How to use multiprocessing.Pool in an imported mod

Question

I have not been able to implement the suggestion here: Applying two functions to two lists simultaneously.

I guess it is because the module is imported by another module and thus my Windows spawns multiple python processes?

My question is: how can I use the code below without the if if __name__ == "__main__":

args_m = [(mortality_men, my_agents, graveyard, families, firms, year, agent) for agent in males]
args_f = [(mortality_women, fertility, year, families, my_agents, graveyard, firms, agent) for agent in females]

with mp.Pool(processes=(mp.cpu_count() - 1)) as p:
    p.map_async(process_males, args_m)
    p.map_async(process_females, args_f)

Both process_males and process_females are fuctions. args_m, args_f are iterators

Also, I don't need to return anything. Agents are class instances that need updating.

Answer 1

The idea of if __name__ == '__main__': is to avoid infinite process spawning.

When pickling a function defined in your main script, python has to figure out what part of your main script is the function code. It will basically re run your script. If your code creating the Pool is in the same script and not protected by the "if main", then by trying to import the function, you will try to launch another Pool that will try to launch another Pool....

Thus you should separate the function definitions from the actual main script:

from multiprocessing import Pool

# define test functions outside main
# so it can be imported withou launching
# new Pool
def test_func():
    pass

if __name__ == '__main__':
    with Pool(4) as p:
        r = p.apply_async(test_func)
        ... do stuff
        result = r.get()

Answer 2

The reason you need to guard multiprocessing code in a if __name__ == "__main__" is that you don't want it to run again in the child process. That can happen on Windows, where the interpreter needs to reload all of its state since there's no fork system call that will copy the parent process's address space. But you only need to use it where code is supposed to be running at the top level since you're in the main script. It's not the only way to guard your code.

In your specific case, I think you should put the multiprocessing code in a function. That won't run in the child process, as long as nothing else calls the function when it should not. Your main module can import the module, then call the function (from within an if __name__ == "__main__" block, probably).

It should be something like this:

some_module.py:

def process_males(x):
    ...

def process_females(x):
    ...

args_m = [...] # these could be defined inside the function below if that makes more sense
args_f = [...]

def do_stuff():
    with mp.Pool(processes=(mp.cpu_count() - 1)) as p:
        p.map_async(process_males, args_m)
        p.map_async(process_females, args_f)

main.py:

import some_module

if __name__ == "__main__":
    some_module.do_stuff()

In your real code you might want to pass some arguments or get a return value from do_stuff (which should also be given a more descriptive name than the generic one I've used in this example).