature: { status: 'failing', since: '2026-09-18T08:00:00' },
-    };
+  };
-    sensorsMock.getStatus.mockReturnValue(
+  sensorsMock.getStatus.mockReturnValue(
-      of({
+    of({
-        timestamp: '2026-09-18T08:00:00',
+      timestamp: '2026-09-18T08:00:00',
-        sites: [{ site_id: 'SITE001', site_name: 'Bureau Test', overall: 'degraded', sensors }],
+      sites: [{ site_id: 'SITE001', site_name: 'Bureau Test', overall: 'degraded', sensors }],
-      })
+    })
-    );
+  );
-    const fixture = TestBed.createComponent(SensorStatusView);
+  const fixture = TestBed.createComponent(SensorStatusView);
-    fixture.detectChanges();
+  fixture.detectChanges();
-    expect(fixture.nativeElement.textContent).toContain('dernière lecture le');
+  expect(fixture.nativeElement.textContent).toContain('depuis');
    expect(fixture.nativeElement.textContent).toContain('18/09/2026 08:00');
  });
  it("annonce l'absence de lecture quand un site n'en a jamais reçu", () => {
    const sensors: SiteSensors = {
      consumption: { status: 'failing', since: null },
      electrical: { status: 'failing', since: null },
      temperature: { status: 'failing', since: null },
      humidity: { status: 'failing', since: null },
      network: { status: 'failing', since: null },
    };
    sensorsMock.getStatus.mockReturnValue(
      of({
        timestamp: '2026-09-18T08:00:00',
        sites: [{ site_id: 'SITE001', site_name: 'Bureau Test', overall: 'critical', sensors }],
      })
    );
    const fixture = TestBed.createComponent(SensorStatusView);
    fixture.detectChanges();
    expect(fixture.nativeElement.textContent).toContain('aucune lecture reçue');
    expect(fixture.nativeElement.textContent).not.toContain('dernière lecture le');
  });
 });
@@ -0,0 +1,19 @@
 <div class="site-detail-placeholder">
  <nav class="ev-breadcrumb">
    <a routerLink="/dashboard">Tableau de bord</a>
    <span>/</span>
    <a routerLink="/sites">Sites</a>
  </nav>
  <header class="site-detail-placeholder__header">
    <a routerLink="/dashboard" class="ev-brand-link">
      <ev-brand class="site-detail-placeholder__logo" />
    </a>
    <h1>Site {{ siteId() }}</h1>
  </header>
  <ev-card>
    <p>Le détail de ce site est à venir (voir issue #51).</p>
    <a routerLink="/sites" class="ev-link">Retour aux sites</a>
  </ev-card>
 </div>
@@ -0,0 +1,28 @@
 :host {
  display: block;
  color: var(--color-text);
  padding: 2.5rem 2rem;
  max-width: 640px;
  margin: 0 auto;
 }
 .site-detail-placeholder__header {
  display: flex;
  align-items: center;
  gap: 0.85rem;
  margin-bottom: 1.5rem;
  h1 {
    margin: 0;
    font-size: 1.5rem;
    font-weight: 700;
  }
 }
 .site-detail-placeholder__logo {
  font-size: 1.3rem;
 }
 ev-card p {
  margin: 0 0 0.75rem;
 }
@@ -0,0 +1,42 @@
 import { TestBed } from '@angular/core/testing';
 import { ActivatedRoute, convertToParamMap, provideRouter } from '@angular/router';
 import { BehaviorSubject } from 'rxjs';
 import { SiteDetailPlaceholder } from './site-detail-placeholder';
 describe('SiteDetailPlaceholder', () => {
  it("affiche l'identifiant du site depuis la route", () => {
    const paramMap = new BehaviorSubject(convertToParamMap({ siteId: 'SITE001' }));
    TestBed.configureTestingModule({
      imports: [SiteDetailPlaceholder],
      providers: [
        provideRouter([]),
        { provide: ActivatedRoute, useValue: { paramMap } },
      ],
    });
    const fixture = TestBed.createComponent(SiteDetailPlaceholder);
    fixture.detectChanges();
    expect(fixture.nativeElement.textContent).toContain('SITE001');
  });
  it('met à jour l\'affichage quand le paramètre change sans recréer le composant', () => {
    const paramMap = new BehaviorSubject(convertToParamMap({ siteId: 'SITE001' }));
    TestBed.configureTestingModule({
      imports: [SiteDetailPlaceholder],
      providers: [
        provideRouter([]),
        { provide: ActivatedRoute, useValue: { paramMap } },
      ],
    });
    const fixture = TestBed.createComponent(SiteDetailPlaceholder);
    fixture.detectChanges();
    paramMap.next(convertToParamMap({ siteId: 'SITE002' }));
    fixture.detectChanges();
    expect(fixture.nativeElement.textContent).toContain('SITE002');
    expect(fixture.nativeElement.textContent).not.toContain('SITE001');
  });
 });
@@ -0,0 +1,19 @@
 import { Component, inject } from '@angular/core';
 import { toSignal } from '@angular/core/rxjs-interop';
 import { ActivatedRoute, RouterLink } from '@angular/router';
 import { map } from 'rxjs';
 import { Card } from '../../../shared/components/ui/card/card';
 import { Brand } from '../../../shared/components/ui/brand/brand';
@Component({
  selector: 'app-site-detail-placeholder',
  standalone: true,
  imports: [RouterLink, Card, Brand],
  templateUrl: './site-detail-placeholder.html',
  styleUrl: './site-detail-placeholder.scss',
 })
 export class SiteDetailPlaceholder {
  private route = inject(ActivatedRoute);
  siteId = toSignal(this.route.paramMap.pipe(map((params) => params.get('siteId'))));
 }
@@ -1,85 +0,0 @@
 <div class="site-detail">
  <nav class="ev-breadcrumb">
    <a routerLink="/dashboard">Tableau de bord</a>
    <span>/</span>
    <a routerLink="/sites">Sites</a>
  </nav>
  <header class="site-detail__header">
    <a routerLink="/dashboard" class="ev-brand-link">
      <ev-brand class="site-detail__logo" />
    </a>
    <div>
      <h1>{{ site()?.site_name ?? siteId() }}</h1>
      @if (site(); as s) {
        <p class="site-detail__subtitle">
          {{ s.site_type }} · {{ s.location || 'Localisation inconnue' }}
        </p>
      }
    </div>
    <div class="site-detail__badges">
      @if (site(); as s) {
        <ev-badge [tone]="badgeToneForStatus(s.status)">{{ s.status ?? '-' }}</ev-badge>
      }
      @if (hasMeasurement() && qualityLabel(); as label) {
        <ev-badge [tone]="qualityTone()">{{ label }}</ev-badge>
      }
    </div>
  </header>
  @if (error(); as message) {
    <ev-alert severity="danger" class="banner-error">{{ message }}</ev-alert>
  }
  @if (site(); as s) {
    @if (hasMeasurement()) {
      <section class="overview">
        <ev-card class="card card--gauge">
          <span class="card__label">Consommation vs capacité</span>
          @let consumption = consumptionKw();
          @if (consumption !== null) {
            <app-consumption-gauge [consumption]="consumption" [capacity]="s.capacity_kw ?? 0" />
            <span class="card__value">
              {{ consumptionLabel() }} / {{ s.capacity_kw ?? '-' }} kW
            </span>
          } @else {
            <p class="card__unavailable">
              Consommation indisponible
              <span class="metric__reason">({{ consumptionReason() }})</span>
            </p>
          }
        </ev-card>
        <ev-card class="metrics-card">
          <span class="card__label">Mesure instantanée</span>
          <dl class="metrics-grid">
            @for (metric of metrics(); track metric.key) {
              <div class="metric">
                <dt>{{ metric.label }}</dt>
                @if (metric.value !== null) {
                  <dd>{{ metric.value }}</dd>
