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skieffer 59d1b40d14
Multidependencies (#1397)
* Also accept lists and tuples as value of `depends_on`.

* The elements of the lists/tuples may be either Jobs or Job IDs.
* A single Job / Job ID is still accepted as well.

* Represent _all_ job dependencies in `Job.to_dict()`.

We now represent the entire list, instead of just the first element.

* Fix some doctext regarding plurality of dependencies.

* Add unit tests for job dependencies.

* One unit test establishes a pattern for checking execution order as affected by dependencies.

* Another unit test applies this pattern to the new capability to name multiple dependencies.

* Add unit test for new `depends_on` input formats.

Also test that these are properly persisted.

* Repair `Job.restore()`.

Need to convert bytes back to strings when reloading `dependency_ids`.

* Maintain backwards compat. in `Job.to_dict()`.

Keep the old `dependency_id` (singular) key.

* Provide coverage for new test fixture.

* Simplify some code.

Cut some superfluous `as_text()` calls left over from an earlier commit.

* Check for `dependency_id` in `Job.restore()` for backwd. compat.

Also eliminate use of `as_text()` here, in favor of `.decode()`.

* Switch to snake case instead of camel case.

* Eliminate some usages of `as_text()`.

Also cut some `print` statements.

* Cleanup.

* Accept arbitrary iterables for `Job`'s `depends_on` kwarg.

Instead of requiring a list or tuple, we now make use of `ensure_list()`.

* Add test fixtures.

* Provide a system to get two workers working simultaneously, using `multiprocessing`.
* Define a simple job that just says whether its dependencies are met.
* In `rpush`, make an option to record the name of the worker.

* Improve unit tests on execution order with dependencies.

These now actually have two workers going, which makes a more thorough test.

* Add unit test examining `Job.dependencies_are_met()` at execution time.

* Redesign dependency execution order unit tests.

* Simplify assertions.

* Improve doctext and formatting.

* Move fixture tests to new, dedicated module `test_fixtures.py`.

* Use `enqueue` instead of `enqueue_call` in new unit tests.
4 years ago
.github tests: updated github worklow for tests to use requirements.txt and d… (#1364) 4 years ago
docker Fix #1340 (#1341) 4 years ago
docs Document that --serializer CLI argument is only available in 1.8.0 4 years ago
examples fix print in example 11 years ago
rq Multidependencies (#1397) 4 years ago
tests Multidependencies (#1397) 4 years ago
.coveragerc Ignore local.py (it's tested in werkzeug instead). 11 years ago
.deepsource.toml Fix some code quality issues (#1235) 5 years ago
.gitignore RQ v1.0! (#1059) 6 years ago
.mailmap Add .mailmap 9 years ago
CHANGES.md Bump version to 1.7.0 4 years ago
Dockerfile Fix RQScheduler when run with SSL connection (#1383) 4 years ago
LICENSE Fix year. 13 years ago
MANIFEST.in include requirements.txt in sdist (#1335) 4 years ago
Makefile Clean dist+build folders before releasing 10 years ago
README.md Add link to Github Actions badge in README 4 years ago
dev-requirements.txt tests: updated github worklow for tests to use requirements.txt and d… (#1364) 4 years ago
requirements.txt Improve requirements handling (#1287) 5 years ago
run_tests_in_docker.sh Fix RQScheduler when run with SSL connection (#1383) 4 years ago
setup.cfg modify zadd calls for redis-py 3.0 (#1016) 6 years ago
setup.py Exclude tests directory from wheel builds 4 years ago
tox.ini Fix run_tests to use pytest. (#1033) 6 years ago

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

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, 8, 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 -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.