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celery task state

Here are the examples of the python api celery.worker.state.task_ready taken from open source projects. By voting up you can indicate which examples are most useful and appropriate. (see this answer). Monitor a celery task state without polling? So first create the task: from cel.tasks import add res = add.delay(3,4) print(res.status) # 'SUCCESS' print(res.id) # '432890aa-4f02-437d-aaca-1999b70efe8d' Returns forget [source] ¶ Forget the result of this task and its parents. class celery.result.EagerResult (id, ret_value, state, traceback = None) [source] ¶ Result that we know has already been executed. Under some conditions, I want to make a celery task fail from within that task. I then run celery_test.py to call the task. get (timeout = None, propagate = True, disable_sync_subtasks = True, ** kwargs) [source] ¶ Wait until task … See the description and example there. Fetch and return the state of the given celery task. Make sure that the task does not have ignore_result enabled. I can’t describe this more completely than Celery’s documentation on task state. Creating an AsyncResult object from the task id is the way recommended in the FAQ to obtain the task status when the only thing you have is the task id.. Enabling this option will force the worker to skip updating states. However, as of Celery 3.x, there are significant caveats that could bite people if they do not pay attention to them. Parameters. I tried the following: from celery.task import task from celery import states @task() def run_simulation(): if some_condition: run_simulation.update_state(state=states.FAILURE) return False However, the task … python celery_test.py. Tasks — Celery 4.4.7 documentation; Tasks — Celery 4.0.1 documentation; Building Progress Bars for the Web with Django and Celery; jobtastic PyPI; Managing asynchronous backend tasks with Django and Celery; Task Queues; Celery in the wild: tips and tricks to run async tasks in the real world C:\Scripts\playground>python celery_test.py PENDING PENDING PENDING PENDING PENDING PENDING PENDING Which then results in this log from the worker. This is used to differentiate between the actual task executed by the worker and any task that was called within a task (using task.__call__ or task.apply ) It really depends on the specific use-case scenario. async_result (tuple(str, celery.result.AsyncResult)) -- a tuple of the Celery task key and the async Celery object used to fetch the task's state. celery._state.get_current_worker_task [source] ¶ Currently executing task, that was applied by the worker. See the description and example there. This is not so easy to do accidentally on Celery since version 4, which changed the default serializer from Pickle to JSON . It works using AsyncResult. Return the task_id (which is given from .delay()) and ask the celery instance afterwards about the state: x = method.delay(1,2) print x.task_id When asking, get a new AsyncResult using this task_id: from celery.result import AsyncResult res = AsyncResult("your-task-id") res.ready() Solution 2: Celery does not update any state when a task is sent, and any task with no history is assumed to be pending (you know the task id after all). The scope of this function is global so that it can be called by subprocesses in the pool. Significant caveats that could bite people if they do not pay attention them. Celery._State.Get_Current_Worker_Task [ source ] ¶ forget the result of this task and its parents serializer from to... By the worker Celery task ¶ forget the result of this task and its parents then... 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