                } @else {
                  <dd class="metric__unavailable">
                    Indisponible
                    <span class="metric__reason">({{ metric.reason }})</span>
                  </dd>
                }
              </div>
            }
          </dl>
        </ev-card>
      </section>
      @if (history().length > 0) {
        <section class="chart-section">
          <h2>Historique de consommation</h2>
          <app-reading-history-chart [readings]="history()" />
        </section>
      }
    } @else {
      <ev-alert severity="warning" class="banner-empty">{{ noMeasurementMessage }}</ev-alert>
    }
  }
  <a routerLink="/sites" class="ev-link">Retour aux sites</a>
 </div>
@@ -1,119 +0,0 @@
 :host {
  display: block;
  color: var(--color-text);
  padding: 2.5rem 2rem;
  max-width: 1100px;
  margin: 0 auto;
 }
 .site-detail__header {
  display: flex;
  align-items: center;
  gap: 0.85rem;
  margin-bottom: 2rem;
  h1 {
    margin: 0;
    font-size: 1.75rem;
    font-weight: 700;
  }
 }
 .site-detail__logo {
  font-size: 1.3rem;
 }
 .site-detail__subtitle {
  margin: 0.25rem 0 0;
  color: var(--color-text-muted);
 }
 .site-detail__badges {
  display: flex;
  align-items: center;
  gap: 0.5rem;
  margin-left: auto;
 }
 .banner-error {
  display: block;
  margin: 0 0 1.5rem;
 }
 .banner-empty {
  display: block;
  margin: 0 0 1.5rem;
 }
 .overview {
  display: grid;
  grid-template-columns: repeat(auto-fit, minmax(260px, 1fr));
  gap: 1rem;
  margin-bottom: 2.5rem;
 }
 .card {
  padding: 1.25rem;
  gap: 0.35rem;
 }
 .card--gauge {
  align-items: center;
  text-align: center;
 }
 .card__label {
  font-size: 0.8rem;
  color: var(--color-text-muted);
  text-transform: uppercase;
  letter-spacing: 0.02em;
 }
 .card__value {
  font-size: 1.6rem;
  font-weight: 700;
 }
 .card__unavailable {
  color: var(--color-text-muted);
  margin: 0;
 }
 .metrics-grid {
  display: grid;
  grid-template-columns: repeat(2, 1fr);
  gap: 0.75rem 1.5rem;
  margin: 0.5rem 0 0;
 }
 .metric {
  dt {
    font-size: 0.75rem;
    color: var(--color-text-muted);
  }
  dd {
    margin: 0;
    font-size: 1.05rem;
    font-weight: 600;
  }
 }
 .metric__unavailable {
  color: var(--color-text-muted);
  font-weight: 400;
 }
 .metric__reason {
  font-size: 0.8rem;
 }
 h2 {
  font-size: 1.1rem;
  font-weight: 600;
  margin: 0 0 1rem;
 }
 .chart-section {
  margin-bottom: 2rem;
 }
@@ -1,281 +0,0 @@
 import { TestBed } from '@angular/core/testing';
 import { ActivatedRoute, convertToParamMap, provideRouter } from '@angular/router';
 import { vi } from 'vitest';
 import { BehaviorSubject, of, throwError } from 'rxjs';
 import { SiteDetail } from './site-detail';
 import { SitesService } from '../../../core/services/sites.service';
 import { ReadingsService } from '../../../core/services/readings.service';
 const SITE = {
  site_id: 'SITE001',
  site_name: 'Site 1',
  site_type: 'industriel',
  location: 'Nantes',
  capacity_kw: 500,
  status: 'actif',
 };
 const CURRENT_COMPLET = {
  timestamp: '2026-09-17T10:00:00Z',
  site_id: 'SITE001',
  site_type: 'industriel',
  consumption_kw: 120,
  consumption_kwh: null,
  voltage_v: 230,
  current_a: 12,
  power_factor: 0.95,
  temperature_celsius: 22,
  humidity_percent: 55,
  null_reasons: [] as string[],
  data_quality: 'good' as const,
 };
 const SANS_MESURE = {
  ...CURRENT_COMPLET,
  timestamp: null,
  consumption_kw: null,
  voltage_v: null,
  current_a: null,
  power_factor: null,
  temperature_celsius: null,
  humidity_percent: null,
  data_quality: 'critical' as const,
 };
 const LECTURE = {
  reading_id: 1,
  site_id: 'SITE001',
  timestamp: '2026-09-17T09:00:00Z',
  source: 'api_history' as const,
  consumption_kw: 118,
  consumption_kwh: null,
  consumption_euros: null,
  voltage_v: 230,
  current_a: 12,
  power_factor: 0.95,
  temperature_celsius: 22,
  humidity_percent: 55,
  solar_irradiance_wm2: null,
  is_working_hours: true,
  data_quality: 'good' as const,
  null_reasons: null,
  imputed_values: null,
  imputation_method: null,
 };
 function setup(
  siteId: string,
  sitesMock: Partial<SitesService>,
  readingsMock: Partial<ReadingsService>,
 ) {
  const paramMap = new BehaviorSubject(convertToParamMap({ siteId }));
  TestBed.configureTestingModule({
    imports: [SiteDetail],
    providers: [
      provideRouter([]),
      { provide: ActivatedRoute, useValue: { paramMap } },
      { provide: SitesService, useValue: sitesMock },
      { provide: ReadingsService, useValue: readingsMock },
    ],
  });
  return { fixture: TestBed.createComponent(SiteDetail), paramMap };
 }
 describe('SiteDetail', () => {
  it('charge le site, la mesure courante et son historique au démarrage', () => {
    const { fixture } = setup(
      'SITE001',
      {
        getSite: vi.fn().mockReturnValue(of(SITE)),
        getCurrent: vi.fn().mockReturnValue(of(CURRENT_COMPLET)),
      },
      { getHistory: vi.fn().mockReturnValue(of([LECTURE])) },
    );
    fixture.detectChanges();
    expect(fixture.componentInstance.site()?.site_id).toBe('SITE001');
    expect(fixture.componentInstance.current()?.consumption_kw).toBe(120);
    expect(fixture.componentInstance.history().length).toBe(1);
    expect(fixture.componentInstance.error()).toBeNull();
  });
  it("signale l'indisponibilité quand un des appels échoue", () => {
    const { fixture } = setup(
      'SITE001',
      {
        getSite: vi.fn().mockReturnValue(throwError(() => new Error('nope'))),
        getCurrent: vi.fn().mockReturnValue(of(CURRENT_COMPLET)),
      },
      { getHistory: vi.fn().mockReturnValue(of([])) },
    );
    fixture.detectChanges();
    expect(fixture.componentInstance.error()).not.toBeNull();
    expect(fixture.componentInstance.site()).toBeNull();
  });
  it('efface les données du site précédent quand le chargement du suivant échoue', () => {
    const getSite = vi
      .fn()
      .mockReturnValueOnce(of(SITE))
      .mockReturnValueOnce(throwError(() => new Error('404')));
    const { fixture, paramMap } = setup(
      'SITE001',
      { getSite, getCurrent: vi.fn().mockReturnValue(of(CURRENT_COMPLET)) },
      { getHistory: vi.fn().mockReturnValue(of([LECTURE])) },
    );
    fixture.detectChanges();
    expect(fixture.componentInstance.site()?.site_id).toBe('SITE001');
    paramMap.next(convertToParamMap({ siteId: 'SITE002' }));
    fixture.detectChanges();
    expect(fixture.componentInstance.error()).not.toBeNull();
    expect(fixture.componentInstance.site()).toBeNull();
    expect(fixture.componentInstance.current()).toBeNull();
    expect(fixture.componentInstance.history()).toEqual([]);
    expect(fixture.nativeElement.textContent).not.toContain('Site 1');
  });
  it('interroge le site et sa mesure courante en parallèle', () => {
    const getSite = vi.fn().mockReturnValue(of(SITE));
    const getCurrent = vi.fn().mockReturnValue(of(CURRENT_COMPLET));
    const { fixture } = setup(
      'SITE001',
      { getSite, getCurrent },
      { getHistory: vi.fn().mockReturnValue(of([])) },
    );
    fixture.detectChanges();
    expect(getSite).toHaveBeenCalledWith('SITE001');
    expect(getCurrent).toHaveBeenCalledWith('SITE001');
