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+8
-5
@@ -29,15 +29,18 @@ 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
|
||||
# Airflow (api-server + scheduler + dag-processor, 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
|
||||
# Clé de session de l'api-server Airflow, distincte de la précédente. Générer la
|
||||
# vôtre : python -c "import secrets; print(secrets.token_urlsafe(48))"
|
||||
AIRFLOW_WEBSERVER_SECRET_KEY=change_me
|
||||
AIRFLOW_API_SECRET_KEY=change_me
|
||||
# Secret des jetons JWT entre scheduler, tâches et api-server (conteneurs distincts, le secret
|
||||
# doit être partagé). Même générateur que ci-dessus.
|
||||
AIRFLOW_JWT_SECRET=change_me
|
||||
AIRFLOW_ADMIN_USERNAME=admin
|
||||
# Compte Airflow créé au premier démarrage (service `airflow-init`), sans rapport avec les
|
||||
# comptes `app_user` d'EnerVision.
|
||||
@@ -67,7 +70,7 @@ PUBLIC_ORIGIN=
|
||||
PROXY_HTTP_PORT=
|
||||
PROXY_HTTPS_PORT=
|
||||
# Réglages mémoire de la stack déployée. Sans eux, timescaledb-tune réserve 25 % de la RAM de la
|
||||
# machine à chaque base au premier démarrage, et le webserver Airflow lance 4 workers gunicorn.
|
||||
# machine à chaque base au premier démarrage. L'api-server Airflow 3 n'a rien à régler ici : son
|
||||
# nombre de workers vaut 1 par défaut, contre 4 pour le webserver d'Airflow 2.
|
||||
TS_TUNE_MEMORY=2GB
|
||||
TS_TUNE_NUM_CPUS=2
|
||||
AIRFLOW_WEBSERVER_WORKERS=2
|
||||
|
||||
@@ -10,6 +10,15 @@ updates:
|
||||
frontend-dependencies:
|
||||
patterns:
|
||||
- "*"
|
||||
ignore:
|
||||
# Pourquoi : @angular/build épingle typescript (>=6.0 <6.1) et vitest (^4). Une majeure
|
||||
# de l'un ou l'autre casse `npm ci` tant qu'Angular ne suit pas.
|
||||
- dependency-name: "typescript"
|
||||
update-types: ["version-update:semver-major"]
|
||||
- dependency-name: "vitest"
|
||||
update-types: ["version-update:semver-major"]
|
||||
- dependency-name: "@vitest/coverage-v8"
|
||||
update-types: ["version-update:semver-major"]
|
||||
|
||||
# Backend — uv (lit pyproject.toml / uv.lock)
|
||||
- package-ecosystem: "uv"
|
||||
|
||||
@@ -1,8 +1,9 @@
|
||||
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).
|
||||
# (contrairement à backend.yml et ml.yml) : celui de l'image apache/airflow retenue, et les tests
|
||||
# doivent tourner sur le même interpréteur qu'elle. 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
|
||||
@@ -47,10 +48,10 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: etl/airflow/uv.lock
|
||||
@@ -78,7 +79,7 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
- 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 .
|
||||
|
||||
@@ -30,10 +30,10 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: apps/backend/uv.lock
|
||||
@@ -90,10 +90,10 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: apps/backend/uv.lock
|
||||
@@ -126,10 +126,10 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: apps/backend/uv.lock
|
||||
@@ -150,12 +150,12 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
# 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
|
||||
uses: astral-sh/setup-uv@v7
|
||||
|
||||
# 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.
|
||||
|
||||
@@ -52,6 +52,7 @@ jobs:
|
||||
done
|
||||
echo "L'API ne répond pas après 3 minutes" >&2
|
||||
cd "/srv/enervision/${ENVIRONNEMENT}"
|
||||
docker compose ps
|
||||
docker compose logs --tail=50 backend proxy
|
||||
compose="docker compose -f docker-compose.yml -f docker-compose.prod.yml"
|
||||
$compose ps
|
||||
$compose logs --tail=50 backend proxy
|
||||
exit 1
|
||||
|
||||
@@ -17,10 +17,10 @@ jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/setup-node@v6
|
||||
- uses: actions/checkout@v7
|
||||
- uses: actions/setup-node@v7
|
||||
with:
|
||||
node-version: 24
|
||||
node-version: 26
|
||||
cache: npm
|
||||
cache-dependency-path: apps/frontend/package-lock.json
|
||||
|
||||
@@ -33,10 +33,10 @@ jobs:
|
||||
name: Audit des dépendances
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/setup-node@v6
|
||||
- uses: actions/checkout@v7
|
||||
- uses: actions/setup-node@v7
|
||||
with:
|
||||
node-version: 24
|
||||
node-version: 26
|
||||
# Seuil high : une vulnérabilité moderate de devDependency ne doit pas bloquer une livraison.
|
||||
- run: npm audit --audit-level=high --package-lock-only
|
||||
working-directory: apps/frontend
|
||||
@@ -45,10 +45,10 @@ jobs:
|
||||
needs: build
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/setup-node@v6
|
||||
- uses: actions/checkout@v7
|
||||
- uses: actions/setup-node@v7
|
||||
with:
|
||||
node-version: 24
|
||||
node-version: 26
|
||||
cache: npm
|
||||
cache-dependency-path: apps/frontend/package-lock.json
|
||||
- name : Installation des dépendances (Front)
|
||||
@@ -58,7 +58,7 @@ jobs:
|
||||
run: npm test --watch=false --code-coverage --coverageReporters=lcov
|
||||
working-directory: apps/frontend
|
||||
- name: Upload coverage
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: frontend-coverage
|
||||
path: apps/frontend/coverage/frontend/lcov.info
|
||||
|
||||
@@ -30,10 +30,10 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: ml/uv.lock
|
||||
@@ -67,12 +67,12 @@ jobs:
|
||||
|
||||
steps:
|
||||
- name: Récupère le dépôt
|
||||
uses: actions/checkout@v4
|
||||
uses: actions/checkout@v7
|
||||
|
||||
# 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
|
||||
uses: astral-sh/setup-uv@v7
|
||||
|
||||
- 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
|
||||
|
||||
@@ -24,10 +24,10 @@ jobs:
|
||||
build-front:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/setup-node@v6
|
||||
- uses: actions/checkout@v7
|
||||
- uses: actions/setup-node@v7
|
||||
with:
|
||||
node-version: 24
|
||||
node-version: 26
|
||||
cache: npm
|
||||
cache-dependency-path: apps/frontend/package-lock.json
|
||||
|
||||
@@ -40,10 +40,10 @@ jobs:
|
||||
needs: build-front
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/setup-node@v6
|
||||
- uses: actions/checkout@v7
|
||||
- uses: actions/setup-node@v7
|
||||
with:
|
||||
node-version: 24
|
||||
node-version: 26
|
||||
cache: npm
|
||||
cache-dependency-path: apps/frontend/package-lock.json
|
||||
|
||||
@@ -56,7 +56,7 @@ jobs:
|
||||
working-directory: apps/frontend
|
||||
|
||||
- name: Upload coverage
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: frontend-coverage
|
||||
path: apps/frontend/coverage/frontend/lcov.info
|
||||
@@ -64,9 +64,9 @@ jobs:
|
||||
build-back:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v7
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: apps/backend/uv.lock
|
||||
@@ -95,9 +95,9 @@ jobs:
|
||||
needs: build-back
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v7
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: apps/backend/uv.lock
|
||||
@@ -107,7 +107,7 @@ jobs:
|
||||
working-directory: apps/backend
|
||||
|
||||
- name: Upload coverage
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: backend-coverage
|
||||
path: apps/backend/coverage.xml
|
||||
@@ -115,9 +115,9 @@ jobs:
|
||||
test-ml:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v7
|
||||
- name: Installe uv
|
||||
uses: astral-sh/setup-uv@v5
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
enable-cache: true
|
||||
cache-dependency-glob: ml/uv.lock
|
||||
@@ -135,7 +135,7 @@ jobs:
|
||||
working-directory: ml
|
||||
|
||||
- name: Upload coverage
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v7
|
||||
with:
|
||||
name: ml-coverage
|
||||
path: ml/coverage.xml
|
||||
@@ -143,23 +143,26 @@ jobs:
|
||||
sonarqube:
|
||||
needs: [build-front, build-back, test-front, test-back, test-ml]
