.. _django-first-steps: ========================= First steps with Django ========================= Using Celery with Django ======================== .. note:: 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 :ref:`first-steps` tutorial first and come back to this tutorial. When you have a working example you can continue to the :ref:`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/__init__.py - proj/settings.py - proj/urls.py - manage.py then the recommended way is to create a new `proj/proj/celery.py` module that defines the Celery instance: :file: `proj/proj/celery.py` .. literalinclude:: ../../examples/django/proj/celery.py Then you need to import this app in your :file:`proj/proj/__init__.py` module. This ensures that the app is loaded when Django starts so that the ``@shared_task`` decorator (mentioned later) will use it: :file:`proj/proj/__init__.py`: .. literalinclude:: ../../examples/django/proj/__init__.py 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 :ref:`tut-celery` tutorial. Let's break down what happens in the first module, first we import absolute imports from the future, so that our ``celery.py`` module will not clash with the library: .. code-block:: python from __future__ import absolute_import Then we set the default :envvar:`DJANGO_SETTINGS_MODULE` for the :program:`celery` command-line program: .. code-block:: python 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: .. code-block:: python 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: .. code-block:: python app.config_from_object('django.conf:settings') Next, a common practice for reusable apps is to define all tasks in a separate ``tasks.py`` module, and Celery does have a way to autodiscover these modules: .. code-block:: python app.autodiscover_tasks(lambda: settings.INSTALLED_APPS) With the line above Celery will automatically discover tasks in reusable apps if you follow the ``tasks.py`` convention:: - app1/ - app1/tasks.py - app1/models.py - app2/ - app2/tasks.py - app2/models.py This way you do not have to manually add the individual modules to the :setting:`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: :file:`demoapp/tasks.py`: .. literalinclude:: ../../examples/django/demoapp/tasks.py .. seealso:: You can find the full source code for the Django example project at: https://github.com/celery/celery/tree/3.1/examples/django/ 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: .. code-block:: bash $ 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: .. code-block:: bash $ python manage.py migrate djcelery For those who are not using south, a normal ``syncdb`` will work: .. code-block:: bash $ python manage.py syncdb 4. Configure celery to use the django-celery backend. For the database backend you must use: .. code-block:: python app.conf.update( CELERY_RESULT_BACKEND='djcelery.backends.database:DatabaseBackend', ) For the cache backend you can use: .. code-block:: python app.conf.update( CELERY_RESULT_BACKEND='djcelery.backends.cache:CacheBackend', ) 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) .. _south: http://pypi.python.org/pypi/South/ .. admonition:: Relative Imports You have to be consistent in how you import the task module, e.g. if you have ``project.app`` in ``INSTALLED_APPS`` then you also need to import the tasks ``from project.app`` or else the names of the tasks will be different. See :ref:`task-naming-relative-imports` Starting the worker process =========================== In a production environment you will want to run the worker in the background as a daemon - see :ref:`daemonizing` - 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: .. code-block:: bash $ celery -A proj worker -l info For a complete listing of the command-line options available, use the help command: .. code-block:: bash $ celery help Where to go from here ===================== If you want to learn more you should continue to the :ref:`Next Steps ` tutorial, and after that you can study the :ref:`User Guide `.