  });
  it('signale la panne du capteur de consommation au lieu de tracer une jauge à zéro', () => {
    const sansConsommation = {
      ...CURRENT_COMPLET,
      consumption_kw: null,
      null_reasons: ['consumption_sensor_failure'],
      data_quality: 'partial' as const,
    };
    const { fixture } = setup(
      'SITE001',
      {
        getSite: vi.fn().mockReturnValue(of(SITE)),
        getCurrent: vi.fn().mockReturnValue(of(sansConsommation)),
      },
      { getHistory: vi.fn().mockReturnValue(of([LECTURE])) },
    );
    fixture.detectChanges();
    expect(fixture.componentInstance.consumptionKw()).toBeNull();
    expect(fixture.componentInstance.consumptionReason()).toBe('capteur de consommation en panne');
    expect(fixture.nativeElement.querySelector('app-consumption-gauge')).toBeNull();
    expect(fixture.nativeElement.textContent).toContain('Consommation indisponible');
  });
  it('trace la jauge pour une consommation nulle réellement mesurée', () => {
    const { fixture } = setup(
      'SITE001',
      {
        getSite: vi.fn().mockReturnValue(of(SITE)),
        getCurrent: vi.fn().mockReturnValue(of({ ...CURRENT_COMPLET, consumption_kw: 0 })),
      },
      { getHistory: vi.fn().mockReturnValue(of([LECTURE])) },
    );
    fixture.detectChanges();
    expect(fixture.componentInstance.consumptionLabel()).toBe('0.0 kW');
    expect(fixture.nativeElement.querySelector('app-consumption-gauge')).not.toBeNull();
    expect(fixture.nativeElement.textContent).not.toContain('Consommation indisponible');
  });
  it('affiche explicitement les champs null avec leur raison plutôt que de les masquer', () => {
    const partielle = {
      ...CURRENT_COMPLET,
      voltage_v: null,
      current_a: null,
      power_factor: null,
      null_reasons: ['electrical_sensor_failure'],
      data_quality: 'partial' as const,
    };
    const { fixture } = setup(
      'SITE001',
      {
        getSite: vi.fn().mockReturnValue(of(SITE)),
        getCurrent: vi.fn().mockReturnValue(of(partielle)),
      },
      { getHistory: vi.fn().mockReturnValue(of([LECTURE])) },
    );
    fixture.detectChanges();
    const tension = fixture.componentInstance.metrics().find((m) => m.key === 'voltage_v');
    expect(tension?.value).toBeNull();
    expect(tension?.reason).toBe('capteur électrique en panne');
    const texte = fixture.nativeElement.textContent;
    expect(texte).toContain('Indisponible');
    expect(texte).toContain('capteur électrique en panne');
    expect(texte).toContain('Données partielles');
  });
  it('recharge les données quand le paramètre de route siteId change', () => {
    const getSite = vi.fn().mockReturnValue(of(SITE));
    const { fixture, paramMap } = setup(
      'SITE001',
      { getSite, getCurrent: vi.fn().mockReturnValue(of(CURRENT_COMPLET)) },
      { getHistory: vi.fn().mockReturnValue(of([])) },
    );
    fixture.detectChanges();
    paramMap.next(convertToParamMap({ siteId: 'SITE002' }));
    fixture.detectChanges();
    expect(getSite).toHaveBeenCalledWith('SITE002');
  });
  it("ancre la fenêtre d'historique sur la dernière mesure connue plutôt que sur l'horloge", () => {
    const getHistory = vi.fn().mockReturnValue(of([]));
    const { fixture } = setup(
      'SITE001',
      {
        getSite: vi.fn().mockReturnValue(of(SITE)),
        getCurrent: vi.fn().mockReturnValue(of(CURRENT_COMPLET)),
      },
      { getHistory },
    );
    fixture.detectChanges();
    expect(getHistory).toHaveBeenCalledWith(
      'SITE001',
      '2026-09-16T10:00:00.000Z',
      '2026-09-17T10:00:00Z',
    );
  });
  it("annonce l'absence de mesure sans interroger l'historique quand timestamp est null", () => {
    const getHistory = vi.fn().mockReturnValue(of([]));
    const { fixture } = setup(
      'SITE001',
      {
        getSite: vi.fn().mockReturnValue(of(SITE)),
        getCurrent: vi.fn().mockReturnValue(of(SANS_MESURE)),
      },
      { getHistory },
    );
    fixture.detectChanges();
    expect(getHistory).not.toHaveBeenCalled();
    expect(fixture.componentInstance.hasMeasurement()).toBe(false);
    expect(fixture.nativeElement.textContent).toContain('Aucune mesure remontée pour ce site.');
  });
 });
@@ -1,213 +0,0 @@
 import { Component, DestroyRef, computed, inject, signal } from '@angular/core';
 import { takeUntilDestroyed, toObservable, toSignal } from '@angular/core/rxjs-interop';
 import { ActivatedRoute, RouterLink } from '@angular/router';
 import { catchError, EMPTY, filter, forkJoin, map, Observable, of, switchMap } from 'rxjs';
 import { SitesService } from '../../../core/services/sites.service';
 import { ReadingsService } from '../../../core/services/readings.service';
 import { Site } from '../../../shared/models/site.model';
 import { Reading, ReadingDataQuality } from '../../../shared/models/reading.model';
 import { SiteCurrent } from '../../../shared/models/site-current.model';
 import { Card } from '../../../shared/components/ui/card/card';
 import { Alert } from '../../../shared/components/ui/alert/alert';
 import { Badge, BadgeTone } from '../../../shared/components/ui/badge/badge';
 import { Brand } from '../../../shared/components/ui/brand/brand';
 import { ConsumptionGauge } from '../../../shared/components/consumption-gauge/consumption-gauge';
 import { ReadingHistoryChart } from '../../../shared/components/reading-history-chart/reading-history-chart';
 const UNAVAILABLE_MESSAGE = 'Détail du site indisponible, réessayez plus tard.';
 const NO_MEASUREMENT_MESSAGE = 'Aucune mesure remontée pour ce site.';
 const HISTORY_WINDOW_MS = 24 * 60 * 60 * 1000;
 const TON_PAR_STATUT: Record<string, BadgeTone> = {
  actif: 'success',
  maintenance: 'warning',
  hors_service: 'danger',
 };
 const TON_PAR_QUALITE: Record<ReadingDataQuality, BadgeTone> = {
  good: 'success',
  partial: 'warning',
  degraded: 'danger',
  critical: 'critical',
 };
 const LIBELLE_PAR_QUALITE: Record<ReadingDataQuality, string> = {
  good: 'Données complètes',
  partial: 'Données partielles',
  degraded: 'Données dégradées',
  critical: 'Données critiques',
 };
 type MetricKey =
  | 'consumption_kw'
  | 'voltage_v'
  | 'current_a'
  | 'power_factor'
  | 'temperature_celsius'
  | 'humidity_percent';
 interface MetricDef {
  key: MetricKey;
  label: string;
  format: (value: number) => string;
 }
 const CONSUMPTION_DEF: MetricDef = {
  key: 'consumption_kw',
  label: 'Consommation',
  format: (v) => `${v.toFixed(1)} kW`,
 };
 const METRIC_DEFS: MetricDef[] = [
  CONSUMPTION_DEF,
  { key: 'voltage_v', label: 'Tension', format: (v) => `${v.toFixed(1)} V` },
  { key: 'current_a', label: 'Courant', format: (v) => `${v.toFixed(1)} A` },
  { key: 'power_factor', label: 'Cos φ', format: (v) => v.toFixed(2) },
  { key: 'temperature_celsius', label: 'Température', format: (v) => `${v.toFixed(1)} °C` },
  { key: 'humidity_percent', label: 'Humidité', format: (v) => `${v.toFixed(0)} %` },
 ];
 // Contrainte : miroir de RAISON_VERS_CAPTEUR et CHAMPS_PAR_CAPTEUR (backend, services/sensor.py) ;
 // `null_reasons` porte le code de panne du capteur, jamais le nom du champ resté vide.