|
||||
name: SonarQube
|
||||
# Pourquoi : GitHub ne fournit pas les secrets aux workflows lancés par dependabot[bot].
|
||||
# Sans SONAR_TOKEN le scan échoue sans rien analyser ; build et tests restent joués.
|
||||
if: github.actor != 'dependabot[bot]'
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v6
|
||||
- uses: actions/checkout@v7
|
||||
with:
|
||||
fetch-depth: 0
|
||||
- name: Téléchargement du rapport de couverture (Front)
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: frontend-coverage
|
||||
path: apps/frontend/coverage/frontend
|
||||
- name: Téléchargement du rapport de couverture (Back)
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: backend-coverage
|
||||
path: apps/backend
|
||||
- name: Téléchargement du rapport de couverture (ML)
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v8
|
||||
with:
|
||||
name: ml-coverage
|
||||
path: ml
|
||||
|
||||
@@ -40,7 +40,6 @@ kubeconfig
|
||||
# Airflow
|
||||
etl/airflow/logs/
|
||||
airflow.db
|
||||
airflow-webserver.pid
|
||||
standalone_admin_password.txt
|
||||
|
||||
# Environnement et secrets
|
||||
|
||||
@@ -67,7 +67,7 @@ services-up: ## Démarre les services conteneurisés dont `make dev` dépend (ba
|
||||
docker compose up -d db mailpit
|
||||
@$(MAKE) --no-print-directory db-wait
|
||||
@$(MAKE) --no-print-directory db-ensure-airflow
|
||||
docker compose up -d airflow-init airflow-webserver airflow-scheduler
|
||||
docker compose up -d airflow-init airflow-apiserver airflow-scheduler airflow-dag-processor
|
||||
|
||||
dev-backend: ## Lance l'API seule en rechargement à chaud
|
||||
@echo "backend -> http://localhost:8000 (docs sur /docs)"
|
||||
@@ -132,12 +132,12 @@ airflow-test: ## Verifie que les DAGs s'importent sans erreur et ont la structur
|
||||
|
||||
airflow-check: airflow-lint airflow-test ## Chaîne de vérification complète des DAGs Airflow
|
||||
|
||||
airflow-up: db-ensure-airflow ## Démarre Airflow (webserver + scheduler, LocalExecutor). db-up requis avant.
|
||||
docker compose up -d airflow-init airflow-webserver airflow-scheduler
|
||||
airflow-up: db-ensure-airflow ## Démarre Airflow (api-server + scheduler + dag-processor, LocalExecutor). db-up requis avant.
|
||||
docker compose up -d airflow-init airflow-apiserver airflow-scheduler airflow-dag-processor
|
||||
@echo "airflow -> http://localhost:$${AIRFLOW_PORT:-8080}"
|
||||
|
||||
airflow-down: ## Arrête le webserver et le scheduler Airflow
|
||||
docker compose stop airflow-webserver airflow-scheduler
|
||||
airflow-down: ## Arrête l'api-server, le scheduler et le dag-processor Airflow
|
||||
docker compose stop airflow-apiserver airflow-scheduler airflow-dag-processor
|
||||
|
||||
airflow-logs: ## Suit les journaux du scheduler Airflow (où tournent les tâches, LocalExecutor)
|
||||
docker compose logs -f airflow-scheduler
|
||||
|
||||
@@ -9,8 +9,10 @@ series temporelles energetiques, deployee sur une machine on-premise.
|
||||
|-------|----------------------------------------------------------|
|
||||
| J1 | Valider la préparation de l'environnement et du repo |
|
||||
| J2 | Valider le périmètre retenu et les choix technologiques |
|
||||
| J3 | Valider l'architecture et la gestion de la sécurité |
|
||||
| J4 | Valider la robustesse et assurer les livrables |
|
||||
| J3 | Ingestion & backend |
|
||||
| J4 | Architecture, sécurité & frontend |
|
||||
| J5 | Valider la robustesse et assurer les livrables |
|
||||
| J6 | Amélioration possible |
|
||||
|
||||
Ce que la documentation apporte à chacun : [docs/architecture/00-vue-ensemble.md](docs/architecture/00-vue-ensemble.md).
|
||||
|
||||
@@ -18,15 +20,15 @@ Ce que la documentation apporte à chacun : [docs/architecture/00-vue-ensemble.m
|
||||
|
||||
| Domaine | Technologie | Emplacement | Etat |
|
||||
|------------|-------------------------------------|---------------------|---------------|
|
||||
| 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 |
|
||||
| Backend | FastAPI, Python 3.14 | `apps/backend` | En place |
|
||||
| Frontend | Angular 22, Node 26 | `apps/frontend` | En place |
|
||||
| Base | PostgreSQL 17 + TimescaleDB | `db` | En place |
|
||||
| ETL | Apache Airflow | `etl/airflow` | Quatre DAGs |
|
||||
| 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 |
|
||||
| CI/CD | GitHub Actions | `.github/workflows` | En place |
|
||||
| Monitoring | Prometheus, Grafana, Alertmanager | `monitoring` | A initialiser |
|
||||
| ML | LightGBM, MLflow | `ml` | Entrainement initialise |
|
||||
| ML | LightGBM, MLflow | `ml` | En place |
|
||||
|
||||
Le backend, la base et l'infrastructure (Terraform/k3s) sont initialises a ce stade. Le frontend
|
||||
sert un tableau de bord sur `/dashboard`, dont les données proviennent de fixtures : les endpoints
|
||||
@@ -92,8 +94,9 @@ et frontend en rechargement a chaud sur le poste.
