This document describes the current stable version of Celery (3.1). For development docs, go here.

First steps with Django

Using Celery with Django


Previous versions of Celery required a separate library to work with Django, but since 3.1 this is no longer the case. Django is supported out of the box now so this document only contains a basic way to integrate Celery and Django. You will use the same API as non-Django users so it’s recommended that you read the First Steps with Celery tutorial first and come back to this tutorial. When you have a working example you can continue to the Next Steps guide.

To use Celery with your Django project you must first define an instance of the Celery library (called an “app”)

If you have a modern Django project layout like:

- proj/
  - proj/
  - proj/
  - proj/

then the recommended way is to create a new proj/proj/ module that defines the Celery instance:

from __future__ import absolute_import

import os

from celery import Celery

from django.conf import settings

# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'proj.settings')

app = Celery('proj')

# Using a string here means the worker will not have to
# pickle the object when using Windows.
app.autodiscover_tasks(lambda: settings.INSTALLED_APPS)

def debug_task(self):
    print('Request: {0!r}'.format(self.request))

Then you need to import this app in your proj/proj/ module. This ensures that the app is loaded when Django starts so that the @shared_task decorator (mentioned later) will use it:


from __future__ import absolute_import

# This will make sure the app is always imported when
# Django starts so that shared_task will use this app.
from .celery import app as celery_app

Note that this example project layout is suitable for larger projects, for simple projects you may use a single contained module that defines both the app and tasks, like in the First Steps with Celery tutorial.

Let’s break down what happens in the first module, first we import absolute imports from the future, so that our module will not clash with the library:

from __future__ import absolute_import

Then we set the default DJANGO_SETTINGS_MODULE for the celery command-line program:

os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'proj.settings')

You don’t need this line, but it saves you from always passing in the settings module to the celery program. It must always come before creating the app instances, which is what we do next:

app = Celery('proj')

This is our instance of the library, you can have many instances but there’s probably no reason for that when using Django.

We also add the Django settings module as a configuration source for Celery. This means that you don’t have to use multiple configuration files, and instead configure Celery directly from the Django settings.

You can pass the object directly here, but using a string is better since then the worker doesn’t have to serialize the object when using Windows or execv:


Next, a common practice for reusable apps is to define all tasks in a separate module, and Celery does have a way to autodiscover these modules:

app.autodiscover_tasks(lambda: settings.INSTALLED_APPS)

With the line above Celery will automatically discover tasks in reusable apps if you follow the convention:

- app1/
    - app1/
    - app1/
- app2/
    - app2/
    - app2/

This way you do not have to manually add the individual modules to the CELERY_IMPORTS setting. The lambda so that the autodiscovery can happen only when needed, and so that importing your module will not evaluate the Django settings object.

Finally, the debug_task example is a task that dumps its own request information. This is using the new bind=True task option introduced in Celery 3.1 to easily refer to the current task instance.

Using the @shared_task decorator

The tasks you write will probably live in reusable apps, and reusable apps cannot depend on the project itself, so you also cannot import your app instance directly.

The @shared_task decorator lets you create tasks without having any concrete app instance:


from __future__ import absolute_import

from celery import shared_task

def add(x, y):
    return x + y

def mul(x, y):
    return x * y

def xsum(numbers):
    return sum(numbers)

See also

You can find the full source code for the Django example project at:

Using the Django ORM/Cache as a result backend.

The django-celery library defines result backends that uses the Django ORM and Django Cache frameworks.

To use this with your project you need to follow these four steps:

  1. Install the django-celery library:

    $ pip install django-celery
  2. Add djcelery to INSTALLED_APPS.

  3. Create the celery database tables.

    This step will create the tables used to store results when using the database result backend and the tables used by the database periodic task scheduler. You can skip this step if you don’t use these.

    If you are using south for schema migrations, you’ll want to:

    $ python migrate djcelery

    For those who are not using south, a normal syncdb will work:

    $ python syncdb
  4. Configure celery to use the django-celery backend.

    For the database backend you must use:


    For the cache backend you can use:


    If you have connected Celery to your Django settings then you can add this directly into your settings module (without the app.conf.update part)

Relative Imports

You have to be consistent in how you import the task module, e.g. if you have in INSTALLED_APPS then you also need to import the tasks from or else the names of the tasks will be different.

See Automatic naming and relative imports

Starting the worker process

In a production environment you will want to run the worker in the background as a daemon - see Running the worker as a daemon - but for testing and development it is useful to be able to start a worker instance by using the celery worker manage command, much as you would use Django’s runserver:

$ celery -A proj worker -l info

For a complete listing of the command-line options available, use the help command:

$ celery help

Where to go from here

If you want to learn more you should continue to the Next Steps tutorial, and after that you can study the User Guide.

Previous topic


Next topic


This Page