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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
48 lines
1.3 KiB
Docker
48 lines
1.3 KiB
Docker
# Dockerfile for Celery Replacement Example
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#
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# This demonstrates running a production-ready application with
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# Gunicorn dirty arbiters replacing Celery for background tasks.
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#
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# Key difference from Celery deployment:
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# - Celery: Needs separate web + worker containers + Redis/RabbitMQ
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# - Dirty: Single container handles both HTTP and background tasks
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FROM python:3.12-slim
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# Set working directory
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WORKDIR /app
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# Install system dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# Copy gunicorn source and install (from build context root)
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COPY . /gunicorn-src
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RUN pip install --no-cache-dir /gunicorn-src
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# Copy example application
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COPY examples/celery_alternative /app
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RUN pip install --no-cache-dir flask
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# Environment variables
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ENV PYTHONUNBUFFERED=1
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV PYTHONPATH=/gunicorn-src
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ENV GUNICORN_BIND=0.0.0.0:8000
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ENV GUNICORN_WORKERS=4
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ENV GUNICORN_THREADS=4
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ENV DIRTY_WORKERS=9
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ENV DIRTY_TIMEOUT=300
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ENV LOG_LEVEL=info
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# Expose port
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EXPOSE 8000
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# Health check
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD curl -f http://localhost:8000/health || exit 1
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# Run gunicorn with dirty arbiters
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CMD ["gunicorn", "-c", "gunicorn_conf.py", "app:app"]
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