|
||||
| Mailpit | <http://localhost:8025> |
|
||||
|
||||
Le `.env` doit porter les cles Airflow avant le premier `make dev` : `AIRFLOW_FERNET_KEY`,
|
||||
`AIRFLOW_WEBSERVER_SECRET_KEY`, `AIRFLOW_APP_SECRET_KEY` et `AIRFLOW_ADMIN_PASSWORD`. Sans elles
|
||||
`airflow-init` refuse de demarrer, et `airflow-webserver` comme `airflow-scheduler` avec lui.
|
||||
`AIRFLOW_API_SECRET_KEY`, `AIRFLOW_JWT_SECRET`, `AIRFLOW_APP_SECRET_KEY` et
|
||||
`AIRFLOW_ADMIN_PASSWORD`. Sans elles `airflow-init` refuse de demarrer, et `airflow-apiserver`,
|
||||
`airflow-scheduler` et `airflow-dag-processor` avec lui.
|
||||
|
||||
Les cibles d'origine restent disponibles pour ne demarrer qu'une partie : `make db-up`,
|
||||
`make airflow-up`, `make dev-backend`, `make dev-frontend`.
|
||||
|
||||
Generated
+37
-37
@@ -655,31 +655,31 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "pandas"
|
||||
version = "3.0.5"
|
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version = "3.0.6"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "numpy" },
|
||||
{ name = "python-dateutil" },
|
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{ name = "tzdata", marker = "sys_platform == 'emscripten' or sys_platform == 'win32'" },
|
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||||
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||||
[[package]]
|
||||
@@ -936,27 +936,27 @@ wheels = [
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||||
|
||||
[[package]]
|
||||
name = "ruff"
|
||||
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||||
[[package]]
|
||||
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||||
@@ -3,7 +3,7 @@
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||||
# ==================
|
||||
|
||||
# Image pour frontend
|
||||
FROM node:24-alpine3.22 AS builder
|
||||
FROM node:26-alpine3.22 AS builder
|
||||
|
||||
WORKDIR /app
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||||
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||||
@@ -23,7 +23,7 @@ RUN npm run build
|
||||
# ==================
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||||
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||||
|
||||
FROM nginx:1.28-alpine AS runner
|
||||
FROM nginx:1.31-alpine AS runner
|
||||
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||||
# Copie de la configuration de nginx
|
||||
COPY --chown=root:root --chmod=755 nginx.conf /etc/nginx/nginx.conf
|
||||
|
||||
Generated
+95
-174
@@ -8,12 +8,12 @@
|
||||
"name": "frontend",
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||||
"version": "0.0.0",
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||||
"dependencies": {
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"@angular/common": "^22.1.0",
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||||
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||||
"@angular/forms": "^22.1.0",
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||||
"@angular/platform-browser": "^22.1.0",
|
||||
"@angular/router": "^22.1.0",
|
||||
"@angular/common": "^22.1.7",
|
||||
"@angular/compiler": "^22.1.7",
|
||||
"@angular/core": "^22.1.7",
|
||||
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|
||||
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|
||||
"@angular/router": "^22.1.7",
|
||||
"chart.js": "^4.5.1",
|
||||
"rxjs": "~7.8.0",
|
||||
"tslib": "^2.3.0"
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||||
@@ -21,21 +21,14 @@
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"devDependencies": {
|
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|
||||
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|
||||
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|
||||
"@angular/compiler-cli": "^22.1.7",
|
||||
"@vitest/coverage-v8": "^4.1.11",
|
||||
"jsdom": "^28.0.0",
|
||||
"prettier": "^3.8.1",
|
||||
"jsdom": "^30.1.0",
|
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"prettier": "^3.9.8",
|
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"typescript": "~6.0.2",
|
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"vitest": "^4.0.8"
|
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"vitest": "^4.1.11"
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"node_modules/@acemir/cssom": {
|
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"version": "0.9.31",
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"resolved": "https://registry.npmjs.org/@acemir/cssom/-/cssom-0.9.31.tgz",
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"dev": true,
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"license": "MIT"
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"node_modules/@ampproject/remapping": {
|
||||
"version": "2.3.0",
|
||||
"resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.3.0.tgz",
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||||
@@ -255,9 +248,9 @@
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||||
}
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||||
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||||
"node_modules/@angular/common": {
|
||||
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|
||||
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|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"tslib": "^2.3.0"
|
||||
@@ -266,14 +259,14 @@
|
||||
"node": "^22.22.3 || ^24.15.0 || >=26.0.0"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@angular/core": "22.1.6",
|
||||
"@angular/core": "22.1.7",
|
||||
"rxjs": "^6.5.3 || ^7.4.0"
|
||||
}
|
||||
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|
||||
"node_modules/@angular/compiler": {
|
||||
"version": "22.1.6",
|
||||
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"version": "22.1.7",
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||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"tslib": "^2.3.0"
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||||
@@ -283,9 +276,9 @@
|
||||
}
|
||||
},
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||||
"node_modules/@angular/compiler-cli": {
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||||
"version": "22.1.6",
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"resolved": "https://registry.npmjs.org/@angular/compiler-cli/-/compiler-cli-22.1.6.tgz",
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"integrity": "sha512-C1fQuaSLnibhfbb7Im/vurdBEcfQk+/GqPkY4+dgEKd4EPleO0xWlD+k5DwyNFX8a9w7HebWfo0Zl66HuaEwOQ==",
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"version": "22.1.7",
|
