An implementation and backport of background workers and tasks in Django, as defined in DEP 0014.
Warning: This package is under active development, and breaking changes may be released at any time. Be sure to pin to specific versions if you're using this package in a production environment.
python -m pip install django-tasks
The first step is to add django_tasks
to your INSTALLED_APPS
.
INSTALLED_APPS = [
# ...
"django_tasks",
]
Secondly, you'll need to configure a backend. This connects the tasks to whatever is going to execute them.
If omitted, the following configuration is used:
TASKS = {
"default": {
"BACKEND": "django_tasks.backends.immediate.ImmediateBackend"
}
}
A few backends are included by default:
django_tasks.backends.dummy.DummyBackend
: Don't execute the tasks, just store them. This is especially useful for testing.django_tasks.backends.immediate.ImmediateBackend
: Execute the task immediately in the current threaddjango_tasks.backends.database.DatabaseBackend
: Store tasks in the database (via Django's ORM), and retrieve and execute them using thedb_worker
management command
Note: DatabaseBackend
additionally requires django_tasks.backends.database
adding to INSTALLED_APPS
.
Note: This documentation is still work-in-progress. Further details can also be found on the DEP. The tests are also a good exhaustive reference.
A task is created with the task
decorator.
from django_tasks import task
@task()
def calculate_meaning_of_life() -> int:
return 42
The task decorator accepts a few arguments to customize the task:
priority
: The priority of the task (between -100 and 100. Larger numbers are higher priority. 0 by default)queue_name
: Whether to run the task on a specific queuebackend
: Name of the backend for this task to use (as defined inTASKS
)enqueue_on_commit
: Whether the task is enqueued when the current transaction commits successfully, or enqueued immediately. By default, this is handled by the backend (see below).enqueue_on_commit
may not be modified with.using
.
These attributes (besides enqueue_on_commit
) can also be modified at run-time with .using
:
modified_task = calculate_meaning_of_life.using(priority=10)
In addition to the above attributes, run_after
can be passed to specify a specific time the task should run. Both a timezone-aware datetime
or timedelta
may be passed.
To execute a task, call the enqueue
method on it:
result = calculate_meaning_of_life.enqueue()
The returned TaskResult
can be interrogated to query the current state of the running task, as well as its return value.
If the task takes arguments, these can be passed as-is to enqueue
.
By default, tasks are enqueued after the current transaction (if there is one) commits successfully (using Django's transaction.on_commit
method), rather than enqueueing immediately.
This can be configured using the ENQUEUE_ON_COMMIT
setting. True
and False
force the behaviour.
TASKS = {
"default": {
"BACKEND": "django_tasks.backends.immediate.ImmediateBackend",
"ENQUEUE_ON_COMMIT": False
}
}
This can also be configured per-task by passing enqueue_on_commit
to the task
decorator.
By default, tasks are enqueued onto the "default" queue. When using multiple queues, it can be useful to constrain the allowed names, so tasks aren't missed.
TASKS = {
"default": {
"BACKEND": "django_tasks.backends.immediate.ImmediateBackend",
"QUEUES": ["default", "special"]
}
}
Enqueueing tasks to an unknown queue name raises InvalidTaskError
.
To disable queue name validation, set QUEUES
to []
.
First, you'll need to add django_tasks.backends.database
to INSTALLED_APPS
:
INSTALLED_APPS = [
# ...
"django_tasks",
"django_tasks.backends.database",
]
Then, run migrations:
./manage.py migrate
Next, configure the database backend:
TASKS = {
"default": {
"BACKEND": "django_tasks.backends.database.DatabaseBackend"
}
}
Finally, you can run the db_worker
command to run tasks as they're created. Check the --help
for more options.
./manage.py db_worker
After a while, tasks may start to build up in your database. This can be managed using the prune_db_task_results
management command, which deletes completed and failed tasks according to the given retention policy. Check the --help
for the available options.
When enqueueing a task, you get a TaskResult
, however it may be useful to retrieve said result from somewhere else (another request, another task etc). This can be done with get_result
(or aget_result
):
result_id = result.id
# Later, somewhere else...
calculate_meaning_of_life.get_result(result_id)
Only tasks of the same type can be retrieved this way. To retrieve the result of any task, you can call get_result
on the backend:
from django_tasks import default_task_backend
default_task_backend.get_result(result_id)
If your task returns something, it can be retrieved from the .return_value
attribute on a TaskResult
. Accessing this property on an unfinished task (ie not COMPLETE
or FAILED
) will raise a ValueError
.
assert result.status == ResultStatus.COMPLETE
assert result.return_value == 42
If a result has been updated in the background, you can call refresh
on it to update its values. Results obtained using get_result
will always be up-to-date.
assert result.status == ResultStatus.NEW
result.refresh()
assert result.status == ResultStatus.COMPLETE
If a task raised an exception, its .exception
will be the exception raised:
assert isinstance(result.exception, ValueError)
As part of the serialization process for exceptions, some information is lost. The traceback information is reduced to a string that you can print to help debugging:
assert isinstance(result.traceback, str)
The stack frames, globals()
and locals()
are not available.
If the exception could not be serialized, the .result
is None
.
Because django-tasks
enables support for multiple different backends, those backends may not support all features, and it can be useful to determine this at runtime to ensure the chosen task queue meets the requirements, or to gracefully degrade functionality if it doesn't.
supports_defer
: Can tasks be enqueued with therun_after
attribute?supports_async_task
: Can coroutines be enqueued?supports_get_result
: Can results be retrieved after the fact (from any thread / process)?
from django_tasks import default_task_backend
assert default_task_backend.supports_get_result
This is particularly useful in combination with Django's system check framework.
A few Signals are provided to more easily respond to certain task events.
Whilst signals are available, they may not be the most maintainable approach.
django_tasks.signals.task_enqueued
: Called when a task is enqueued. The sender is the backend class. Also called with the enqueuedtask_result
.django_tasks.signals.task_finished
: Called when a task finishes (COMPLETE
orFAILED
). The sender is the backend class. Also called with the finishedtask_result
.
See CONTRIBUTING.md for information on how to contribute.