 const RAISONS_PAR_CHAMP: Record<MetricKey, string[]> = {
  consumption_kw: ['consumption_sensor_failure', 'network_loss'],
  voltage_v: ['electrical_sensor_failure', 'network_loss'],
  current_a: ['electrical_sensor_failure', 'network_loss'],
  power_factor: ['electrical_sensor_failure', 'network_loss'],
  temperature_celsius: ['temperature_sensor_failure', 'network_loss'],
  humidity_percent: ['humidity_sensor_failure', 'network_loss'],
 };
 const LIBELLE_PAR_RAISON: Record<string, string> = {
  consumption_sensor_failure: 'capteur de consommation en panne',
  electrical_sensor_failure: 'capteur électrique en panne',
  temperature_sensor_failure: 'capteur de température en panne',
  humidity_sensor_failure: "capteur d'humidité en panne",
  network_loss: 'perte réseau',
 };
 export interface MetricView {
  key: MetricKey;
  label: string;
  value: string | null;
  reason: string;
 }
@Component({
  selector: 'app-site-detail',
  standalone: true,
  imports: [RouterLink, Card, Alert, Badge, Brand, ConsumptionGauge, ReadingHistoryChart],
  templateUrl: './site-detail.html',
  styleUrl: './site-detail.scss',
 })
 export class SiteDetail {
  private route = inject(ActivatedRoute);
  private sitesService = inject(SitesService);
  private readingsService = inject(ReadingsService);
  private destroyRef = inject(DestroyRef);
  readonly noMeasurementMessage = NO_MEASUREMENT_MESSAGE;
  siteId = toSignal(this.route.paramMap.pipe(map((params) => params.get('siteId') ?? '')));
  site = signal<Site | null>(null);
  current = signal<SiteCurrent | null>(null);
  history = signal<Reading[]>([]);
  error = signal<string | null>(null);
  hasMeasurement = computed(() => this.current()?.timestamp != null);
  consumptionKw = computed(() => this.current()?.consumption_kw ?? null);
  consumptionLabel = computed(() => {
    const kw = this.consumptionKw();
    return kw != null ? CONSUMPTION_DEF.format(kw) : null;
  });
  consumptionReason = computed(() => this.reasonFor('consumption_kw', this.current()));
  qualityLabel = computed(() => {
    const quality = this.current()?.data_quality;
    return quality ? LIBELLE_PAR_QUALITE[quality] : null;
  });
  qualityTone = computed<BadgeTone>(() => {
    const quality = this.current()?.data_quality;
    return quality ? TON_PAR_QUALITE[quality] : 'neutral';
  });
  metrics = computed<MetricView[]>(() => {
    const current = this.current();
    return METRIC_DEFS.map((def) => {
      const valeur = current ? current[def.key] : null;
      return {
        key: def.key,
        label: def.label,
        value: valeur != null ? def.format(valeur) : null,
        reason: valeur == null ? this.reasonFor(def.key, current) : '',
      };
    });
  });
  constructor() {
    toObservable(this.siteId)
      .pipe(
        filter((siteId): siteId is string => !!siteId),
        // Piège : switchMap sur le flux externe annule le chargement en cours dès qu'un
        // nouveau siteId arrive, sinon une réponse en retard peut écraser le site affiché.
        switchMap((siteId) => this.load(siteId)),
        takeUntilDestroyed(this.destroyRef),
      )
      .subscribe((result) => {
        this.error.set(null);
        this.site.set(result.site);
        this.current.set(result.current);
        this.history.set(result.history);
      });
  }
  badgeToneForStatus(status: string | null): BadgeTone {
    return status ? (TON_PAR_STATUT[status] ?? 'neutral') : 'neutral';
  }
  private load(siteId: string) {
    return forkJoin({
      site: this.sitesService.getSite(siteId),
      current: this.sitesService.getCurrent(siteId),
    }).pipe(
      switchMap(({ site, current }) =>
        this.loadHistory(siteId, current).pipe(map((history) => ({ site, current, history }))),
      ),
      catchError(() => this.reportUnavailable()),
    );
  }
  private loadHistory(siteId: string, current: SiteCurrent): Observable<Reading[]> {
    // Piège : le jeu de données s'arrête bien avant « maintenant » ; ancrer la fenêtre sur la
    // dernière mesure connue plutôt que sur l'horloge évite un historique systématiquement vide.
    const end = current.timestamp;
    if (end === null) {
      return of([]);
    }
    const start = new Date(new Date(end).getTime() - HISTORY_WINDOW_MS).toISOString();
    return this.readingsService.getHistory(siteId, start, end);
  }
  private reasonFor(field: MetricKey, current: SiteCurrent | null): string {
    const raisons = RAISONS_PAR_CHAMP[field];
    const trouvees = (current?.null_reasons ?? [])
      .filter((raison) => raisons.includes(raison))
      .map((raison) => LIBELLE_PAR_RAISON[raison] ?? raison);
    return trouvees.length > 0 ? trouvees.join(', ') : 'cause inconnue';
  }
  // Piège : vider les signaux avec l'erreur, sinon la page garde le site précédemment chargé
  // sous le bandeau et laisse lire les chiffres de A en croyant regarder B.