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"resolved": "https://registry.npmjs.org/@angular/compiler-cli/-/compiler-cli-22.1.7.tgz",
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||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">= 14"
|
||||
}
|
||||
},
|
||||
"node_modules/jsdom/node_modules/https-proxy-agent": {
|
||||
"version": "7.0.6",
|
||||
"resolved": "https://registry.npmjs.org/https-proxy-agent/-/https-proxy-agent-7.0.6.tgz",
|
||||
"integrity": "sha512-vK9P5/iUfdl95AI+JVyUuIcVtd4ofvtrOr3HNtM2yxC9bnMbEdp3x01OhQNnjb8IJYi38VlTE3mBXwcfvywuSw==",
|
||||
"node_modules/jsdom/node_modules/whatwg-url": {
|
||||
"version": "17.1.1",
|
||||
"resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-17.1.1.tgz",
|
||||
"integrity": "sha512-ohjk1mdUebJVadRt3bAhQhx8lSnISq+GDttK79LFl8EHQkAPvzwctoasC4hs8tBt6kLAncBWWyq1N52qEfKvDw==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"agent-base": "^7.1.2",
|
||||
"debug": "4"
|
||||
"@exodus/bytes": "^1.15.1",
|
||||
"tr46": "^6.0.0",
|
||||
"webidl-conversions": "^8.0.1"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 14"
|
||||
"node": "^22.14.0 || >=24.0.0"
|
||||
}
|
||||
},
|
||||
"node_modules/jsesc": {
|
||||
@@ -6708,9 +6636,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/prettier": {
|
||||
"version": "3.9.6",
|
||||
"resolved": "https://registry.npmjs.org/prettier/-/prettier-3.9.6.tgz",
|
||||
"integrity": "sha512-OpN0zzVdiaiAhxpuuj5efpIS4sY9j7bY6uR5mnj5yPzGkdkjNKSJeUThPb60Jw29QuAZgA4o+/iB49kFiaBX6g==",
|
||||
"version": "3.9.8",
|
||||
"resolved": "https://registry.npmjs.org/prettier/-/prettier-3.9.8.tgz",
|
||||
"integrity": "sha512-WRFq3Wn3WId7LLROfMLdH7xaFr2jR62wU8nLO6rQUOLOxNZUviyJQs1M0iIhLexSFy+L+w0ch66wtoO2jRjG0A==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"bin": {
|
||||
@@ -7308,13 +7236,6 @@
|
||||
"node": ">=8"
|
||||
}
|
||||
},
|
||||
"node_modules/symbol-tree": {
|
||||
"version": "3.2.4",
|
||||
"resolved": "https://registry.npmjs.org/symbol-tree/-/symbol-tree-3.2.4.tgz",
|
||||
"integrity": "sha512-9QNk5KwDF+Bvz+PyObkmSYjI5ksVUYtjW7AU22r2NKcfLJcXp96hkDWU3+XndOsUb+AQ9QhfzfCT2O+CNWT5Tw==",
|
||||
"dev": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/tinybench": {
|
||||
"version": "2.9.0",
|
||||
"resolved": "https://registry.npmjs.org/tinybench/-/tinybench-2.9.0.tgz",
|
||||
@@ -7469,13 +7390,13 @@
|
||||
}
|
||||
},
|
||||
"node_modules/undici": {
|
||||
"version": "7.29.1",
|
||||
"resolved": "https://registry.npmjs.org/undici/-/undici-7.29.1.tgz",
|
||||
"integrity": "sha512-RYONW2MeafgYlkVOKYKkA/Ag7BmXqgIWCa8t1m0JcxrQg9pI9lEqRhAOruOBCbAohOa/gkCF+iPi9hrgvTzu6Q==",
|
||||
"version": "8.10.2",
|
||||
"resolved": "https://registry.npmjs.org/undici/-/undici-8.10.2.tgz",
|
||||
"integrity": "sha512-/y4/bH9YNU5hi9NIrpOuvGXFcxrj3CMrV+/AYpowAYTpHn8gX/XPFjNy766FPoYY0miQhdW977JFWKGNhBdwyQ==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">=20.18.1"
|
||||
"node": ">=22.19.0"
|
||||
}
|
||||
},
|
||||
"node_modules/unpipe": {
|
||||
|
||||
+10
-10
@@ -12,12 +12,12 @@
|
||||
"private": true,
|
||||
"packageManager": "npm@11.19.0",
|
||||
"dependencies": {
|
||||
"@angular/common": "^22.1.0",
|
||||
"@angular/compiler": "^22.1.0",
|
||||
"@angular/core": "^22.1.0",
|
||||
"@angular/forms": "^22.1.0",
|
||||
"@angular/platform-browser": "^22.1.0",
|
||||
"@angular/router": "^22.1.0",
|
||||
"@angular/common": "^22.1.7",
|
||||
"@angular/compiler": "^22.1.7",
|
||||
"@angular/core": "^22.1.7",
|
||||
"@angular/forms": "^22.1.7",
|
||||
"@angular/platform-browser": "^22.1.7",
|
||||
"@angular/router": "^22.1.7",
|
||||
"chart.js": "^4.5.1",
|
||||
"rxjs": "~7.8.0",
|
||||
"tslib": "^2.3.0"
|
||||
@@ -25,11 +25,11 @@
|
||||
"devDependencies": {
|
||||
"@angular/build": "^22.1.8",
|
||||
"@angular/cli": "^22.1.8",
|
||||
"@angular/compiler-cli": "^22.1.0",
|
||||
"@angular/compiler-cli": "^22.1.7",
|
||||
"@vitest/coverage-v8": "^4.1.11",
|
||||
"jsdom": "^28.0.0",
|
||||
"prettier": "^3.8.1",
|
||||
"jsdom": "^30.1.0",
|
||||
"prettier": "^3.9.8",
|
||||
"typescript": "~6.0.2",
|
||||
"vitest": "^4.0.8"
|
||||
"vitest": "^4.1.11"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
-- Base de metadonnees Airflow (webserver + scheduler, LocalExecutor). Separee de la base
|
||||
-- Base de metadonnees Airflow (api-server + scheduler + dag-processor, 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).
|
||||
|
||||
@@ -22,11 +22,9 @@ services:
|
||||
ports: !override
|
||||
- "127.0.0.1:${MAILPIT_UI_PORT:-8025}:8025"
|
||||
|
||||
airflow-webserver:
|
||||
airflow-apiserver:
|
||||
ports: !override
|
||||
- "127.0.0.1:${AIRFLOW_PORT:-8080}:8080"
|
||||
environment:
|
||||
AIRFLOW__WEBSERVER__WORKERS: ${AIRFLOW_WEBSERVER_WORKERS:-2}
|
||||
|
||||
backend:
|
||||
ports: !reset null
|
||||
@@ -51,7 +49,7 @@ services:
|
||||
ports: !reset null
|
||||
|
||||
proxy:
|
||||
image: nginx:1.28-alpine
|
||||
image: nginx:1.31-alpine
|
||||
depends_on:
|
||||
backend:
|
||||
condition: service_healthy
|
||||
|
||||
+31
-13
@@ -5,9 +5,9 @@
|
||||
|
||||
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
|
||||
# Piege : LocalExecutor fait tourner les taches comme sous-processus du scheduler, jamais de
|
||||
# l'api-server. `airflow_ml_state` (modele entraine, magasin MLflow) n'a donc besoin d'etre monte
|
||||
# que sur `airflow-scheduler` en pratique, mais reste partage avec l'api-server pour que ce
|
||||
# dernier puisse au besoin l'inspecter sans en devenir dependant.
|
||||
x-airflow-common: &airflow-common
|
||||
build:
|
||||
@@ -19,9 +19,16 @@ x-airflow-common: &airflow-common
|
||||
# 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-init` (ci-dessous), dont `api-server`, `dag-processor` et `scheduler` dependent.
|
||||
AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW_FERNET_KEY:-}
|
||||
AIRFLOW__WEBSERVER__SECRET_KEY: ${AIRFLOW_WEBSERVER_SECRET_KEY:-}
|
||||
AIRFLOW__API__SECRET_KEY: ${AIRFLOW_API_SECRET_KEY:-}
|
||||
# Signe les jetons entre scheduler, tâches et api-server. Conteneurs distincts : un secret
|
||||
# généré au démarrage ne serait pas partagé, il doit venir du .env.
|
||||
AIRFLOW__API_AUTH__JWT_SECRET: ${AIRFLOW_JWT_SECRET:-}
|
||||
AIRFLOW__CORE__EXECUTION_API_SERVER_URL: http://airflow-apiserver:8080/execution/
|
||||
# FabAuthManager plutôt que le SimpleAuthManager par défaut d'Airflow 3 : seul le provider
|
||||
# FAB sait créer le compte admin que `airflow-init` pose via `_AIRFLOW_WWW_USER_*`.
|
||||
AIRFLOW__CORE__AUTH_MANAGER: airflow.providers.fab.auth_manager.fab_auth_manager.FabAuthManager
|
||||
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.
