3c89f9dada
* Initial work on Execution class * Executions are now created and deleted when jobs are performed * Added execution.heartbeat() * Added a way to get execution IDs from execution registry * Job.fetch should also support execution composite key * Added ExecutionRegistry.get_executions() * execution.heartbeat() now also updates StartedJobRegistry * Added job.get_executions() * Added worker.prepare_execution() * Simplified start_worker function in fixtures.py * Minor test fixes * Black * Fixed a failing shutdown test * Removed Execution.create from worker.prepare_job_execution * Fix Sentry test * Minor fixes * Better test coverage * Readded back worker.set_current_job_working_time() * Reverse the order of handle_exception and handle_job_failure * Fix SSL test * job.delete() also deletes executions. * Set job._status to FAILED as soon as job raises an exception * Exclusively use execution.composite_key in StartedJobRegistry * Use codecov v3 * Format with black * Remove print statement * Remove Redis server 3 from tests * Remove support for Redis server < 4 * Fixed ruff warnings * Added tests and remove unused code * Linting fixes |
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.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
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.