A multiprocessing distributed task queue for Django
Project description
A multiprocessing distributed task queue for Django
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, Disque, IronMQ, SQS, MongoDB or ORM
Rollbar and Sentry support
Requirements
Django > = 2.2
Tested with: Python 3.7, 3.8 Django 2.2.X and 3.0.X
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_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
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))
# 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.
Testing
To run the tests you will need the following in addition to install requirements:
disque from https://github.com/antirez/disque.git
Redis
MongoDB
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
Locale
Currently available in English and French. Translation pull requests are always welcome.
Todo
Better tests and coverage
Less dependencies?
Acknowledgements
Project details
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