• 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, Disque, IronMQ, SQS, MongoDB or ORM
• Rollbar and Sentry support

• Django > = 2.2
• Django-picklefield
• Arrow
• Blessed

Tested with: Python 3.7, 3.8, 3.9 Django 2.2.X and 3.2.X

• Redis
• Disque
• IronMQ
• Amazon SQS
• MongoDB
• Django ORM

• Install the latest version with pip:

  $ pip install django-q
  

• 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-q.readthedocs.org

All configuration settings are optional. e.g:

# settings.py example
Q_CLUSTER = {
    'name': 'myproject',
    'workers': 8,
    'recycle': 500,
    'timeout': 60,
    'compress': True,
    'cpu_affinity': 1,
    'save_limit': 250,
    'queue_limit': 500,
    'label': 'Django Q',
    'redis': {
        'host': '127.0.0.1',
        'port': 6379,
        'db': 0, }
}

For full configuration options, see the configuration documentation.

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

Use async_task from your code to quickly offload tasks:

from django_q.tasks import async_task, result

# create the task
async_task('math.copysign', 2, -2)

# or with a reference
import math.copysign

task_id = async_task(copysign, 2, -2)

# get the result
task_result = result(task_id)

# result returns None if the task has not been executed yet
# you can wait for it
task_result = result(task_id, 200)

# but in most cases you will want to use a hook:

async_task('math.modf', 2.5, hook='hooks.print_result')

# hooks.py
def print_result(task):
    print(task.result)

For more info see Tasks

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

# Use the schedule function
from django_q.tasks import schedule

schedule('math.copysign',
         2, -2,
         hook='hooks.print_result',
         schedule_type=Schedule.DAILY)

# Or create the object directly
from django_q.models import Schedule

Schedule.objects.create(func='math.copysign',
                        hook='hooks.print_result',
                        args='2,-2',
                        schedule_type=Schedule.DAILY
                        )

# Run a task every 5 minutes, starting at 6 today
# for 2 hours
import arrow

schedule('math.hypot',
         3, 4,
         schedule_type=Schedule.MINUTES,
         minutes=5,
         repeats=24,
         next_run=arrow.utcnow().replace(hour=18, minute=0))

# Use a cron expression
schedule('math.hypot',
         3, 4,
         schedule_type=Schedule.CRON,
         cron = '0 22 * * 1-5')

For more info check the Schedules documentation.

To run the tests you will need the following in addition to install requirements:

• py.test
• pytest-django
• Disque from https://github.com/antirez/disque.git
• Redis
• MongoDB

Or you can use the included Docker Compose file.

The following commands can be used to run the tests:

# Create virtual environment
python -m venv venv

# Install requirements
venv/bin/pip install -r requirements.txt

# Install test dependencies
venv/bin/pip install pytest pytest-django

# Install django-q
venv/bin/python setup.py develop

# Run required services (you need to have docker-compose installed)
docker-compose -f test-services-docker-compose.yaml up -d

# Run tests
venv/bin/pytest

# Stop the services required by tests (when you no longer plan to run tests)
docker-compose -f test-services-docker-compose.yaml down

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

• Better tests and coverage
• Less dependencies?

• Django Q was inspired by working with Django-RQ and RQ
• Human readable hashes by HumanHash
• Redditors feedback at r/django
• JetBrains for their Open Source Support Program