|
||||
@@ -111,11 +118,11 @@ services:
|
||||
# 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`).
|
||||
# `pgdata` deja peuple) fait echouer ce service, et api-server, dag-processor et 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.
|
||||
# refuse en plus les cles et secrets vides.
|
||||
airflow-init:
|
||||
<<: *airflow-common
|
||||
restart: "no"
|
||||
@@ -135,13 +142,14 @@ services:
|
||||
- |
|
||||
set -euo pipefail
|
||||
: "$${AIRFLOW__CORE__FERNET_KEY:?AIRFLOW_FERNET_KEY manquant dans .env}"
|
||||
: "$${AIRFLOW__WEBSERVER__SECRET_KEY:?AIRFLOW_WEBSERVER_SECRET_KEY manquant dans .env}"
|
||||
: "$${AIRFLOW__API__SECRET_KEY:?AIRFLOW_API_SECRET_KEY manquant dans .env}"
|
||||
: "$${AIRFLOW__API_AUTH__JWT_SECRET:?AIRFLOW_JWT_SECRET manquant dans .env}"
|
||||
: "$${APP_SECRET_KEY:?AIRFLOW_APP_SECRET_KEY manquant dans .env}"
|
||||
exec airflow version
|
||||
|
||||
airflow-webserver:
|
||||
airflow-apiserver:
|
||||
<<: *airflow-common
|
||||
command: webserver
|
||||
command: api-server
|
||||
ports:
|
||||
- "${AIRFLOW_PORT:-8080}:8080"
|
||||
depends_on:
|
||||
@@ -150,7 +158,7 @@ services:
|
||||
airflow-init:
|
||||
condition: service_completed_successfully
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
|
||||
test: ["CMD", "curl", "--fail", "http://localhost:8080/api/v2/monitor/health"]
|
||||
interval: 30s
|
||||
timeout: 10s
|
||||
retries: 5
|
||||
@@ -165,6 +173,16 @@ services:
|
||||
airflow-init:
|
||||
condition: service_completed_successfully
|
||||
|
||||
# Obligatoire depuis Airflow 3 : le scheduler ne parse plus les fichiers de dags/ lui-même.
|
||||
airflow-dag-processor:
|
||||
<<: *airflow-common
|
||||
command: dag-processor
|
||||
depends_on:
|
||||
db:
|
||||
condition: service_healthy
|
||||
airflow-init:
|
||||
condition: service_completed_successfully
|
||||
|
||||
volumes:
|
||||
pgdata:
|
||||
airflow_logs:
|
||||
|
||||
@@ -63,8 +63,9 @@ secret.
|
||||
|
||||
- Deux TimescaleDB sur une machine de 8 Go : sans réglage, chacune se réserverait 25 % de la
|
||||
RAM au premier démarrage. L'overlay fixe `TS_TUNE_MEMORY` à 2 Go et `TS_TUNE_NUM_CPUS` à 2 par
|
||||
base, et 2 workers gunicorn par webserver Airflow. La montée à 32 Go prévue par les
|
||||
consignes est à demander.
|
||||
base. Airflow 3 n'a rien à régler de ce côté : son api-server lance un seul worker par défaut,
|
||||
là où le webserver d'Airflow 2 en lançait quatre. La montée à 32 Go prévue par les consignes
|
||||
est à demander.
|
||||
- Un runner auto-hébergé sur un dépôt public exécute le code qu'on lui envoie. `deploy.yml` ne
|
||||
se déclenche jamais sur `pull_request`, le runner tourne sous un utilisateur dédié, et le
|
||||
dépôt doit exiger une approbation pour les workflows des PR externes.
|
||||
|
||||
@@ -49,20 +49,28 @@ Trois pièges sont documentés en tête du `docker-compose.yml`, ils ne se devin
|
||||
- `db/init` est monté **fichier par fichier**. Monter le dossier masquerait les scripts d'init de
|
||||
l'image, dont `timescaledb-tune`. Ajouter un fichier dans `db/init/` impose donc une ligne dans
|
||||
le compose. Voir [`db/README.md`](../../db/README.md).
|
||||
- `LocalExecutor` exécute les tâches comme sous-processus du **scheduler**, jamais du webserver :
|
||||
- `LocalExecutor` exécute les tâches comme sous-processus du **scheduler**, jamais de l'api-server :
|
||||
c'est le scheduler qui a besoin du volume `airflow_ml_state` (modèle, magasin MLflow).
|
||||
|
||||
### Airflow (issues #115, #116 et #119)
|
||||
|
||||
Trois services, `docker compose profiles` non utilisés (démarrage explicite via `make
|
||||
Quatre services (Airflow 3.3), `docker compose profiles` non utilisés (démarrage explicite via `make
|
||||
airflow-up`, pas dans `make dev`) :
|
||||
|
||||
| Service | Rôle | Points notables |
|
||||
|---|---|---|
|
||||
| `airflow-init` | Migre la base de métadonnées, crée le compte admin | Conteneur jetable (`restart: "no"`), ne redémarre jamais. `webserver`/`scheduler` attendent qu'il se termine avec succès |
|
||||
| `airflow-webserver` | UI, port `8080` | `LocalExecutor` : n'exécute aucune tâche lui-même |
|
||||
| `airflow-init` | Migre la base de métadonnées, crée le compte admin | Conteneur jetable (`restart: "no"`), ne redémarre jamais. `api-server`, `dag-processor` et `scheduler` attendent qu'il se termine avec succès |
|
||||
| `airflow-apiserver` | UI et API REST (`/api/v2`), port `8080` | `LocalExecutor` : n'exécute aucune tâche lui-même. Sert aussi l'Execution API que les tâches appellent, d'où le secret JWT partagé |
|
||||
| `airflow-dag-processor` | Parse `dags/` et publie les DAGs sérialisés | Composant à part entière depuis Airflow 3 : le scheduler ne lit plus les fichiers de DAG |
|
||||
| `airflow-scheduler` | Planifie et **exécute** les tâches (`LocalExecutor`) | Les DAGs y tournent en sous-processus (`uv run --no-sync python -m ...`), c'est lui qui a besoin du volume `airflow_ml_state` |
|
||||
|
||||
Airflow 3 impose deux choses que le compose reflète : les tâches ne touchent plus la base de
|
||||
métadonnées et passent par l'Execution API de l'`api-server`, avec un jeton signé par
|
||||
`AIRFLOW_JWT_SECRET` (secret partagé entre conteneurs, jamais celui généré au démarrage) ; et
|
||||
l'authentification par défaut (`SimpleAuthManager`) ne sait pas créer de compte, d'où le
|
||||
`FabAuthManager` qui garde le compte admin posé par `airflow-init`. Pas de `triggerer` : aucun
|
||||
opérateur déférable dans les DAGs.
