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

• Python >= 3.6.x
  • pipenv (pip install pipenv)
• Docker
  • docker-compose

Running

Install project dependencies

Execute the following command:

pipenv --python <your_python_version>
pipenv install --dev

Run example

1. Run command docker-compose upto start up the RabbitMQ, Redis and flower instances.
2. Start the fastapi web application with pipenv run uvicorn main:app --reload.
3. Start the celery worker with command pipenv run celery worker -A 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).