Task is a Python function which will be launched in the separate thread.

Defining task with annotation

from atasker import background_task

def mytask():
    print('I am working in the background!')

task = mytask()

It’s not required to notify task supervisor about task completion, background_task will do this automatically as soon as task function is finished.

All start parameters (args, kwargs) are passed to task functions as-is.

Task function without annotation

To start task function without annotation, you must manually decorate it:

from atasker import background_task, TASK_LOW

def mytask():
    print('I am working in the background!')

task = background_task(mytask, name='mytask', priority=TASK_LOW)()

Multiprocessing task

Run as background task

To put task into multiprocessing pool, append parameter tt=TT_MP:

from atasker import TASK_HIGH, TT_MP

task = background_task(
    tests.mp.test, priority=TASK_HIGH, tt=TT_MP)(1, 2, 3, x=2)

Optional parameter callback can be used to specify function which handles task result.


Multiprocessing target function always receives _task_id param.

Run in async way

You may put task from your coroutine, without using callback, example:

from atasker import co_mp_apply, TASK_HIGH

async def f1():
    result = await co_mp_apply(
        tests.mp.test, args=(1,2,3), kwargs={'x': 2},

Task object

If you saved only task.id but not the whole object, you may later obtain Task object again:

from atasker import task_supervisor

task = task_supervisor.get_task(task.id)

Task info object fields:

  • id task id
  • task task object
  • tt task type (TT_THREAD, TT_MP)
  • priority task priority
  • time_queued time when task was queued
  • time_started time when task was started
  • result task result
  • status task status
    0 queued 2 delayed 100 started 200 completed -1 canceled

If task info is None, consider the task is completed and supervisor destroyed information about it.


As soon as task is marked as completed, supervisor no longer stores information about it

Wait until completed

You may wait until pack of tasks is completed with the following method:

from atasker import wait_completed

wait_completed([task1, task2, task3 .... ], timeout=None)

The method return list of task results if all tasks are finished, or raises TimeoutError if timeout was specified but some tasks are not finished.

If you call method with a single task instead of list or tuple, single result is returned.