FastAPI with Celery, RabbitMQ, and Redis
A minimal example demonstrating how to integrate FastAPI with Celery using RabbitMQ and Redis for asynchronous task processing.
What is FastAPI with Celery, RabbitMQ, and Redis?
FastAPI-Celery is a minimal example project that demonstrates how to integrate FastAPI with Celery to handle asynchronous background tasks. It uses RabbitMQ as a message broker, Redis for storing task results, and Flower for monitoring, providing a complete reference architecture for building scalable web applications with task queues.
Backend developers and engineers building Python web applications with FastAPI who need to offload long-running or resource-intensive tasks to background workers.
It offers a production-ready, easy-to-understand example that eliminates the guesswork of setting up FastAPI with Celery, including Docker configurations for all required services, making it ideal for learning or as a foundation for real projects.
Overview
Minimal example utilizing fastapi and celery with RabbitMQ for task queue, Redis for celery backend and flower for monitoring the celery tasks.
Use Cases
Best For
- Learning how to integrate FastAPI with Celery for asynchronous processing
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