After you’ve integrated Celery and refactored your Django code, sending feedback in your app is such a great experience that you don’t want to stop sending positive feedback messages!

Handling long-running or compute-expensive tasks asynchronously in the background with Celery, instead of bogging down your web app with tasks that it wasn’t intended to handle, can breathe fresh air into a slow-running application.

Celery aims to provide a quick interface for sending messages to its distributed task queue. In this example, you experienced how little you might need to change to use Celery in your Django app.

In this video course, you learned how to:

Recognize effective use cases for Celery
Differentiate between Celery beat and Celery workers
Integrate Celery and Redis in a Django project
Set up asynchronous tasks that run independently of your Django app
Refactor Django code to run a task with Celery instead

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00:00 Summary, well done. You’ve made it to the end of the course. Now you’ve integrated Celery and refactored your Django code. Sending feedback in your app is smooth and quick, handling long-running, or compute-intensive tasks asynchronously in the background with Celery.

00:16 Instead of bogging down the web app with them, can breathe fresh air into a slow-running application.

00:22 Celery aims to provide a quick interface for sending messages to its distributed task queue. Here you experienced how little you might need to change to use Celery in your Django app.

00:33 In this course, you learned how to recognize effective use cases for Celery, differentiate between Celery Beat and Celery workers. Integrate Celery and Redis into a Django project.

00:46 Set up asynchronous tasks that run independently of your Django app and refactor Django code to run a task with Celery instead.

00:56 In the future, you can keep identifying any task that Django doesn’t need to handle and offload them to your favorite distributed task queue. Instead, with Celery as your ally, you can start integrating more features into your web app, let a distributed task queue.

01:10 Run these tasks asynchronously in the background.

01:13 We hope you found this course useful, and we’ll see you again soon at realpython.com.

danilolimadutra on March 24, 2024

For anyone who want to run this project in docker, follow the files.

Unzip the course sample code.
Rename, rename the Django root folder for app.
Create Dockerfile.
Create docker-compose.yaml.
Create requirements.txt in the app folder.
Craete the image and the containers

# docker compose commands
$ docker compose build
$ docker compose up

Dockerfile

FROM python:3.11-slim
COPY app /app
WORKDIR /app

ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1

RUN pip install -r requirements.txt
RUN python manage.py migrate

docker-compose.yaml

version: '3.8'
services:
  django:
    build: .
    container_name: django
    command: python manage.py runserver 0.0.0.0:8000
    ports:
      - 8000:8000
    volumes:
      - ./app:/app
    environment:
      - DEBUG=1
      - DJANGO_ALLOWED_HOSTS=localhost 127.0.0.1
      - CELERY_BROKER=redis://redis:6379/0
      - CELERY_BACKEND=redis://redis:6379/0
    depends_on:
      - redis
  redis:
    image: "redis:alpine"
    ports:
      - 6379:6379
  celery:
    build: .
    command: celery -A django_celery worker -l INFO
    volumes:
      - ./app:/app
    depends_on:
      - django
      - redis

requirements.txt

celery==5.3.6
Django==5.0.1
redis==5.0.1

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Creating Asynchronous Tasks With Celery and Django (Summary)