Minimal example utilizing FastAPI and Celery with RabbitMQ for task queue, Redis for Celery backend and flower for monitoring the Celery tasks.

• Docker
  • docker-compose

1. Run command docker-compose upto start up the RabbitMQ, Redis, flower and our application/worker instances.
2. 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).

• Python >= 3.7
  • poetry
• RabbitMQ instance
• Redis instance

The RabbitMQ, Redis and flower services can be started with docker-compose -f docker-compose-services.yml up

Execute the following command: poetry install --dev

1. Start the FastAPI web application with poetry run hypercorn app/main:app --reload.
2. Start the celery worker with command poetry run celery worker -A app.worker.celery_worker -l info -Q test-queue -c 1
3. 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).