celery

============================================
celery - Distributed Task Queue for Django.
============================================

:Version: 0.2.10

Introduction
============

``celery`` is a distributed task queue framework for Django.

It is used for executing tasks *asynchronously*, routed to one or more
worker servers, running concurrently using multiprocessing.

It is designed to solve certain problems related to running websites
demanding high-availability and performance.

It is perfect for filling caches, posting updates to twitter, mass
downloading data like syndication feeds or web scraping. Use-cases are
plentiful. Implementing these features asynchronously using ``celery`` is
easy and fun, and the performance improvements can make it more than
worthwhile.

Features
========

* Uses AMQP messaging (RabbitMQ, ZeroMQ) to route tasks to the
worker servers.

* You can run as many worker servers as you want, and still
be *guaranteed that the task is only executed once.*

* Tasks are executed *concurrently* using the Python 2.6
``multiprocessing`` module (also available as a back-port
to older python versions)

* Supports *periodic tasks*, which makes it a (better) replacement
for cronjobs.

* When a task has been executed, the return value is stored using either
a MySQL/Oracle/PostgreSQL/SQLite database, memcached,
or Tokyo Tyrant back-end.

* If the task raises an exception, the exception instance is stored,
instead of the return value.

* All tasks has a Universally Unique Identifier (UUID), which is the
task id, used for querying task status and return values.

* Supports *task-sets*, which is a task consisting of several sub-tasks.
You can find out how many, or if all of the sub-tasks has been executed.
Excellent for progress-bar like functionality.

* Has a ``map`` like function that uses tasks, called ``dmap``.

* However, you rarely want to wait for these results in a web-environment.
You'd rather want to use Ajax to poll the task status, which is
available from a URL like ``celery//status/``. This view
returns a JSON-serialized data structure containing the task status,
and the return value if completed, or exception on failure.

API Reference Documentation
===========================

The `API Reference Documentation`_ is hosted at Github
(http://ask.github.com/celery)

.. _`API Reference Docmentation`: http://ask.github.com/celery/

Installation
=============

You can install ``celery`` either via the Python Package Index (PyPI)
or from source.

To install using ``pip``,::

$ pip install celery

To install using ``easy_install``,::

$ easy_install celery

If you have downloaded a source tarball you can install it
by doing the following,::

$ python setup.py build
# python setup.py install # as root

Usage
=====

Have to write a cool tutorial, but here is some simple usage info.

*Note* You need to have a AMQP message broker running, like `RabbitMQ`_,
and you need to have the amqp server setup in your settings file, as described
in the `carrot distribution README`_.

*Note* If you're running ``SQLite`` as the database back-end, ``celeryd`` will
only be able to process one message at a time, this is because ``SQLite``
doesn't allow concurrent writes.

.. _`RabbitMQ`: http://www.rabbitmq.com
.. _`carrot distribution README`: http://pypi.python.org/pypi/carrot/0.3.3


Defining tasks
--------------

>>> from celery.task import tasks
>>> from celery.log import setup_logger
>>> def do_something(some_arg, **kwargs):
... logger = setup_logger(**kwargs)
... logger.info("Did something: %s" % some_arg)
... return 42
>>> tasks.register(do_something, "do_something")

Tell the celery daemon to run a task
-------------------------------------

>>> from celery.task import delay_task
>>> delay_task("do_something", some_arg="foo bar baz")


Execute a task, and get its return value.
-----------------------------------------

>>> from celery.task import delay_task
>>> result = delay_task("do_something", some_arg="foo bar baz")
>>> result.ready()
False
>>> result.get() # Waits until the task is done.
42
>>> result.status()
'DONE'

If the task raises an exception, the tasks status will be ``FAILURE``, and
``result.result`` will contain the exception instance raised.

Running the celery daemon
--------------------------

::

$ cd mydjangoproject
$ python manage.py celeryd
[....]
[2009-04-23 17:44:05,115: INFO/Process-1] Did something: foo bar baz
[2009-04-23 17:44:05,118: INFO/MainProcess] Waiting for queue.

Launching celeryd in the background as a daemon
------------------------------------------------

::

$ cd mydjangoproject
$ python manage.py celeryd --daemon

Getting help for the available options to celeryd
-------------------------------------------------

::

$ cd mydjangoproject
$ python manage.py help celeryd



Auto-discovery of tasks
-----------------------

``celery`` has an auto-discovery feature like the Django Admin, that
automatically loads any ``tasks.py`` module in the applications listed
in ``settings.INSTALLED_APPS``.

A good place to add this command could be in your ``urls.py``,
::

from celery.task import tasks
tasks.autodiscover()


Then you can add new tasks in your applications ``tasks.py`` module,
::

from celery.task import tasks
from celery.log import setup_logger
from clickcounter.models import ClickCount

def increment_click(for_url, **kwargs):
logger = setup_logger(**kwargs)
clicks_for_url, cr = ClickCount.objects.get_or_create(url=for_url)
clicks_for_url.clicks = clicks_for_url.clicks + 1
clicks_for_url.save()
logger.info("Incremented click count for %s (not at %d)" % (
for_url, clicks_for_url.clicks)
tasks.register(increment_click, "increment_click")


Periodic Tasks
---------------

Periodic tasks are tasks that are run every ``n`` seconds. They don't
support extra arguments. Here's an example of a periodic task:


>>> from celery.task import tasks, PeriodicTask
>>> from datetime import timedelta
>>> class MyPeriodicTask(PeriodicTask):
... name = "foo.my-periodic-task"
... run_every = timedelta(seconds=30)
...
... def run(self, **kwargs):
... logger = self.get_logger(**kwargs)
... logger.info("Running periodic task!")
...
>>> tasks.register(MyPeriodicTask)


For periodic tasks to work you need to add ``celery`` to ``INSTALLED_APPS``,
and issue a ``syncdb``.

License
=======

This software is licensed under the ``New BSD License``. See the ``LICENSE``
file in the top distribution directory for the full license text.

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