Understanding how tasks are imported
Behind-the-scenes when you decorate a function with :py:meth:`~Huey.task` or :py:meth:`~Huey.periodic_task`, the function registers itself with a centralized in-memory registry. When that function is called, a reference is put into the queue (along with the arguments the function was called with, etc), and when that message is consumed, the function is then looked-up in the consumer's registry. Because of the way this works, it is strongly recommended that all decorated functions be imported when the consumer starts up.
If a task is not recognized, the consumer will throw a :py:class:`QueueException`
The consumer is executed with a single required parameter -- the import path to a :py:class:`Huey` object. It will import the object along with anything else in the module -- thus you must be sure imports of your tasks should also occur with the import of the Huey object.
Suggested organization of code
Generally, I structure things like this, which makes it very easy to avoid circular imports. If it looks familiar, that's because it is exactly the way the project is laid out in the :ref:`getting started <getting-started>` guide.
config.py, the module containing the :py:class:`Huey` object.
# config.py from huey import RedisHuey huey = RedisHuey('testing', host='localhost')
tasks.py, the module containing any decorated functions. Imports the
hueyobject from the
# tasks.py from config import huey @huey.task() def count_beans(num): print('Counted %s beans' % num)
app.py, the "main" module. Imports both the
config.pymodule and the
# main.py from config import huey # import the "huey" object. from tasks import count_beans # import any tasks / decorated functions if __name__ == '__main__': beans = raw_input('How many beans? ') count_beans(int(beans)) print('Enqueued job to count %s beans' % beans)
To run the consumer, point it at
main.huey, in this way, both the
instance and the task functions are imported in a centralized location.
$ huey_consumer.py main.huey