  private reportUnavailable(): Observable<never> {
    this.error.set(UNAVAILABLE_MESSAGE);
    this.site.set(null);
    this.current.set(null);
    this.history.set([]);
    return EMPTY;
  }
 }
@@ -1 +0,0 @@
 <canvas #canvas></canvas>
@@ -1,4 +0,0 @@
 :host {
  display: block;
  height: 260px;
 }
@@ -1,101 +0,0 @@
 import { TestBed } from '@angular/core/testing';
 import { vi } from 'vitest';
 import { Chart } from 'chart.js';
 import { ReadingHistoryChart } from './reading-history-chart';
 vi.mock('chart.js', () => {
  class ChartMock {
    static instances: ChartMock[] = [];
    static register = vi.fn();
    update = vi.fn();
    destroy = vi.fn();
    data: { labels?: unknown[]; datasets: Record<string, unknown>[] } = { datasets: [{}] };
    constructor(_canvas: unknown, config?: { data?: ChartMock['data'] }) {
      if (config?.data) {
        this.data = config.data;
      }
      ChartMock.instances.push(this);
    }
  }
  return { Chart: ChartMock, registerables: [] };
 });
 type ChartDouble = {
  destroy: ReturnType<typeof vi.fn>;
  data: { labels?: unknown[]; datasets: Record<string, unknown>[] };
 };
 function lastChart(): ChartDouble | undefined {
  return (Chart as unknown as { instances: ChartDouble[] }).instances.at(-1);
 }
 const READING = {
  reading_id: 1,
  site_id: 'S1',
  timestamp: '2026-09-17T10:00:00Z',
  source: 'api_history' as const,
  consumption_kw: 42,
  consumption_kwh: null,
  consumption_euros: null,
  voltage_v: null,
  current_a: null,
  power_factor: null,
  temperature_celsius: null,
  humidity_percent: null,
  solar_irradiance_wm2: null,
  is_working_hours: null,
  data_quality: 'good' as const,
  null_reasons: null,
  imputed_values: null,
  imputation_method: null,
 };
 describe('ReadingHistoryChart', () => {
  it('se crée sans erreur avec une liste de lectures valide', () => {
    TestBed.configureTestingModule({ imports: [ReadingHistoryChart] });
    const fixture = TestBed.createComponent(ReadingHistoryChart);
    fixture.componentRef.setInput('readings', [READING]);
    expect(() => fixture.detectChanges()).not.toThrow();
  });
  it('met à jour le graphique quand les lectures changent après initialisation', () => {
    TestBed.configureTestingModule({ imports: [ReadingHistoryChart] });
    const fixture = TestBed.createComponent(ReadingHistoryChart);
    fixture.componentRef.setInput('readings', [READING]);
    fixture.detectChanges();
    fixture.componentRef.setInput('readings', [
      { ...READING, reading_id: 2, consumption_kw: 60, data_quality: 'critical' as const },
    ]);
    fixture.detectChanges();
    expect(() => fixture.detectChanges()).not.toThrow();
  });
  it("trace du plus ancien au plus récent, quel que soit l'ordre reçu de l'API", () => {
    TestBed.configureTestingModule({ imports: [ReadingHistoryChart] });
    const fixture = TestBed.createComponent(ReadingHistoryChart);
    // L'API trie en timestamp décroissant : le composant doit rétablir la chronologie.
    fixture.componentRef.setInput('readings', [
      { ...READING, reading_id: 2, timestamp: '2026-09-17T11:00:00Z', consumption_kw: 60 },
      { ...READING, reading_id: 1, timestamp: '2026-09-17T10:00:00Z', consumption_kw: 42 },
    ]);
    fixture.detectChanges();
    const chart = lastChart();
    expect(chart?.data.labels).toEqual(['2026-09-17T10:00:00Z', '2026-09-17T11:00:00Z']);
    expect(chart?.data.datasets[0]['data']).toEqual([42, 60]);
  });
  it('détruit le graphique quand le composant est détruit', () => {
    TestBed.configureTestingModule({ imports: [ReadingHistoryChart] });
    const fixture = TestBed.createComponent(ReadingHistoryChart);
    fixture.componentRef.setInput('readings', [READING]);
    fixture.detectChanges();
    const chart = lastChart();
    fixture.destroy();
    expect(chart?.destroy).toHaveBeenCalledTimes(1);
  });
 });
@@ -1,95 +0,0 @@
 import {
  Component,
  ElementRef,
  ViewChild,
  input,
  effect,
  AfterViewInit,
  OnDestroy,
 } from '@angular/core';
 import { Chart, registerables } from 'chart.js';
 import { Reading, ReadingDataQuality } from '../../models/reading.model';
 Chart.register(...registerables);
 const QUALITY_COLORS: Record<ReadingDataQuality, string> = {
  good: '#3b82f6',
  partial: '#f9a825',
  degraded: '#ef6c00',
  critical: '#c62828',
 };
 const UNKNOWN_QUALITY_COLOR = '#9ca3af';
 interface ChartSeries {
  labels: string[];
  values: number[];
  colors: string[];
 }
 // Piège : l'API renvoie les lectures du plus récent au plus ancien (ReadingRepository.list_history
 // trie en timestamp desc) ; sans ce tri l'axe des abscisses se lirait à rebours.
 function toSeries(readings: Reading[]): ChartSeries {
  const ordered = [...readings].sort((a, b) => Date.parse(a.timestamp) - Date.parse(b.timestamp));
  return {
    labels: ordered.map((r) => r.timestamp),
    values: ordered.map((r) => r.consumption_kw ?? 0),
    colors: ordered.map((r) =>
      r.data_quality ? QUALITY_COLORS[r.data_quality] : UNKNOWN_QUALITY_COLOR,
    ),
  };
 }
@Component({
  selector: 'app-reading-history-chart',
  standalone: true,
  templateUrl: './reading-history-chart.html',
  styleUrl: './reading-history-chart.scss',
 })
 export class ReadingHistoryChart implements AfterViewInit, OnDestroy {
  readings = input.required<Reading[]>();
  @ViewChild('canvas') private canvasRef!: ElementRef<HTMLCanvasElement>;
  private chart?: Chart<'line'>;
  constructor() {
    effect(() => {
      const series = toSeries(this.readings());
      if (this.chart) {
        this.chart.data.labels = series.labels;
        this.chart.data.datasets[0].data = series.values;
        this.chart.data.datasets[0].pointBackgroundColor = series.colors;
        this.chart.update('none');
      }
    });
  }
  ngAfterViewInit(): void {
    const series = toSeries(this.readings());
    this.chart = new Chart(this.canvasRef.nativeElement, {
      type: 'line',
      data: {
        labels: series.labels,
        datasets: [
          {
            data: series.values,
            borderColor: '#3b82f6',
            pointBackgroundColor: series.colors,
            tension: 0.25,
          },
        ],
      },
      options: {
        responsive: true,
        maintainAspectRatio: false,
        plugins: { legend: { display: false } },
        scales: {
          y: { beginAtZero: true, title: { display: true, text: 'Consommation (kW)' } },
        },
      },
    });
  }
  ngOnDestroy(): void {
    this.chart?.destroy();
  }
 }
@@ -1,24 +0,0 @@
 export type PredictionStatus = 'available' | 'insufficient_data' | 'error';
 export type PredictionTargetMetric = 'consumption_kwh' | 'consumption_kw';
 export interface SitePrediction {
  target_at: string;
  target_metric: PredictionTargetMetric;
  period_minutes: number | null;
  predicted_value: number | null;
  status: PredictionStatus;
  failure_reason: string | null;
  model_reference: string;
  created_at: string;
 }
 export interface SitePredictionSummary {
  site_id: string;
  site_name: string;
  prediction: SitePrediction | null;
 }
 export interface PredictionSummary {
  timestamp: string;
  sites: SitePredictionSummary[];
 }
@@ -1,23 +0,0 @@
 export type ReadingSource = 'csv' | 'api_current' | 'api_history';
 export type ReadingDataQuality = 'good' | 'partial' | 'degraded' | 'critical';
 export interface Reading {
  reading_id: number;
  site_id: string;
  timestamp: string;
  source: ReadingSource;
  consumption_kw: number | null;
  consumption_kwh: number | null;
  consumption_euros: string | null;
  voltage_v: number | null;
  current_a: number | null;
  power_factor: number | null;
  temperature_celsius: number | null;
  humidity_percent: number | null;
  solar_irradiance_wm2: number | null;
  is_working_hours: boolean | null;
  data_quality: ReadingDataQuality | null;
  null_reasons: string[] | null;
  imputed_values: Record<string, unknown> | null;
  imputation_method: string | null;
 }
@@ -1,16 +0,0 @@
 import { ReadingDataQuality } from './reading.model';
 export interface SiteCurrent {
  timestamp: string | null;
  site_id: string;
  site_type: string;
  consumption_kw: number | null;
  consumption_kwh: number | null;
  voltage_v: number | null;
  current_a: number | null;
  power_factor: number | null;
  temperature_celsius: number | null;
  humidity_percent: number | null;
  null_reasons: string[];
  data_quality: ReadingDataQuality;
 }
@@ -1,5 +1,5 @@
 export const environment = {
  production: false,
  apiUrl: '/api/v1',
-  useMockFixtures: false,
+  useMockFixtures: true, // a passer a false une fois le backend prêt
 };
@@ -1,5 +0,0 @@
 -- Base de metadonnees Airflow (webserver + scheduler, LocalExecutor). Separee de la base
 -- applicative : les tables internes d'Airflow (dag_run, task_instance, ...) n'ont rien a faire
 -- dans le schema metier. Meme conteneur Postgres que `enervision`/`enervision_test` plutot qu'un
 -- service dedie, pour ne pas ajouter un conteneur de plus (issue #115).
