A backport of Django's built-in Tasks framework, `django-tasks` provides a robust way to run asynchronous background tasks within Django applications. As of version 0.12.0, it focuses on mirroring the upstream `django.tasks` package, with backends like DB and RQ now available as separate packages. It maintains an active release cadence, frequently updating to support new Django and Python versions.
Install & Compatibility
Where this runs
tested against v0.12.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
from django_tasks import task
This quickstart demonstrates how to define a task using the `@task` decorator and enqueue it for asynchronous execution using `.delay()`. It includes a minimal Django configuration for testing, assuming the `django-tasks-db` backend is used and installed.
import os
from django.conf import settings
# Minimal Django setup for demonstration
if not settings.configured:
settings.configure(
INSTALLED_APPS=[
'django.contrib.auth',
'django.contrib.contenttypes',
'tasks' # Ensure 'tasks' is in INSTALLED_APPS
],
DATABASES={
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': ':memory:',
}
},
TASKS_BACKEND='tasks_db.backends.DatabaseBackend', # Or 'tasks_rq.backends.RQBackend'
USE_TZ=True
)
# Ensure migrations are run for tasks_db if using it
# In a real project, this would be part of `manage.py migrate`
import django
django.setup()
# This part assumes django-tasks-db is installed for the example
# and that tasks.backends is configured.
# For a true quickstart, you'd run `python manage.py makemigrations tasks_db && python manage.py migrate`
from tasks import task
@task
def greet_user(name):
print(f"Hello, {name}!")
return f"Greeting for {name} completed."
# Enqueue the task for asynchronous execution
result = greet_user.delay("World")
print(f"Task enqueued with ID: {result.pk}")
# To process the task (typically run by a worker process)
# For local testing, you might manually run the task
# from tasks import run_task
# run_task(result.pk)
# You can inspect the result object (needs refresh if worker is separate)
# result.refresh_from_db()
# print(f"Task status: {result.status}")
# print(f"Task result: {result.result}")
Upgrade
Version history
Breaking-change detection hasn't run for this library yet.
Audit
Security & dependencies
CVE tracking and dependency tree are planned for a later release.