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README.md

WARNING: DON'T USE THIS IN PRODUCTION (yet)

RQ (Redis Queue) is a lightweight* Python library for queueing jobs and processing them in the background with workers. It is backed by Redis and it is extremely simple to use.

* It is under 20 kB in size and under 500 lines of code.

Getting started

First, run a Redis server, of course:

{% highlight console %} $ redis-server {% endhighlight %}

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

{% highlight python %} import urllib2

def count_words_at_url(url): f = urllib2.urlopen(url) count = 0 while True: line = f.readline() if not line: break count += len(line.split()) return count {% endhighlight %}

Then, create a RQ queue:

{% highlight python %} import rq import * use_redis() q = Queue() {% endhighlight %}

And enqueue the function call:

{% highlight python %} from my_module import count_words_at_url result = q.enqueue( count_words_at_url, 'http://nvie.com') {% endhighlight %}

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:

{% highlight console %} $ rqworker *** Listening for work on default Got count_words_at_url('http://nvie.com') from default Job result = 818 *** Listening for work on default {% endhighlight %}

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+git@github.com:nvie/rq.git@master#egg=rq

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.