 CREATE DATABASE airflow;
@@ -1,74 +0,0 @@
 # Piège : `APP_ENV` et `APP_DEBUG` sont en dur et non en `${APP_ENV:-prod}` : le `.env` du poste
 # vaut `local` et reprendrait le dessus, ce qui laisserait le cookie sans `__Secure-` et
 # rouvrirait `/docs`. Hors `local`, l'API exige en retour une origine CORS non vide.
 # Piège : les listes de ports se cumulent à la fusion des deux fichiers. `!reset` est le seul
 # moyen de dépublier 8000 et 3000 : sans lui, l'API resterait joignable en clair à côté du proxy.
 # Piège : pas de `:?` sur `PUBLIC_HOST`. Compose interpole tout le fichier, y compris pour
 # `stop` et `logs` : la garde vit dans `make stack-up`, qui la compare au certificat servi.
 name: enervision
 services:
  db:
    ports: !override
      - "127.0.0.1:${POSTGRES_PORT:-5433}:5432"
  mailpit:
    ports: !override
      - "127.0.0.1:${MAILPIT_UI_PORT:-8025}:8025"
  airflow-webserver:
    ports: !override
      - "127.0.0.1:${AIRFLOW_PORT:-8080}:8080"
  backend:
    ports: !reset null
    command:
      - uvicorn
      - app.main:create_app
      - --factory
      - --host
      - 0.0.0.0
      - --port
      - "8000"
      - --proxy-headers
      - --forwarded-allow-ips=*
    environment:
      APP_ENV: prod
      APP_DEBUG: "false"
      APP_TRUST_PROXY_HEADERS: "true"
      APP_CORS_ORIGINS: https://${PUBLIC_HOST:-enervision.local}
      APP_FRONTEND_RESET_PASSWORD_URL: https://${PUBLIC_HOST:-enervision.local}/reset-password
  frontend:
    ports: !reset null
  proxy:
    image: nginx:1.31-alpine
    depends_on:
      backend:
        condition: service_healthy
      frontend:
        condition: service_started
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - ./infra/proxy/nginx.conf:/etc/nginx/nginx.conf:ro
      - ./infra/proxy/conf.d:/etc/nginx/conf.d:ro
      - ./infra/proxy/tls:/etc/nginx/tls:ro
      - acme_webroot:/var/www/certbot
    restart: unless-stopped
  certbot:
    image: certbot/certbot:v5.8.0
    profiles: ["acme"]
    volumes:
      - letsencrypt:/etc/letsencrypt
      - acme_webroot:/var/www/certbot
      - ./infra/proxy/tls:/tls
      - ./infra/proxy/acme-deploy-hook.sh:/deploy-hook.sh:ro
 volumes:
  acme_webroot:
  letsencrypt:
@@ -5,41 +5,6 @@
 name: enervision
 # Piege : LocalExecutor fait tourner les taches comme sous-processus du scheduler, jamais du
 # webserver. `airflow_ml_state` (modele entraine, magasin MLflow) n'a donc besoin d'etre monte
 # que sur `airflow-scheduler` en pratique, mais reste partage avec le webserver pour que ce
 # dernier puisse au besoin l'inspecter sans en devenir dependant.
 x-airflow-common: &airflow-common
  build:
    context: .
    dockerfile: etl/airflow/Dockerfile
  environment: &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: LocalExecutor
    AIRFLOW__CORE__LOAD_EXAMPLES: "false"
    # Piege : pas de `:?` sur les secrets Airflow. Compose interpole le fichier entier avant de
    # filtrer les services : une variable requise manquante casserait aussi `make db-up`,
    # `make dev`... pour quiconque n'a pas encore complete son `.env`. Le refus est porte par
    # `airflow-init` (ci-dessous), dont `webserver` et `scheduler` dependent.
    AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW_FERNET_KEY:-}
    AIRFLOW__WEBSERVER__SECRET_KEY: ${AIRFLOW_WEBSERVER_SECRET_KEY:-}
    AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://${POSTGRES_USER}:${POSTGRES_PASSWORD}@db:5432/airflow
    # Role `enervision_ml` dedie pas encore provisionne (dette assumee, cf. ADR 0003) :
    # memes identifiants que le backend en attendant.
    ML_DATABASE_URL: postgresql+psycopg://${POSTGRES_USER}:${POSTGRES_PASSWORD}@db:5432/${POSTGRES_DB}
    MLFLOW_TRACKING_URI: sqlite:////opt/ml/state/mlflow.db
    # Le DAG `alertes` lance le backend en sous-processus : il lit `DATABASE_URL`, en
    # dialecte asyncpg, là où le pipeline ML lit `ML_DATABASE_URL`.
    DATABASE_URL: postgresql+asyncpg://${POSTGRES_USER}:${POSTGRES_PASSWORD}@db:5432/${POSTGRES_DB}
