[Python module] multiprocessing

multiprocessing — Process-based “threading” interface
Introduction
multiprocessing is a 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.
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Warning
Some of this package’s functionality requires a functioning shared semaphore implementation on the host operating system. Without one, the multiprocessing.synchronize module will be disabled, and attempts to import it will result in an ImportError. See issue 3770 for additional information.
Note
Functionality within this package requires that the __main__ method be importable by the children. This is covered in Programming guidelines however it is worth pointing out here. This means that some examples, such as the multiprocessing.Pool examples will not work in the interactive interpreter. For example:
>>> from multiprocessing import Pool
>>> p = Pool(5)
>>> def f(x):
... return x*x
...
>>> p.map(f, [1,2,3])
Process PoolWorker-1:
Process PoolWorker-2:
Traceback (most recent call last):
AttributeError: 'module' object has no attribute 'f'
AttributeError: 'module' object has no attribute 'f'
AttributeError: 'module' object has no attribute 'f'
The Process class
In multiprocessing, processes are spawned by creating a Process object and then calling its start() method. Process follows the API of threading.Thread. A trivial example of a multiprocess program is
from multiprocessing import Process
def f(name):
print('hello', name)
if __name__ == '__main__':
p = Process(target=f,