celery - Distributed Task Queue
|Version:||3.0.22 (Chiastic Slide)|
|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 machines.
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 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. So far there's RCelery for the Ruby programming language, and a PHP client, but language interoperability can also be achieved by using webhooks.
What do I need?
Celery version 3.0 runs on,
- Python (2.5, 2.6, 2.7, 3.2, 3.3)
- PyPy (1.8, 1.9)
- Jython (2.5, 2.7).
This is the last version to support Python 2.5, and from Celery 3.1, Python 2.6 or later is required. The last version to support Python 2.4 was Celery series 2.2.
Celery requires a message broker to send and receive messages. The RabbitMQ, Redis and MongoDB broker transports are feature complete, but there's also support for a myriad of other solutions, including using SQLite for local development.
Celery can run on a single machine, on multiple machines, or even across datacenters.
If this is the first time you're trying to use Celery, or you are new to Celery 3.0 coming from previous versions then you should read our getting started tutorials:
Tutorial teaching you the bare minimum needed to get started with Celery.
A more complete overview, showing more features.
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 celery = Celery('hello', broker='amqp://guest@localhost//') @celery.task def hello(): return 'hello world'
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.
A single Celery process can process millions of tasks a minute, with sub-millisecond round-trip latency (using RabbitMQ, py-librabbitmq, and optimized settings).
Almost every part of Celery can be extended or used on its own, Custom pool implementations, serializers, compression schemes, logging, schedulers, consumers, producers, autoscalers, broker transports and much more.
- AMQP, Redis
- memcached, MongoDB
- SQLAlchemy, Django ORM
- Apache Cassandra
- pickle, json, yaml, msgpack.
- zlib, bzip2 compression.
- Cryptographic message signing.
Celery is easy to integrate with web frameworks, some of which even have integration packages:
Django django-celery 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
The latest documentation with user guides, tutorials and API reference is hosted at Read The Docs.
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
Celery also defines a group of bundles that can be used to install Celery and the dependencies for a given feature.
The following bundles are available:
|celery-with-redis:||for using Redis as a broker.|
|celery-with-mongodb:||for using MongoDB as a broker.|
|django-celery-with-redis:||for Django, and using Redis as a broker.|
|django-celery-with-mongodb:||for Django, and using MongoDB as a broker.|
Downloading and installing from source
Download the latest version of Celery from http://pypi.python.org/pypi/celery/
You can install it by doing the following,:
$ tar xvfz celery-0.0.0.tar.gz $ cd celery-0.0.0 $ python setup.py build # python setup.py install
The last command must be executed as a privileged user if you are not currently using a virtualenv.
Using the development version
You can clone the repository by doing the following:
$ git clone https://github.com/celery/celery $ cd celery $ python setup.py develop
The development version will usually also depend on the development version of kombu, the messaging framework Celery uses to send and receive messages, so you should also install that from git:
$ git clone https://github.com/celery/kombu $ cd kombu $ python setup.py develop
For discussions about the usage, development, and future of celery, please join the celery-users mailing list.
Come chat with us on IRC. The #celery channel is located at the Freenode network.
If you have any suggestions, bug reports or annoyances please report them to our issue tracker at http://github.com/celery/celery/issues/
Development of celery happens at Github: http://github.com/celery/celery
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 documentation.
This software is licensed under the New BSD License. See the
file in the top distribution directory for the full license text.