celery: daemonic processes are not allowed to have children

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走了就别回头了
走了就别回头了 2021-02-19 03:32

In Python (2.7) I try to create processes (with multiprocessing) in a celery task (celery 3.1.17) but it gives the error:

daemonic processes are not allowed to h         


        
4条回答
  •  我在风中等你
    2021-02-19 03:49

    billiard and multiprocessing are different libraries - billiard is the Celery project's own fork of multiprocessing. You will need to import billiard and use it instead of multiprocessing

    However the better answer is probably that you should refactor your code so that you spawn more Celery tasks instead of using two different ways of distributing your work.

    You can do this using Celery canvas

    from celery import group
    
    @app.task
    def sleepawhile(t):
        print("Sleeping %i seconds..." % t)
        time.sleep(t)
        return t    
    
    def work(num_procs):
        return group(sleepawhile.s(randint(1, 5)) for x in range(num_procs)])
    
    def test(self):
        my_group = group(work(randint(1, 5)) for x in range(5))
        result = my_group.apply_async()
        result.get()
    

    I've attempted to make a working version of your code that uses canvas primitives instead of multiprocessing. However since your example was quite artificial it's not easy to come up with something that makes sense.

    Update:

    Here is a translation of your real code that uses Celery canvas:

    tasks.py:

    @shared_task
    run_training_method(saveindex, embedder_id):
        embedder = Embedder.objects.get(pk=embedder_id)
        embedder.training_method(saveindex)
    

    models.py:

    from tasks import run_training_method
    from celery import group
    
    class Embedder(Model):
    
        def embedder_update_task(self):
            my_group = []
    
            for saveindex in range(self.start_index, self.start_index + self.nsaves):
                self.create_storage(saveindex)
                # Add to list
                my_group.extend([run_training_method.subtask((saveindex, self.id)) 
                             for i in range(self.nproc)])
    
            result = group(my_group).apply_async()
    

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