Awesome
FastAPI with Celery
Minimal example utilizing FastAPI and Celery with RabbitMQ for task queue, Redis for Celery backend and flower for monitoring the Celery tasks.
Requirements
- Docker
Run example
- Run command
docker-compose up
to start up the RabbitMQ, Redis, flower and our application/worker instances. - Navigate to the http://localhost:8000/docs and execute test API call. You can monitor the execution of the celery tasks in the console logs or navigate to the flower monitoring app at http://localhost:5555 (username: user, password: test).
Run application/worker without Docker?
Requirements/dependencies
- Python >= 3.7
- RabbitMQ instance
- Redis instance
The RabbitMQ, Redis and flower services can be started with
docker-compose -f docker-compose-services.yml up
Install dependencies
Execute the following command: poetry install --dev
Run FastAPI app and Celery worker app
- Start the FastAPI web application with
poetry run hypercorn app/main:app --reload
. - Start the celery worker with command
poetry run celery worker -A app.worker.celery_worker -l info -Q test-queue -c 1
- Navigate to the http://localhost:8000/docs and execute test API call. You can monitor the execution of the celery tasks in the console logs or navigate to the flower monitoring app at http://localhost:5555 (username: user, password: test).