How to use Django with Celery?

Django is a popular Python framework known for its “batteries-included” philosophy. Celery is a powerful, production-ready asynchronous job queue, which allows you to run time-consuming Python functions in the background.

When using Django with Celery, you’ll need to add some settings to your Django project and then you can call Celery tasks from your Django code. Note that Celery does require a message transport to send messages from your application to workers. One commonly used message transport is RabbitMQ.

Here are steps on how to use Django with Celery:

1. Install RabbitMQ and Celery

You can install RabbitMQ via their official website and install Celery via `pip install celery`.

1. Create a Celery.py file in your Django project

This file will contain the settings for Celery. Example:

```

your_project/celery.py
from future import absolute_import, unicode_literals
import os
from celery import Celery

set the default Django settings module for the ‘celery’ program.
os.environ.setdefault(‘DJANGO_SETTINGS_MODULE’, ‘your_project.settings’)
app = Celery(‘your_project’)
app.config_from_object(‘django.conf:settings’, namespace=‘CELERY’)
Load task modules from all registered Django app configs.
app.autodiscover_tasks()
```

1. Update your settings.py file

Add below lines to your Django settings.py file:

```

your_project/settings.py
CELERY_BROKER_URL = ‘pyamqp://guest@localhost//’
```

1. Create tasks

You can now create tasks in your Django app by creating a tasks.py file. In this file, you can define some time-consuming tasks that Celery will execute in the background.

```

your_app/tasks.py
from future import absolute_import, unicode_literals
from celery import shared_task

@shared_task
def some_time_consuming_task(): do_something() return None
```

1. Call tasks

Now that you have tasks defined, you can call them from your Django views or models like this:

```

your_app/views.py
from django.http import HttpResponse
from .tasks import some_time_consuming_task

def some_view(request): result = some_time_consuming_task.delay() return HttpResponse(‘Task has been called’)
```

1. Run Workers

In your terminal, run both your Django server (`python manage.py runserver`) and the Celery worker (`celery -A your_project worker —loglevel=info`).

In this example setup, you utilize `RabbitMQ` as a message broker (specified in `CELERY_BROKER_URL`), and a worker listens for tasks and executes them asynchronously.

You can find comprehensive information on how to use Django with Celery in the official Celery documentation (https://docs.celeryproject.org/en/stable/django/first-steps-with-django.html).

It should be noted that managing asynchronous jobs may get complex depending on your use case. However, if used correctly, Celery is an extremely powerful tool that can help make your Django applications much more efficient.