3e2e26e702
* Add an exception handler for the pubsub thread After a connection error to Redis the pubsub thread was stopped and the worker could not receive commands anymore. This commit adds an exception handler for the thread that adds a log message and ignores `redis.exceptions.ConnectionError`. Any other exception is re-raised. redis-py internal mechanism allows the pubsub thread to recover its connection and reinstall the pubsub channel subscription to allow the worker to receive commands again after connection errors. It tries to behave the same as the main worker loop retry mechanism but without the backoff wait factor. Fixes #1836 Fixes #2070 * Add test for untested line, improve logging and comments Add *args & **kwargs to tests.fixtures.raise_exc to pass tests with Python 3.7 |
||
---|---|---|
.github | ||
docs | ||
examples | ||
rq | ||
tests | ||
.coveragerc | ||
.deepsource.toml | ||
.gitignore | ||
.mailmap | ||
.pre-commit-config.yaml | ||
CHANGES.md | ||
Dockerfile | ||
LICENSE | ||
Makefile | ||
README.md | ||
codecov.yml | ||
pyproject.toml | ||
tox.ini |
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.
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())
Then, create an RQ queue:
from redis import Redis
from rq import Queue
queue = Queue(connection=Redis())
And enqueue the function call:
from my_module import count_words_at_url
job = queue.enqueue(count_words_at_url, 'http://nvie.com')
Scheduling jobs are also similarly easy:
# Schedule job to run at 9:15, October 10th
job = queue.enqueue_at(datetime(2019, 10, 10, 9, 15), say_hello)
# Schedule job to run in 10 seconds
job = queue.enqueue_in(timedelta(seconds=10), say_hello)
Retrying failed jobs is also supported:
from rq import Retry
# Retry up to 3 times, failed job will be requeued immediately
queue.enqueue(say_hello, retry=Retry(max=3))
# Retry up to 3 times, with configurable intervals between retries
queue.enqueue(say_hello, retry=Retry(max=3, interval=[10, 30, 60]))
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 --with-scheduler
*** 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 git+https://github.com/rq/rq.git@master#egg=rq
Docs
To build and run the docs, install jekyll and run:
cd docs
jekyll serve
Related Projects
If you use 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.