Python: Multiprocessing Async Apply

async_apply.py

#!/usr/bin/env python3

# the explaination for this behaviour is: http://stackoverflow.com/q/40283772/582917

import functools
from multiprocessing import Pool 

def processing_function(unprocessed_data):
    return unprocessed_data

def callback_function(processed_data):
    print("FUNCTION: " + str(processed_data))

def create_processing_closure(initial_data):
    def processing_function(unprocessed_data):
        return initial_data + unprocessed_data
    return processing_function

def create_callback_closure():
    def callback(processed_data):
        print("CLOSURE: " + str(processed_data))
    return callback

def create_processing_lambda(initial_data):
    return lambda unprocessed_data: initial_data + unprocessed_data

def create_callback_lambda():
    return lambda processed_data: print("LAMBDA: " + str(processed_data))

def processing_partial(unprocessed_data1, unprocessed_data2):
    return (unprocessed_data1 + unprocessed_data2)

def callback_partial(initial_data, processed_data):
    print("PARTIAL: " + str(processed_data))

pool = Pool(processes=1)

print("Testing if they work normally...")

f1 = processing_function
f2 = callback_function

f2(f1(1))

f3 = create_processing_closure(1)
f4 = create_callback_closure()

f4(f3(1))

f5 = create_processing_lambda(1)
f6 = create_callback_lambda()

f6(f5(1))

f7 = functools.partial(processing_partial, 1)
f8 = functools.partial(callback_partial, 1)

f8(f7(1))

# bonus round!
x = 1
f9 = lambda unprocessed_data: unprocessed_data + x
f10 = lambda processed_data: print("GLOBAL LAMBDA: " + str(processed_data))

f10(f9(1))

print("Testing if they work in apply_async...")

# works
pool.apply_async(f1, args=(1,), callback=f2)
# doesn't work
pool.apply_async(f3, args=(1,), callback=f4)
# doesn't work
pool.apply_async(f5, args=(1,), callback=f6)
# works
pool.apply_async(f7, args=(1,), callback=f8)
# doesn't work
pool.apply_async(f9, args=(1,), callback=f10)

pool.close()
pool.join()