    # Clé distincte de celle de l'API : la détection ne signe ni ne vérifie aucun jeton, et
    # Airflow permet d'exécuter du code depuis son interface (cf. ADR 0008).
    APP_SECRET_KEY: ${AIRFLOW_APP_SECRET_KEY:-}
  volumes:
    - ./etl/airflow/dags:/opt/airflow/dags
    - ./etl/airflow/plugins:/opt/airflow/plugins
    - airflow_logs:/opt/airflow/logs
    - airflow_ml_state:/opt/ml/state
  restart: unless-stopped
 services:
  db:
    image: timescale/timescaledb-ha:pg17
@@ -54,7 +19,6 @@ services:
      - pgdata:/home/postgres/pgdata/data
      - ./db/init/100-extensions.sql:/docker-entrypoint-initdb.d/100-extensions.sql:ro
      - ./db/init/110-test-database.sql:/docker-entrypoint-initdb.d/110-test-database.sql:ro
      - ./db/init/120-airflow-database.sql:/docker-entrypoint-initdb.d/120-airflow-database.sql:ro
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U $${POSTGRES_USER} -d $${POSTGRES_DB}"]
      interval: 10s
@@ -86,12 +50,6 @@ services:
      APP_SECRET_KEY: ${APP_SECRET_KEY:?}
      APP_CORS_ORIGINS: ${APP_CORS_ORIGINS:-http://localhost:4200}
      DATABASE_URL: postgresql+asyncpg://${POSTGRES_USER}:${POSTGRES_PASSWORD}@db:5432/${POSTGRES_DB}
      APP_MOCK_API_BASE_URL: ${APP_MOCK_API_BASE_URL:-https://api-mock.charlieandre.fr}
      APP_MOCK_API_USERNAME: ${APP_MOCK_API_USERNAME:-}
      APP_MOCK_API_PASSWORD: ${APP_MOCK_API_PASSWORD:-}
      APP_MOCK_API_TIMEOUT_SECONDS: ${APP_MOCK_API_TIMEOUT_SECONDS:-10}
      APP_FRONTEND_RESET_PASSWORD_URL: ${APP_FRONTEND_RESET_PASSWORD_URL:-http://localhost:4200/reset-password}
      APP_SMTP_HOST: mailpit
      APP_SMTP_PORT: "1025"
@@ -104,67 +62,9 @@ services:
  frontend:
    build: ./apps/frontend
    ports:
-      - "${FRONTEND_PORT:-3000}:3000"
+      - "${FRONTEND_PORT:-3000}:80"
    restart: unless-stopped
-
+        
  # Conteneur unique, jamais redemarre. La migration et la creation du premier compte sont
  # portees par l'entrypoint de l'image (`_AIRFLOW_DB_MIGRATE`, `_AIRFLOW_WWW_USER_*`), qui porte
  # aussi leur code de sortie : une migration ratee (ex. base `airflow` absente sur un volume
  # `pgdata` deja peuple) fait echouer ce service, et `webserver`/`scheduler`, qui attendent son
  # succes, ne demarrent pas sur une base non migree. Le mot de passe passe par l'environnement,
  # jamais par `argv` (ni `ps`, ni `docker compose config`).
  # Sans mot de passe, l'entrypoint refuse lui-meme de creer le compte ; la commande ci-dessous
  # refuse en plus les deux cles de chiffrement vides.
  airflow-init:
    <<: *airflow-common
    restart: "no"
    environment:
      <<: *airflow-common-env
      _AIRFLOW_DB_MIGRATE: "true"
      _AIRFLOW_WWW_USER_CREATE: "true"
      _AIRFLOW_WWW_USER_USERNAME: ${AIRFLOW_ADMIN_USERNAME:-admin}
      _AIRFLOW_WWW_USER_PASSWORD: ${AIRFLOW_ADMIN_PASSWORD:-}
      _AIRFLOW_WWW_USER_EMAIL: ${AIRFLOW_ADMIN_EMAIL:-admin@enervision.fr}
    depends_on:
      db:
        condition: service_healthy
    command:
      - bash
      - -c
      - |
        set -euo pipefail
        : "$${AIRFLOW__CORE__FERNET_KEY:?AIRFLOW_FERNET_KEY manquant dans .env}"
        : "$${AIRFLOW__WEBSERVER__SECRET_KEY:?AIRFLOW_WEBSERVER_SECRET_KEY manquant dans .env}"
        : "$${APP_SECRET_KEY:?AIRFLOW_APP_SECRET_KEY manquant dans .env}"
        exec airflow version
  airflow-webserver:
    <<: *airflow-common
    command: webserver
    ports:
      - "${AIRFLOW_PORT:-8080}:8080"
    depends_on:
      db:
        condition: service_healthy
      airflow-init:
        condition: service_completed_successfully
    healthcheck:
      test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
      interval: 30s
      timeout: 10s
      retries: 5
      start_period: 60s
  airflow-scheduler:
    <<: *airflow-common
    command: scheduler
    depends_on:
      db:
        condition: service_healthy
      airflow-init:
        condition: service_completed_successfully
 volumes:
  pgdata:
  airflow_logs:
  airflow_ml_state:
@@ -1,177 +0,0 @@
 # ML-START : accès aux données, scoring, frontière API et ML
 Document de référence du module `ml/`, cité par le code (`enervision_ml/config.py`, `data.py`,
 `train.py`, `score.py`, `features.py`), par l'[ADR 0005](adr/0005-modele-prediction-lightgbm.md)
 et par les vues d'architecture. Il répond à trois questions, et à elles seules :
 1. **comment le pipeline accède aux données**, et pourquoi pas par l'API ;
 2. **ce que fait un run de scoring**, étape par étape ;
 3. **où passe la frontière entre l'API et le ML**, et pourquoi elle est là.
 Le mode d'emploi (installation, commandes, options) est dans [`ml/README.md`](../ml/README.md).
 Le choix du modèle est dans l'ADR 0005. Ce document ne les répète pas.
 ---
 ## 1. Mécanisme d'accès aux données
 ### Deux sources, un seul schéma de sortie
 `enervision_ml.data` expose trois chargeurs qui produisent **exactement les mêmes neuf colonnes**
 (`site_id`, `timestamp`, `consumption_kwh`, `temperature_celsius`, `humidity_percent`,
 `solar_irradiance_wm2`, `is_working_hours`, `site_type`, `capacity_kw`) :
 | Fonction | Source | Usage |
 |---|---|---|
 | `load_from_csv(path)` | `ml/data/all_sites_combined.csv` | Chemin de démarrage, tant que la base n'est pas peuplée |
 | `load_from_database(connection)` | `reading` joint à `site`, **historique complet** | Entraînement |
 | `load_recent_from_database(connection, since=…)` | `reading` joint à `site`, **borné par `since`** | Scoring |
 L'égalité des schémas n'est pas un confort : c'est ce qui permet de valider tout le pipeline sur
 CSV, sans base joignable, et d'obtenir le même comportement une fois la base peuplée. Une
 divergence entre les deux chemins ne se verrait pas au chargement, elle se verrait en production
 sous forme de prédictions silencieusement fausses.
 ### Connexion directe à PostgreSQL, pas l'API
 Le pipeline lit `reading` et `site` **en SQL direct**, jamais par `GET /api/v1/readings`. Trois
 raisons, à défendre telles quelles :
 - **Volume.** L'entraînement lit l'historique complet d'une hypertable TimescaleDB. Le faire
  passer par une API REST paginée, sérialisée en JSON et contrôlée route par route, c'est payer
  trois fois pour un `SELECT`.
 - **Couplage.** Le pipeline n'est pas un client de l'application, c'est un consommateur du
  schéma. Passer par l'API le rendrait dépendant du contrat HTTP, de l'authentification et de la
  disponibilité du service, pour lire des données dont il connaît déjà la forme.
 - **Droits.** Un rôle de lecture sur deux tables est une surface plus petite qu'un compte
  applicatif porteur d'un rôle métier.
 ### `ML_DATABASE_URL`, et pourquoi ce n'est pas `DATABASE_URL`
 La chaîne de connexion est lue dans **`ML_DATABASE_URL`**, jamais dans `DATABASE_URL`. Ce n'est
 pas une préférence de nommage : `DATABASE_URL` est celle du backend applicatif, **propriétaire du
 schéma**, avec les droits d'écriture complets. Réutiliser cette variable par défaut ferait tourner
 l'entraînement et le scoring avec ces droits, **en silence**. `enervision_ml.config.database_url()`
 lève donc plutôt que de retomber sur une valeur par défaut.
