Python_Multiprocessing_Entry_Point.py

# Python multiprocessing - Process-based parallelism
# The following scripts are written to demonstrate multiprocessing (Process-based parallelism) 
# using Python.
# Multiprocessing is a Python package that supports spawning processes using an API similar to 
# the threading module. The multiprocessing package offers both local and remote concurrency, 
# effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. 
# Due to this, the multiprocessing module allows the programmer to fully leverage multiple 
# processors on a given machine. It runs on both Unix and Windows.
# The multiprocessing module also introduces APIs which do not have analogs in the threading module. 
# A prime example of this is the Pool object which offers a convenient means of parallelizing the 
# execution of a function across multiple input values, distributing the input data across processes 
# (data parallelism). 
# Using the spawn or forkserver start method running the following module would fail with a RuntimeError.
# Instead one should protect the “entry point” of the program by using if __name__ == '__main__': 
# as follows:
 
from multiprocessing import Process, freeze_support, set_start_method

def foo():
    print('hello')

if __name__ == '__main__':

    freeze_support()
    set_start_method('spawn')

    p = Process(target=foo)
    p.start()