Simple job queues for Python
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Signed-off-by: Paul Spooren <mail@aparcar.org>
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README.md

RQ (Redis Queue) is a simple Python library for queueing jobs and processing them in the background with workers. It is backed by Redis and it is designed to have a low barrier to entry. It should be integrated in your web stack easily.

RQ requires Redis >= 3.0.0.

Build status PyPI Coverage

Full documentation can be found here.

Support RQ

If you find RQ useful, please consider supporting this project via Tidelift.

Getting started

First, run a Redis server, of course:

$ redis-server

To put jobs on queues, you don't have to do anything special, just define your typically lengthy or blocking function:

import requests

def count_words_at_url(url):
    """Just an example function that's called async."""
    resp = requests.get(url)
    return len(resp.text.split())

You do use the excellent requests package, don't you?

Then, create an RQ queue:

from redis import Redis
from rq import Queue

q = Queue(connection=Redis())

And enqueue the function call:

from my_module import count_words_at_url
job = q.enqueue(count_words_at_url, 'http://nvie.com')

For a more complete example, refer to the docs. But this is the essence.

The worker

To start executing enqueued function calls in the background, start a worker from your project's directory:

$ rq worker
*** Listening for work on default
Got count_words_at_url('http://nvie.com') from default
Job result = 818
*** Listening for work on default

That's about it.

Installation

Simply use the following command to install the latest released version:

pip install rq

If you want the cutting edge version (that may well be broken), use this:

pip install -e git+https://github.com/nvie/rq.git@master#egg=rq

Check out these below repos which might be useful in your rq based project.

Project history

This project has been inspired by the good parts of Celery, Resque and this snippet, and has been created as a lightweight alternative to the heaviness of Celery or other AMQP-based queueing implementations.