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A multiprocessing distributed task queue for Django

django-q.readthedocs.org

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MIT license

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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

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

Warning

Since Python 3.7 async became a reserved keyword and was refactored to async_task

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 messagebroker , configure and install the appropriate client library.

Read the full documentation athttps://django-q.readthedocs.org

Configuration

All configuration settings are optional. e.g:

# settings.py exampleQ_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 theconfiguration documentation.

Management Commands

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:

fromdjango_q.tasksimportasync_task,result# create the taskasync_task('math.copysign',2,-2)# or with a referenceimportmath.copysigntask_id=async_task(copysign,2,-2)# get the resulttask_result=result(task_id)# result returns None if the task has not been executed yet# you can wait for ittask_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.pydefprint_result(task):print(task.result)

For more info seeTasks

Schedule

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

# Use the schedule functionfromdjango_q.tasksimportscheduleschedule('math.copysign',2,-2,hook='hooks.print_result',schedule_type=Schedule.DAILY)# Or create the object directlyfromdjango_q.modelsimportScheduleSchedule.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 hoursimportarrowschedule('math.hypot',3,4,schedule_type=Schedule.MINUTES,minutes=5,repeats=24,next_run=arrow.utcnow().replace(hour=18,minute=0))# Use a cron expressionschedule('math.hypot',3,4,schedule_type=Schedule.CRON,cron='0 22 * * 1-5')

For more info check theSchedules documentation.

Testing

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

py.test
pytest-django
Disque fromhttps://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 environmentpython -m venv venv# Install requirementsvenv/bin/pip install -r requirements.txt# Install test dependenciesvenv/bin/pip install pytest pytest-django# Install django-qvenv/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 testsvenv/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