 **Dette assumée, à dire à l'oral et non à masquer** : le rôle PostgreSQL dédié `enervision_ml`,
 restreint en lecture sur `reading` et `site`, **n'est pas provisionné**. En développement,
 `ML_DATABASE_URL` pointe sur la même base que le backend. La cible est un rôle séparé, cohérente
 avec le principe de moindre privilège posé par l'[ADR 0003](adr/0003-autorisation-rbac-a-trois-roles.md).
 ### Le seul endroit qui construit les features
 `enervision_ml.features.build_features` est **l'unique** constructeur de features, à
 l'entraînement comme au scoring. Le piège que cela évite : si les deux divergent, même d'une
 fenêtre de moyenne glissante, le modèle reçoit en service des features qui ne ressemblent plus à
 ce qu'il a appris, et ses prédictions se dégradent **sans qu'aucune erreur ne se déclenche**.
 Ne jamais réécrire cette logique ailleurs : importer le module.
 Conséquence sur la validation : la coupure entraînement / validation est **chronologique**, jamais
 un tirage aléatoire de lignes. Un tirage aléatoire laisserait des lignes de validation voir des
 lignes d'entraînement à travers leurs lags et leurs moyennes glissantes, une fuite qui masquerait
 un surapprentissage.
 ---
 ## 2. Les étapes d'un run de scoring
 `python -m enervision_ml.score` calcule, pour chaque site ou pour un seul avec `--site-id`, la
 consommation prévue de **l'heure suivant sa dernière lecture connue**, et écrit une ligne dans
 `prediction`.
 | # | Étape | Point de vigilance |
 |---|---|---|
 | 1 | Charger une **fenêtre récente** de `reading` joint à `site` : 21 jours par défaut | Une marge au-dessus des 168 h qu'exige le lag hebdomadaire. Un `SELECT` non borné sur l'hypertable serait la même erreur que celle corrigée sur `GET /readings` |
 | 2 | Ajouter **une ligne future par site**, l'heure suivante, et calculer ses features par `build_features` | La même fonction qu'à l'entraînement, cf. section 1 |
 | 3 | Si le **lag de 168 h est absent** (moins d'une semaine d'historique) : écrire `status = "insufficient_data"` | **LightGBM n'est jamais appelé.** Un modèle interrogé sans son lag principal rendrait un nombre, et ce nombre serait faux sans le dire |
 | 4 | Sinon : `booster.predict(...)`, puis écrire `status = "available"` et la valeur prévue | |
 ### Ce que le run écrit, et ce qu'il n'écrase pas
 La table `prediction` **n'a pas de contrainte d'unicité sur `(site_id, target_at)`** : chaque run
 insère une ligne de plus au lieu d'écraser la précédente. C'est délibéré, et c'est ce qui rendra
 possible la comparaison prévision contre réalisé, donc la surveillance de dérive (#44, #45), qui
 n'existe pas encore.
 Trois contraintes de cohérence sont portées par la base et non par le code applicatif :
 `status = 'available'` exige une `predicted_value` et interdit un `failure_reason` ;
 `insufficient_data` et `error` exigent l'inverse ; `target_metric` est bornée à
 `consumption_kwh` ou `consumption_kw`, et la forme énergie impose une `period_minutes`.
 ### `model_reference` est un hachage, pas un nom de fichier
 `train.py` réécrit **toujours le même chemin** (`models/lightgbm-consumption.txt`) à chaque
 entraînement. Le nom de fichier ne distinguerait donc pas deux versions du modèle. `prediction`
 porte pour cela le **SHA-256 tronqué du fichier modèle**. C'est ce qui permet, devant une
 prédiction douteuse, de savoir quel modèle l'a produite.
 ### Mode CSV : rien n'est écrit en base
 En `--csv`, le run ne touche pas la base. L'heure future calculée depuis la fin du CSV n'existe
 dans aucune base réelle : ce serait inscrire une prévision pour un instant déjà passé. Le mode
 sert à valider le pipeline sans base joignable.
 ### Limite assumée
 La feature `is_working_hours` de la ligne future est **recopiée** depuis la dernière lecture
 réelle, pas recalculée : il n'existe aucune règle d'heures ouvrables dans ce dépôt, elle vit dans
 le générateur du jeu de données d'origine. L'approximation n'est fausse qu'aux heures de bascule,
 sur une feature parmi une dizaine, pour une prévision à un seul pas.
 ---
 ## 3. La frontière entre l'API et le ML
 ```mermaid
 flowchart LR
    subgraph ml["ml/ · projet Python indépendant"]
        train["enervision_ml.train<br/>LightGBM + MLflow"]
        score["enervision_ml.score<br/>prévision à un pas"]
    end
    subgraph db["PostgreSQL + TimescaleDB"]
        reading[("reading, site")]
        prediction[("prediction")]
    end
    subgraph api["apps/backend · FastAPI"]
        route["GET /api/v1/predictions"]
    end
    reading -- "SQL direct, ML_DATABASE_URL" --> train
    reading -- "fenêtre récente" --> score
    train -- "models/*.txt + run MLflow" --> score
    score -- "INSERT" --> prediction
    prediction -- "lecture seule" --> route
 ```
 **La règle, en une phrase : FastAPI ne fait jamais tourner LightGBM.**
 `GET /api/v1/predictions` lit la dernière prévision par site dans `prediction`, jamais un recalcul
 à la volée. Ce qui en découle, et qui est l'argument à tenir devant le jury :
 - **La latence de l'API ne dépend pas du modèle.** Une route de lecture indexée
  (`ix_prediction_site_target`) répond en temps constant, qu'un run de scoring dure une seconde
  ou une minute.
 - **Le service de production n'embarque ni LightGBM ni MLflow.** `ml/` est un projet Python
  séparé, avec son propre `uv.lock`. Le backend n'a aucune raison de porter ces dépendances, ni
  leur surface de vulnérabilités, pour un script lancé hors du chemin de requête.
 - **Une panne du pipeline dégrade, elle n'interrompt pas.** Si le scoring ne tourne plus, l'API
  continue de servir la dernière prévision connue, avec son `created_at` et son
  `model_reference`, au lieu de rendre une erreur.
 - **Le contrat est la table, pas un appel.** Ce qui traverse la frontière, ce sont des lignes de
  `prediction` et leurs contraintes de cohérence, vérifiables en SQL.
 Le corollaire est qu'il n'y a **aucune prévision à la demande** : la fraîcheur d'une prévision est
 celle du dernier run de scoring. Ce run est ordonnancé par Airflow, DAG `ml_score` en `@hourly`
 (issue #115) ; seuls le mode `--csv` et un lancement local restent manuels, tout comme
 l'entraînement, dont le DAG `ml_train` n'a pas de planification. La dette qui subsiste est la
 surveillance de dérive, portée par les issues #44 et #45.
 ---
 ## Voir aussi
 - [`ml/README.md`](../ml/README.md) : installation, commandes, options, où écrire les tests
 - [ADR 0005](adr/0005-modele-prediction-lightgbm.md) : pourquoi LightGBM, et les 6 candidats écartés
 - [ADR 0006](adr/0006-moteur-de-regles-dans-le-backend.md) : ce qui consomme les prédictions
 - [`architecture/20-backend.md`](architecture/20-backend.md) : le contrat de `GET /predictions`
 - [`architecture/40-data.md`](architecture/40-data.md) : le modèle de données
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