![Q logo](https://raw.githubusercontent.com/aaronkurtz/django-q/master/docs/_static/logo.png)
- 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
- Python 2 and 3
- Django > = 1.7
- Django-picklefield
- Arrow
- Blessed
Tested with: Python 2.7 & 3.5. Django 1.7.10 & 1.8.6
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
Check overall statistics with:
$ python manage.py qinfo
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
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.
To run the tests you will need py.test and pytest-django
- Better tests and coverage
- Less dependencies?