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celery 4.0.0rc3

Distributed Task Queue

Package Documentation

celery - Distributed Task Queue

.. image::

|build-status| |coverage| |bitdeli|

:Version: 4.0.0rc3 (0today8)
:Keywords: task queue, job queue, asynchronous, async, rabbitmq, amqp, redis,
python, webhooks, queue, distributed


What is a Task Queue?

Task queues are used as a mechanism to distribute work across threads or

A task queue's input is a unit of work, called a task, dedicated worker
processes then constantly monitor the queue for new work to perform.

Celery communicates via messages, usually using a broker
to mediate between clients and workers. To initiate a task a client puts a
message on the queue, the broker then delivers the message to a worker.

A Celery system can consist of multiple workers and brokers, giving way
to high availability and horizontal scaling.

Celery is written in Python, but the protocol can be implemented in any
language. In addition to Python there's node-celery_ for Node.js,
and a `PHP client`_.

Language interoperability can also be achieved
by `using webhooks`_.

.. _node-celery:
.. _`PHP client`:
.. _`using webhooks`:

What do I need?

Celery version 4.0 runs on,

- Python (2.7, 3.4, 3.5)
- PyPy (5.1, 2.4)

This is the last version to support Python 2.7,
and from the next version (Celery 5.x) Python 3.6 or newer is required.

If you are running an older version of Python, you need to be running
an older version of Celery:

- Python 2.6: Celery series 3.1 or earlier.
- Python 2.5: Celery series 3.0 or earlier.
- Python 2.4 was Celery series 2.2 or earlier.

Celery is a project with minimal funding,
so we do not support Microsoft Windows.
Please do not open any issues related to that platform.

*Celery* is usually used with a message broker to send and receive messages.
The RabbitMQ transports is feature complete, but there's also Qpid and Amazon
SQS broker support.

*Celery* can run on a single machine, on multiple machines, or even
across datacenters.

Get Started

If this is the first time you're trying to use Celery, or you are
new to Celery 4.0 coming from previous versions then you should read our
getting started tutorials:

- `First steps with Celery`_

Tutorial teaching you the bare minimum needed to get started with Celery.

- `Next steps`_

A more complete overview, showing more features.

.. _`First steps with Celery`:

.. _`Next steps`:

Celery is...

- **Simple**

Celery is easy to use and maintain, and does *not need configuration files*.

It has an active, friendly community you can talk to for support,
including a `mailing-list`_ and and an IRC channel.

Here's one of the simplest applications you can make::

from celery import Celery

app = Celery('hello', broker='amqp://guest@localhost//')

def hello():
return 'hello world'

- **Highly Available**

Workers and clients will automatically retry in the event
of connection loss or failure, and some brokers support
HA in way of *Master/Master* or *Master/Slave* replication.

- **Fast**

A single Celery process can process millions of tasks a minute,
with sub-millisecond round-trip latency (using RabbitMQ,
py-librabbitmq, and optimized settings).

- **Flexible**

Almost every part of *Celery* can be extended or used on its own,
Custom pool implementations, serializers, compression schemes, logging,
schedulers, consumers, producers, broker transports and much more.

It supports...

- **Message Transports**

- RabbitMQ_, Amazon SQS

- **Concurrency**

- Prefork, Eventlet_, gevent_, single threaded (``solo``)

- **Result Stores**

- AMQP, Redis
- memcached
- SQLAlchemy, Django ORM
- Apache Cassandra, IronCache, Elasticsearch

- **Serialization**

- *pickle*, *json*, *yaml*, *msgpack*.
- *zlib*, *bzip2* compression.
- Cryptographic message signing.

.. _`Eventlet`:
.. _`gevent`:

.. _RabbitMQ:
.. _Redis:
.. _SQLAlchemy:

Framework Integration

Celery is easy to integrate with web frameworks, some of which even have
integration packages:

| `Django`_ | not needed |
| `Pyramid`_ | `pyramid_celery`_ |
| `Pylons`_ | `celery-pylons`_ |
| `Flask`_ | not needed |
| `web2py`_ | `web2py-celery`_ |
| `Tornado`_ | `tornado-celery`_ |

The integration packages are not strictly necessary, but they can make
development easier, and sometimes they add important hooks like closing
database connections at ``fork``.