|
||||
|
||||
Construits depuis `etl/airflow/Dockerfile`, contexte `.` (racine du repo, pas `etl/airflow/`) :
|
||||
l'image doit pouvoir `COPY` les sources de `ml/` **et** de `apps/backend/` pour se synchroniser
|
||||
deux environnements Python **3.14** (`/opt/ml/.venv` et `/opt/backend/.venv`, `uv sync --locked` à
|
||||
@@ -102,14 +110,14 @@ rend contraignant.
|
||||
`airflow-init` s'appuie sur l'entrypoint de l'image (`_AIRFLOW_DB_MIGRATE`,
|
||||
`_AIRFLOW_WWW_USER_*`) plutôt que sur un script maison : l'entrypoint porte le code de sortie, une
|
||||
migration ratée (typiquement la base `airflow` absente, cf. ci-dessous) fait échouer le service et
|
||||
`webserver`/`scheduler` ne démarrent pas sur une base non migrée. Le mot de passe du compte admin
|
||||
`api-server`, `dag-processor` et `scheduler` ne démarrent pas sur une base non migrée. Le mot de passe du compte admin
|
||||
passe par l'environnement, jamais par `argv` (ni `ps`, ni `docker compose config`).
|
||||
|
||||
Les variables `AIRFLOW_*` ne sont volontairement pas en `${VAR:?}` : Compose interpole le fichier
|
||||
entier avant de filtrer les services, une variable requise manquante casserait `make db-up`,
|
||||
`make dev`... pour tout poste dont le `.env` est antérieur. Elles valent `${VAR:-}` et c'est
|
||||
`airflow-init` qui refuse de démarrer (clé Fernet, clé Flask, mot de passe ou
|
||||
`AIRFLOW_APP_SECRET_KEY` vides).
|
||||
`airflow-init` qui refuse de démarrer (clé Fernet, clé de session de l'API, secret JWT, mot de
|
||||
passe ou `AIRFLOW_APP_SECRET_KEY` vides).
|
||||
|
||||
Le conteneur reçoit deux variables du backend en plus de `ML_DATABASE_URL` : `DATABASE_URL`, en
|
||||
dialecte asyncpg, et `APP_SECRET_KEY`, alimentée par `AIRFLOW_APP_SECRET_KEY`. Cette dernière est
|
||||
@@ -277,7 +285,7 @@ Ces arbitrages sont pris. Ils ne vivaient jusqu'ici que dans des commentaires de
|
||||
| Base applicative | `enervision` | Variable `POSTGRES_DB` |
|
||||
| Base de test | `enervision_test` | Créée par `db/init/110-test-database.sql`, nom attendu en dur par `apps/backend/tests/conftest.py` |
|
||||
| Base de métadonnées Airflow | `airflow` | Créée par `db/init/120-airflow-database.sql`, même conteneur `db` |
|
||||
| Webserver Airflow | `8080` | `make airflow-up`. Scheduler et webserver ne publient que ce port ; les tâches (`LocalExecutor`) tournent côté scheduler, sans port propre |
|
||||
| API server Airflow | `8080` | `make airflow-up`. Api-server, scheduler et dag-processor ne publient que ce port ; les tâches (`LocalExecutor`) tournent côté scheduler, sans port propre |
|
||||
|
||||
## Le trou vers k3s
|
||||
|
||||
|
||||
@@ -90,9 +90,10 @@ rien changer), mais ce serait à borner sur un dépôt à forte fréquence de pu
|
||||
`backend.yml`, `ml.yml` et `airflow.yml` déclarent en plus un groupe de concurrence par référence
|
||||
git avec `cancel-in-progress`, ce qui annule un run devenu obsolète par un push plus récent.
|
||||
|
||||
**Piège de version** : `etl/airflow` tourne en **Python 3.12** et non 3.14, parce qu'Airflow 2.10
|
||||
ne supporte pas encore 3.14. Le 3.14 du module ML ne vit, dans ce contexte, que dans l'image
|
||||
Docker et son propre environnement.
|
||||
**Piège de version** : `etl/airflow` tourne en **Python 3.12** et non 3.14 : c'est l'interpréteur
|
||||
de l'image `apache/airflow:3.3.2-python3.12` retenue, et les tests d'intégrité doivent tourner sur
|
||||
le même. Le 3.14 du module ML ne vit, dans ce contexte, que dans l'image Docker et son propre
|
||||
environnement.
|
||||
|
||||
## Déploiement
|
||||
|
||||
|
||||
@@ -1,9 +1,9 @@
|
||||
# Image Airflow EnerVision : ajoute ml/ et apps/backend/ dans leurs propres environnements Python
|
||||
# 3.14, distincts du Python 3.12 qui fait tourner Airflow lui-meme (apache-airflow 2.10 ne supporte
|
||||
# pas 3.14), pour que les DAGs puissent lancer `uv run python -m enervision_ml.train`/`.score`,
|
||||
# 3.14, distincts du Python 3.12 de l'image de base qui fait tourner Airflow lui-meme, pour que
|
||||
# les DAGs puissent lancer `uv run python -m enervision_ml.train`/`.score`,
|
||||
# `app.detection.internal_alerts` et `app.cli` en sous-processus. Airflow ne devient jamais un
|
||||
# consommateur direct de LightGBM, de MLflow ou du SQLAlchemy du backend. Cf. ADR 0008.
|
||||
FROM apache/airflow:2.10.4-python3.12
|
||||
FROM apache/airflow:3.3.2-python3.12
|
||||
|
||||
# LightGBM est compile contre libgomp (OpenMP), absent de l'image de base (minimale, sans
|
||||
# toolchain de compilation). Sans lui : `OSError: libgomp.so.1: cannot open shared object file`
|
||||
@@ -21,9 +21,8 @@ RUN apt-get update \
|
||||
RUN mkdir -p /opt/ml/state /opt/backend && chown -R airflow:root /opt/ml /opt/backend
|
||||
USER airflow
|
||||
|
||||
# L'image de base embarque deja un `uv`, mais trop ancien (0.4.29) pour le format de verrou de
|
||||
# `ml/uv.lock`. On le remplace par la version deja pinnee ailleurs dans le depot
|
||||
# (apps/backend/Dockerfile).
|
||||
# L'image de base embarque deja un `uv`, mais pas celui que le depot epingle par ailleurs
|
||||
# (apps/backend/Dockerfile) : on aligne, pour que le format de verrou lu soit le meme partout.
|
||||
COPY --from=ghcr.io/astral-sh/uv:0.11.26 /uv /home/airflow/.local/bin/uv
|
||||
|
||||
# Piege : pas de `UV_PROJECT_ENVIRONMENT` global. Il vaudrait pour les deux projets, et `uv run`
|
||||
|
||||
@@ -15,8 +15,8 @@ from __future__ import annotations
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from airflow.models.dag import DAG
|
||||
from airflow.operators.bash import BashOperator
|
||||
from airflow.providers.standard.operators.bash import BashOperator
|
||||
from airflow.sdk import DAG
|
||||
|
||||
# Le backend a son propre environnement uv dans l'image (ADR 0008). `--no-sync` et
|
||||
# `env -u VIRTUAL_ENV` : cf. `ml_train.py`, même raisonnement.
|
||||
|
||||
@@ -1,45 +1,45 @@
|
||||
"""DAG d'import du dataset historique EnerVision (issue #119).
