Skip to main content

Distributed Task Queue.

Project description

http://docs.celeryproject.org/en/latest/_images/celery-banner-small.png

Build status coverage BSD License Celery can be installed via wheel Supported Python versions. Support Python implementations. Backers on Open Collective Sponsors on Open Collective

Version:

4.2.0rc4 (latentcall)

Web:

http://celeryproject.org/

Download:

https://pypi-hypernode.com/project/celery/

Source:

https://github.com/celery/celery/

Keywords:

task, queue, job, async, rabbitmq, amqp, redis, python, distributed, actors

What’s 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, 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 in such a way that the client enqueues an URL to be requested by a worker.

What do I need?

Celery version 4.1 runs on,

  • Python (2.7, 3.4, 3.5, 3.6)

  • PyPy (5.8)

This is the last version to support Python 2.7, and from the next version (Celery 5.x) Python 3.5 or newer is required.

If you’re 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 don’t support Microsoft Windows. Please don’t open any issues related to that platform.

Celery is usually used with a message broker to send and receive messages. The RabbitMQ, Redis transports are feature complete, but there’s also experimental 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.

Get Started

If this is the first time you’re trying to use Celery, or you’re new to Celery 4.1 coming from previous versions then you should read our getting started tutorials:

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, like at our mailing-list, or the IRC channel.

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

    from celery import Celery
    
    app = Celery('hello', broker='amqp://guest@localhost//')
    
    @app.task
    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 Primary/Primary or Primary/Replica 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

  • Concurrency

  • Result Stores

    • AMQP, Redis

    • memcached

    • SQLAlchemy, Django ORM

    • Apache Cassandra, IronCache, Elasticsearch

  • Serialization

    • pickle, json, yaml, msgpack.

    • zlib, bzip2 compression.

    • Cryptographic message signing.

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 aren’t strictly necessary, but they can make development easier, and sometimes they add important hooks like closing database connections at fork.

Documentation

The latest documentation is hosted at Read The Docs, containing user guides, tutorials, and an API reference.

Installation

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

To install using pip:

$ pip 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,redis,auth,msgpack]"

The following bundles are available:

Serializers

celery[auth]:

for using the auth security serializer.

celery[msgpack]:

for using the msgpack serializer.

celery[yaml]:

for using the yaml serializer.

Concurrency

celery[eventlet]:

for using the eventlet pool.

celery[gevent]:

for using the gevent pool.

Transports and Backends

celery[librabbitmq]:

for using the librabbitmq C library.

celery[redis]:

for using Redis as a message transport or as a result backend.

celery[sqs]:

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

celery[tblib]:

for using the task_remote_tracebacks feature.

celery[memcache]:

for using Memcached as a result backend (using pylibmc)

celery[pymemcache]:

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

celery[cassandra]:

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

celery[couchbase]:

for using Couchbase as a result backend.

celery[elasticsearch]:

for using Elasticsearch as a result backend.

celery[riak]:

for using Riak as a result backend.

celery[zookeeper]:

for using Zookeeper as a message transport.

celery[sqlalchemy]:

for using SQLAlchemy as a result backend (supported).

celery[pyro]:

for using the Pyro4 message transport (experimental).

celery[slmq]:

for using the SoftLayer Message Queue transport (experimental).

celery[consul]:

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

celery[django]:

specifies the lowest version possible for Django support.

You should probably not use this in your requirements, it’s here for informational purposes only.

Downloading and installing from source

Download the latest version of Celery from PyPI:

https://pypi-hypernode.com/project/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 aren’t currently using a virtualenv.

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 https://github.com/celery/celery/zipball/master#egg=celery
$ pip install https://github.com/celery/billiard/zipball/master#egg=billiard
$ pip install https://github.com/celery/py-amqp/zipball/master#egg=amqp
$ pip install https://github.com/celery/kombu/zipball/master#egg=kombu
$ pip install https://github.com/celery/vine/zipball/master#egg=vine

With git

Please see the Contributing section.

Getting Help

Mailing list

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

IRC

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

Bug tracker

If you have any suggestions, bug reports, or annoyances please report them to our issue tracker at https://github.com/celery/celery/issues/

Wiki

https://wiki.github.com/celery/celery/

Credits

Contributors

This project exists thanks to all the people who contribute. Development of celery happens at GitHub: https://github.com/celery/celery

You’re 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.

oc-contributors

Backers

Thank you to all our backers! 🙏 [Become a backer]

oc-backers

Sponsors

Support this project by becoming a sponsor. Your logo will show up here with a link to your website. [Become a sponsor]

oc-sponsors

License

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

celery-4.2.0rc4.tar.gz (1.4 MB view details)

Uploaded Source

Built Distribution

celery-4.2.0rc4-py2.py3-none-any.whl (401.0 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file celery-4.2.0rc4.tar.gz.

File metadata

  • Download URL: celery-4.2.0rc4.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for celery-4.2.0rc4.tar.gz
Algorithm Hash digest
SHA256 68291fb53ec47600fb7c0ec5def6d631fd0f0a0f37fb2c4a050e56e5794cc9e5
MD5 1e0dc70edc40ff7bff6f8f7c6cd3fbbc
BLAKE2b-256 b5f7f862b92e6fc7c3628712d69d8f5d41173db5bda27f0504b17444a79b98bc

See more details on using hashes here.

Provenance

File details

Details for the file celery-4.2.0rc4-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for celery-4.2.0rc4-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 22dc3b5a43f6d2ca127d976009357684a6e0671577987193695222936ac0a6dd
MD5 022728f7f9fb35e829e55fa06469b343
BLAKE2b-256 e33b411ae267bbb10a1ea8d7ab79ec6be0f2530a4a9ae977e35afa5879c76d89

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page