Coroutines, Concurrency & Distributed Systems

Primary focus should be on:

1. Using yield to create coroutines
2. Using the new multiprocessing module

and then showing some alternative techniques.

foo bar input() baz.

Multiprocessing

Example by Michele Simionato in comp lang python. Here is an example of using multiprocessing (which is included in Python 2.6 and easy_installable in older Python versions) to print a spin bar while a computation is running:

import sys, time
import multiprocessing
DELAY = 0.1
DISPLAY = [ '|', '/', '-', '\\' ]
def spinner_func(before='', after=''):
    write, flush = sys.stdout.write, sys.stdout.flush
    pos = -1
    while True:
        pos = (pos + 1) % len(DISPLAY)
        msg = before + DISPLAY[pos] + after
        write(msg); flush()
        write('\x08' * len(msg))
        time.sleep(DELAY)
def long_computation():
    # emulate a long computation
    time.sleep(3)
if __name__ == '__main__':
    spinner = multiprocessing.Process(
        None, spinner_func, args=('Please wait ... ', ''))
    spinner.start()
    try:
        long_computation()
        print 'Computation done'
    finally:
        spinner.terminate()

Further Reading

This article argues that large-scale parallelism – which is what multiprocessing supports – is the more important problem to solve, and that functional languages don’t help that much with this problem.

http://jessenoller.com/2009/02/01/python-threads-and-the-global-interpreter-lock/