|
||||
|
||||
Orchestre le pipeline existant `app.etl.historical_import` sans dupliquer sa logique ETL.
|
||||
Le dataset historique sert à initialiser l'environnement : le DAG reste donc manuel.
|
||||
|
||||
Le backend est exécuté dans l'environnement `/opt/backend` embarqué dans l'image Airflow,
|
||||
sur le même patron que le DAG `alertes` (ADR 0008).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from airflow.models.dag import DAG
|
||||
from airflow.operators.bash import BashOperator
|
||||
|
||||
COMMANDE_BACKEND = "cd /opt/backend && env -u VIRTUAL_ENV uv run --no-sync python -m"
|
||||
|
||||
CSV_PATH = "/opt/data/raw/all_sites_combined.csv"
|
||||
METADATA_PATH = "/opt/data/raw/dataset_metadata.json"
|
||||
SOURCE_TIMEZONE = "UTC"
|
||||
BATCH_SIZE = 1000
|
||||
|
||||
with DAG(
|
||||
dag_id="historical_import",
|
||||
description="Importe le dataset historique CSV/JSON dans dataset, site et reading.",
|
||||
schedule=None,
|
||||
start_date=datetime(2026, 1, 1),
|
||||
catchup=False,
|
||||
max_active_runs=1,
|
||||
tags=["etl", "historical"],
|
||||
) as dag:
|
||||
BashOperator(
|
||||
task_id="import_historical",
|
||||
bash_command=(
|
||||
f"{COMMANDE_BACKEND} app.etl.historical_import "
|
||||
f"--csv {CSV_PATH} "
|
||||
f"--metadata {METADATA_PATH} "
|
||||
"--source-timezone UTC "
|
||||
"--batch-size 1000"
|
||||
),
|
||||
retries=1,
|
||||
retry_delay=timedelta(minutes=2),
|
||||
execution_timeout=timedelta(minutes=30),
|
||||
)
|
||||
"""DAG d'import du dataset historique EnerVision (issue #119).
|
||||
|
||||
Orchestre le pipeline existant `app.etl.historical_import` sans dupliquer sa logique ETL.
|
||||
Le dataset historique sert à initialiser l'environnement : le DAG reste donc manuel.
|
||||
|
||||
Le backend est exécuté dans l'environnement `/opt/backend` embarqué dans l'image Airflow,
|
||||
sur le même patron que le DAG `alertes` (ADR 0008).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from airflow.providers.standard.operators.bash import BashOperator
|
||||
from airflow.sdk import DAG
|
||||
|
||||
COMMANDE_BACKEND = "cd /opt/backend && env -u VIRTUAL_ENV uv run --no-sync python -m"
|
||||
|
||||
CSV_PATH = "/opt/data/raw/all_sites_combined.csv"
|
||||
METADATA_PATH = "/opt/data/raw/dataset_metadata.json"
|
||||
SOURCE_TIMEZONE = "UTC"
|
||||
BATCH_SIZE = 1000
|
||||
|
||||
with DAG(
|
||||
dag_id="historical_import",
|
||||
description="Importe le dataset historique CSV/JSON dans dataset, site et reading.",
|
||||
schedule=None,
|
||||
start_date=datetime(2026, 1, 1),
|
||||
catchup=False,
|
||||
max_active_runs=1,
|
||||
tags=["etl", "historical"],
|
||||
) as dag:
|
||||
BashOperator(
|
||||
task_id="import_historical",
|
||||
bash_command=(
|
||||
f"{COMMANDE_BACKEND} app.etl.historical_import "
|
||||
f"--csv {CSV_PATH} "
|
||||
f"--metadata {METADATA_PATH} "
|
||||
"--source-timezone UTC "
|
||||
"--batch-size 1000"
|
||||
),
|
||||
retries=1,
|
||||
retry_delay=timedelta(minutes=2),
|
||||
execution_timeout=timedelta(minutes=30),
|
||||
)
|
||||
|
||||
@@ -10,8 +10,8 @@ from __future__ import annotations
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from airflow.models.dag import DAG
|
||||
from airflow.operators.bash import BashOperator
|
||||
from airflow.providers.standard.operators.bash import BashOperator
|
||||
from airflow.sdk import DAG
|
||||
|
||||
MODEL_PATH = "/opt/ml/state/models/lightgbm-consumption.txt"
|
||||
|
||||
|
||||
@@ -11,8 +11,8 @@ from __future__ import annotations
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
from airflow.models.dag import DAG
|
||||
from airflow.operators.bash import BashOperator
|
||||
from airflow.providers.standard.operators.bash import BashOperator
|
||||
from airflow.sdk import DAG
|
||||
|
||||
MODEL_PATH = "/opt/ml/state/models/lightgbm-consumption.txt"
|
||||
MLFLOW_TRACKING_URI = "sqlite:////opt/ml/state/mlflow.db"
|
||||
|
||||
@@ -4,7 +4,7 @@ version = "0.1.0"
|
||||
description = "DAGs d'orchestration EnerVision (Airflow)"
|
||||
requires-python = ">=3.12,<3.13"
|
||||
dependencies = [
|
||||
"apache-airflow==2.10.4",
|
||||
"apache-airflow==3.3.2",
|
||||
]
|
||||
|
||||
[dependency-groups]
|
||||
|
||||
@@ -5,8 +5,8 @@ from datetime import timedelta
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
from airflow.models.baseoperator import BaseOperator
|
||||
from airflow.models.dagbag import DagBag
|
||||
from airflow.dag_processing.dagbag import DagBag
|
||||
from airflow.sdk import BaseOperator
|
||||
|
||||
DAGS_FOLDER = Path(__file__).resolve().parent.parent / "dags"
|
||||
|
||||
@@ -22,7 +22,7 @@ TACHES = [
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def dagbag() -> DagBag:
|
||||
return DagBag(dag_folder=str(DAGS_FOLDER), include_examples=False)
|
||||
return DagBag(dag_folder=str(DAGS_FOLDER))
|
||||
|
||||
|
||||
def test_dags_folder_has_no_import_error(dagbag: DagBag) -> None:
|
||||
@@ -34,22 +34,22 @@ def test_every_expected_dag_is_discovered(dagbag: DagBag) -> None:
|
||||
|
||||
|
||||
def test_ml_train_has_no_schedule(dagbag: DagBag) -> None:
|
||||
assert dagbag.dags["ml_train"].timetable.summary == "None"
|
||||
assert dagbag.dags["ml_train"].schedule is None
|
||||
|
||||
|
||||
def test_ml_score_runs_every_hour(dagbag: DagBag) -> None:
