Python_Multiprocessing_Remote_Client_Manager.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 a remote manager
# It is possible to run a manager server on one machine and have clients use it from other machines 
# (assuming that the firewalls involved allow it).
# Running the following commands creates a server for a single shared queue which remote clients 
# can access:
 
from multiprocessing.managers import BaseManager
from queue import Queue

queue = Queue()
class QueueManager(BaseManager): pass
QueueManager.register('get_queue', callable=lambda:queue)

m = QueueManager(address=('', 50000), authkey=b'abracadabra')
s = m.get_server()
s.serve_forever()