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

Overview

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

Run example

  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).

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

  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).
Owner
Grega Vrbančič
Young Researcher at University of Maribor, Faculty of Electrical Engineering and Computer Science
Grega Vrbančič
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