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A multiprocessing distributed task queue for Django

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Django Q2 is a fork of Django Q. Big thanks to Ilan Steemers for starting this project. Unfortunately, development has stalled since June 2021. Django Q2 is the new updated version of Django Q, with dependencies updates, docs updates and several bug fixes. Original repository: https://github.com/Koed00/django-q

Features

  • Multiprocessing worker pool
  • Asynchronous tasks
  • Scheduled, cron and repeated tasks
  • Signed and compressed packages
  • Failure and success database or cache
  • Result hooks, groups and chains
  • Django Admin integration
  • PaaS compatible with multiple instances
  • Multi cluster monitor
  • Redis, IronMQ, SQS, MongoDB or ORM
  • Rollbar and Sentry support

Changes compared to the original Django-Q:

  • Dropped support for Disque (hasn't been updated in a long time)
  • Dropped Redis, Arrow and Blessed dependencies
  • Updated all current dependencies
  • Added tests for Django 4.x and 5.x
  • Added Turkish language
  • Improved admin area
  • Fixed a lot of issues

See the changelog for all changes.

Requirements

Tested with: Python 3.8, 3.9, 3.10, 3.11 and 3.12. Works with Django 3.2.X, 4.1.X, 4.2.X and 5.0.X

Brokers

Installation

  • Install the latest version with pip:

    $ pip install django-q2
  • Add django_q to your INSTALLED_APPS in your projects `settings.py`:

    INSTALLED_APPS = (
        # other apps
        'django_q',
    )
  • Run Django migrations to create the database tables:

    $ python manage.py migrate
  • Choose a message broker, configure and install the appropriate client library.

Read the full documentation at https://django-q2.readthedocs.org

Configuration

All configuration settings are optional. e.g:

For full configuration options, see the configuration documentation.

Management Commands

For the management commands to work, you will need to install Blessed: <https://github.com/jquast/blessed>

Start a cluster with:

$ python manage.py qcluster

Monitor your clusters with:

$ python manage.py qmonitor

Monitor your clusters' memory usage with:

$ python manage.py qmemory

Check overall statistics with:

$ python manage.py qinfo

Creating Tasks

Use async_task from your code to quickly offload tasks:

For more info see Tasks

Schedule

Schedules are regular Django models. You can manage them through the Admin page or directly from your code:

For more info check the Schedules documentation.

Testing

Running tests is easy with docker compose, it will also start the necessary databases. Just run:

Locale

Currently available in English, German, Turkish, and French. Translation pull requests are always welcome.

Todo

  • Better tests and coverage
  • Less dependencies?

Acknowledgements

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A multiprocessing distributed task queue for Django based on Django-Q

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