.. _`Django`:
.. _`Pylons`:
.. _`Flask`:
.. _`web2py`:
.. _`Bottle`:
.. _`Pyramid`:
.. _`pyramid_celery`:
.. _`django-celery`:
.. _`celery-pylons`:
.. _`web2py-celery`:
.. _`Tornado`:
.. _`tornado-celery`:

.. _celery-documentation:


The `latest documentation`_ with user guides, tutorials and API reference
is hosted at Read The Docs.

.. _`latest documentation`:

.. _celery-installation:


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

To install using `pip`,:

$ pip install -U Celery

To install using `easy_install`,:

$ easy_install -U Celery

.. _bundles:


Celery also defines a group of bundles that can be used
to install Celery and the dependencies for a given feature.

You can specify these in your requirements or on the ``pip``
command-line by using brackets. Multiple bundles can be specified by
separating them by commas.

$ pip install "celery[librabbitmq]"

$ pip install "celery[librabbitmq,auth,msgpack]"

The following bundles are available:


for using the ``auth`` security serializer.

for using the msgpack serializer.

for using the yaml serializer.


for using the ``eventlet`` pool.

for using the ``gevent`` pool.

Transports and Backends

for using the librabbitmq C library.

for using Amazon SQS as a message transport (*experimental*).

for using the ``task_remote_tracebacks`` feature.

for using Memcached as a result backend (using ``pylibmc``)

for using Memcached as a result backend (pure-Python implementation).

for using Apache Cassandra as a result backend with DataStax driver.

for using Couchbase as a result backend.

for using Elasticsearch as a result backend.

for using Riak as a result backend.

for using Zookeeper as a message transport.

for using SQLAlchemy as a result backend (*supported*).

for using the Pyro4 message transport (*experimental*).

for using the SoftLayer Message Queue transport (*experimental*).

for using the Key/Value store as a message transport or result backend (*experimental*).

.. _celery-installing-from-source:

Downloading and installing from source

Download the latest version of Celery from

You can install it by doing the following,:

$ tar xvfz celery-0.0.0.tar.gz
$ cd celery-0.0.0
$ python build
# python install

The last command must be executed as a privileged user if
you are not currently using a virtualenv.

.. _celery-installing-from-git:

Using the development version

With pip

The Celery development version also requires the development
versions of ``kombu``, ``amqp``, ``billiard`` and ``vine``.

You can install the latest snapshot of these using the following
pip commands:

$ pip install
$ pip install
$ pip install
$ pip install
$ pip install

With git

Please the Contributing section.

.. _getting-help:

Getting Help

.. _mailing-list:

Mailing list

For discussions about the usage, development, and future of celery,
please join the `celery-users`_ mailing list.

.. _`celery-users`:

.. _irc-channel:


Come chat with us on IRC. The **#celery** channel is located at the `Freenode`_

.. _`Freenode`:

.. _bug-tracker:

Bug tracker

If you have any suggestions, bug reports or annoyances please report them
to our issue tracker at

.. _wiki:


.. _contributing-short:


Development of `celery` happens at GitHub:

You are highly encouraged to participate in the development
of `celery`. If you don't like GitHub (for some reason) you're welcome
to send regular patches.

Be sure to also read the `Contributing to Celery`_ section in the

.. _`Contributing to Celery`:

.. _license:


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

.. # vim: syntax=rst expandtab tabstop=4 shiftwidth=4 shiftround

.. |build-status| image::
:alt: Build status

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File Type Py Version Uploaded on Size
celery-4.0.0rc3-py2.py3-none-any.whl (md5, pgp) Python Wheel 2.7 2016-07-08 540KB
celery-4.0.0rc3.tar.gz (md5, pgp) Source 2016-07-08 1MB