|
||||
# `@hourly` est un alias Airflow pour ce cron, c'est sous cette forme que `.summary` le rend.
|
||||
assert dagbag.dags["ml_score"].timetable.summary == "0 * * * *"
|
||||
# `@hourly` est un alias Airflow pour ce cron, c'est sous cette forme que la timetable le rend.
|
||||
assert dagbag.dags["ml_score"].timetable.expression == "0 * * * *"
|
||||
|
||||
|
||||
def test_alertes_runs_after_the_hourly_scoring(dagbag: DagBag) -> None:
|
||||
# Le decalage n'est pas cosmetique : la regle `anomaly` compare une lecture a la `prediction`
|
||||
# du meme instant, que `ml_score` ecrit a l'heure pile.
|
||||
assert dagbag.dags["alertes"].timetable.summary == "15 * * * *"
|
||||
assert dagbag.dags["alertes"].timetable.expression == "15 * * * *"
|
||||
|
||||
|
||||
def test_historical_import_has_no_schedule(dagbag: DagBag) -> None:
|
||||
assert dagbag.dags["historical_import"].timetable.summary == "None"
|
||||
assert dagbag.dags["historical_import"].schedule is None
|
||||
|
||||
|
||||
def test_ml_train_task_calls_the_training_module(dagbag: DagBag) -> None:
|
||||
|
||||
Generated
+554
-653
File diff suppressed because it is too large
Load Diff
@@ -9,7 +9,7 @@ Terminaison TLS et routage de la stack déployée. Seul composant publié sur le
|
||||
- `tls/` : les deux fichiers que nginx lit, `fullchain.pem` et `privkey.pem`. Ignorés par git.
|
||||
- `acme-deploy-hook.sh` : recopie le résultat de certbot dans `tls/`.
|
||||
|
||||
Pas de `Dockerfile` : l'image officielle `nginx:1.28-alpine` est utilisée telle quelle et la
|
||||
Pas de `Dockerfile` : l'image officielle `nginx:1.31-alpine` est utilisée telle quelle et la
|
||||
configuration est montée en volume par `docker-compose.prod.yml`.
|
||||
|
||||
L'overlay emploie les marqueurs `!override` et `!reset`, qui demandent **Docker Compose 2.24.4
|
||||
@@ -88,7 +88,7 @@ docker run --rm \
|
||||
-v "$PWD/infra/proxy/nginx.conf:/etc/nginx/nginx.conf:ro" \
|
||||
-v "$PWD/infra/proxy/conf.d:/etc/nginx/conf.d:ro" \
|
||||
-v "$PWD/infra/proxy/tls:/etc/nginx/tls:ro" \
|
||||
nginx:1.28-alpine nginx -t
|
||||
nginx:1.31-alpine nginx -t
|
||||
```
|
||||
|
||||
Monter `infra/proxy/` entier sur `/etc/nginx` échouerait : `mime.types` vient de l'image.
|
||||
|
||||
@@ -47,13 +47,15 @@ preparer() {
|
||||
fi
|
||||
|
||||
if [[ ! -f "$dossier/.env" ]]; then
|
||||
local brouillon="$dossier/.env.brouillon" oubliees
|
||||
sed -e "s|^POSTGRES_PASSWORD=.*|POSTGRES_PASSWORD=$(secret)|" \
|
||||
-e "s|^POSTGRES_PORT=.*|POSTGRES_PORT=$port_pg|" \
|
||||
-e "s|^APP_SECRET_KEY=.*|APP_SECRET_KEY=$(secret)|" \
|
||||
-e "s|^MAILPIT_UI_PORT=.*|MAILPIT_UI_PORT=$port_mailpit|" \
|
||||
-e "s|^AIRFLOW_PORT=.*|AIRFLOW_PORT=$port_airflow|" \
|
||||
-e "s|^AIRFLOW_FERNET_KEY=.*|AIRFLOW_FERNET_KEY=$(fernet)|" \
|
||||
-e "s|^AIRFLOW_WEBSERVER_SECRET_KEY=.*|AIRFLOW_WEBSERVER_SECRET_KEY=$(secret)|" \
|
||||
-e "s|^AIRFLOW_API_SECRET_KEY=.*|AIRFLOW_API_SECRET_KEY=$(secret)|" \
|
||||
-e "s|^AIRFLOW_JWT_SECRET=.*|AIRFLOW_JWT_SECRET=$(secret)|" \
|
||||
-e "s|^AIRFLOW_ADMIN_PASSWORD=.*|AIRFLOW_ADMIN_PASSWORD=$(secret | cut -c1-20)|" \
|
||||
-e "s|^AIRFLOW_APP_SECRET_KEY=.*|AIRFLOW_APP_SECRET_KEY=$(secret)|" \
|
||||
-e "s|^PUBLIC_HOST=.*|PUBLIC_HOST=$hote|" \
|
||||
@@ -61,13 +63,21 @@ preparer() {
|
||||
-e "s|^COMPOSE_PROJECT_NAME=.*|COMPOSE_PROJECT_NAME=enervision-$env|" \
|
||||
-e "s|^PROXY_HTTP_PORT=.*|PROXY_HTTP_PORT=$port_http|" \
|
||||
-e "s|^PROXY_HTTPS_PORT=.*|PROXY_HTTPS_PORT=$port_https|" \
|
||||
"$dossier/.env.example" > "$dossier/.env"
|
||||
"$dossier/.env.example" > "$brouillon"
|
||||
# Branche antérieure à l'ADR 0009 : ces clés manquent alors dans .env.example.
|
||||
for cle in "COMPOSE_PROJECT_NAME=enervision-$env" "PUBLIC_ORIGIN=$origine" \
|
||||
"PROXY_HTTP_PORT=$port_http" "PROXY_HTTPS_PORT=$port_https"; do
|
||||
grep -q "^${cle%%=*}=" "$dossier/.env" || echo "$cle" >> "$dossier/.env"
|
||||
grep -q "^${cle%%=*}=" "$brouillon" || echo "$cle" >> "$brouillon"
|
||||
done
|
||||
chmod 600 "$dossier/.env"
|
||||
# Piège : une clé renommée en amont garde sa valeur d'exemple, que le `:?` du compose ne
|
||||
# voit pas puisqu'elle n'est pas vide. Cas vécu : AIRFLOW_WEBSERVER_SECRET_KEY, Airflow 3.
|
||||
oubliees="$(grep '=change_me$' "$brouillon" | grep -v '^APP_MOCK_API_' | cut -d= -f1 | tr '\n' ' ' || true)"
|
||||
if [[ -n "$oubliees" ]]; then
|
||||
rm -f "$brouillon"
|
||||
erreur "$env : secrets non générés, .env non écrit : $oubliees"
|
||||
fi
|
||||
chmod 600 "$brouillon"
|
||||
mv "$brouillon" "$dossier/.env"
|
||||
echo "$env : .env généré. Reste à renseigner APP_MOCK_API_USERNAME et APP_MOCK_API_PASSWORD."
|
||||
fi
|
||||
|
||||
|
||||
Reference in New Issue
Block a user