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.
[](https://secure.travis-ci.org/rq/rq)
[](https://pypi.python.org/pypi/rq)
[](https://codecov.io/gh/rq/rq)
Full documentation can be found [here][d].
## Support RQ
If you find RQ useful, please consider supporting this project via [Tidelift ](https://tidelift.com/subscription/pkg/pypi-rq?utm_source=pypi-rq&utm_medium=referral&utm_campaign=readme ).
## Getting started
First, run a Redis server, of course:
```console
$ redis-server
```
To put jobs on queues, you don't have to do anything special, just define
your typically lengthy or blocking function:
```python
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][r] package, don't you?
Then, create an RQ queue:
```python
from redis import Redis
from rq import Queue
q = Queue(connection=Redis())
```
And enqueue the function call:
```python
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][d]. But this is the essence.
### The worker
To start executing enqueued function calls in the background, start a worker
from your project's directory:
```console
$ 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
## Project history
This project has been inspired by the good parts of [Celery][1], [Resque][2]
and [this snippet][3], and has been created as a lightweight alternative to the
heaviness of Celery or other AMQP-based queueing implementations.
[r]: http://python-requests.org
[d]: http://python-rq.org/
[m]: http://pypi.python.org/pypi/mailer
[p]: http://docs.python.org/library/pickle.html
[1]: http://www.celeryproject.org/
[2]: https://github.com/resque/resque
[3]: http://flask.pocoo.org/snippets/73/
