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17ac6a5254
Demonstrates replacing Celery with Gunicorn's dirty arbiters for background task processing. Includes: - 4 task workers: Email, Image, Data, Scheduled - Stateful workers with persistent connections/caches - Streaming progress for long-running tasks - Per-app worker allocation - Flask API with 15+ endpoints - Docker deployment (single container vs Celery's 4+) - Unit tests (19 tests) and integration tests - Migration guide from Celery
80 lines
1.7 KiB
YAML
80 lines
1.7 KiB
YAML
# Docker Compose for Celery Replacement Example
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#
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# Notice: Only ONE service needed!
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# Compare with typical Celery deployment which requires:
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# - web (gunicorn/uvicorn)
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# - celery_worker
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# - celery_beat (for scheduled tasks)
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# - redis or rabbitmq
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#
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# With dirty arbiters, everything runs in a single container.
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services:
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app:
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build:
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context: ../.. # Gunicorn repo root
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dockerfile: examples/celery_alternative/Dockerfile
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ports:
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- "8000:8000"
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environment:
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- GUNICORN_WORKERS=4
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- GUNICORN_THREADS=4
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- DIRTY_WORKERS=9
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- DIRTY_TIMEOUT=300
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- LOG_LEVEL=info
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 10s
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# Resource limits (optional)
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deploy:
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resources:
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limits:
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memory: 1G
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reservations:
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memory: 256M
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# Test runner service
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tests:
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build:
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context: ../..
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dockerfile: examples/celery_alternative/Dockerfile
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depends_on:
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app:
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condition: service_healthy
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environment:
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- APP_URL=http://app:8000
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command: ["python", "-m", "pytest", "tests/", "-v", "--tb=short"]
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profiles:
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- test
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# For comparison, here's what a Celery deployment would look like:
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#
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# services:
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# web:
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# build: .
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# command: gunicorn app:app -b 0.0.0.0:8000
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# ports:
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# - "8000:8000"
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# depends_on:
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# - redis
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#
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# celery_worker:
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# build: .
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# command: celery -A tasks worker -l info
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# depends_on:
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# - redis
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#
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# celery_beat:
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# build: .
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# command: celery -A tasks beat -l info
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# depends_on:
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# - redis
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#
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# redis:
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# image: redis:alpine
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# ports:
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# - "6379:6379"
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