Multiprocessing

fork:

import os
newpid = os.fork()
if newpid == 0:
    child()
else:
    parent()
print(os.getpid())

https://serverfault.com/a/598005

https://docs.python.org/3/library/multiprocessing.html

• Raymond 2017
• Parallelism in one line (multiprocessing.Pool.map)
• https://timber.io/blog/multiprocessing-vs-multithreading-in-python-what-you-need-to-know/
  • Lot of I/O or Network usage. Multithreading is your best bet because of its low overhead
  • GUI: Multithreading so your UI thread doesn't get locked up
  • If your code is CPU bound. Use multiprocessing (if your machine has multiple cores)

Threading

https://docs.python.org/3/library/threading.html

• Daemon thread - entire program exists only when daemon threads are left.
• join() waits until the thread terminates
• Lock
  • locked/unlocked (default state)
  • acquire(): set locked=True and return if unlocked; otherwise block
  • release(): set locked=False
• Rlock Reentrant lock. May be acquired several times by the same thread. It introduces the concept of "owning thread" and "recursion level". Only after final release() the lock is released.
• Condition - for consumer/producer
  • wait()
  • notify(), notify_all()
• Semaphore - one of the oldest sync primitives, introduced by Dijkstra. Guards resources with limited capacity. E.g. connection pool.
  • P() -> acquire(): counter--; block if counter == 0
  • V() -> release(): counter++
• Event simple mechanism. set()/clear(), wait()
• Timer - call action after a certain time
• Barrier - block until a given threshold has been reached. Then release all threads simultaneously.

A Lock, Condition and a Semaphores (all w. acquire() and release()) can be used in the with statement.