WRinnovation/django-q

A multiprocessing distributed task queue for Django

Features

Multiprocessing worker pool
Asynchronous tasks
Scheduled and repeated tasks
Encrypted 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 support

Requirements

Tested with: Python 2.7 & 3.5. Django 1.8.14, 1.9.8 and 1.10rc1

Brokers

Installation

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

Configuration

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.

Management Commands

Start a cluster with:

$ python manage.py qcluster

Monitor your clusters with:

$ python manage.py qmonitor

Check overall statistics with:

$ python manage.py qinfo

Creating Tasks

Use async from your code to quickly offload tasks:

from django_q.tasks import async, result

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

# or with a reference
import math.copysign

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

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

For more info see Tasks

Schedule

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))

For more info check the Schedules documentation.

Testing

To run the tests you will need py.test and pytest-django

Todo

Better tests and coverage
Less dependencies?

Acknowledgements

Django Q was inspired by working with Django-RQ and RQ
Human readable hashes by HumanHash
Redditors feedback at r/django

WRinnovation / django-q