Using multiple processes

Key 2: Churning CPU-intensive tasks.

Multiple processes are helpful to fully utilize all CPU cores. It helps in CPU-intensive work as tasks are run in separate processes, and there is no GIL between actual working processes. The setup and communication cost between processes is higher than threads. In the following code section, proc_iotask, proc_cputask are processes that run them for various inputs:

import time
from tasker import cputask, iotask
from random import randint
import multiprocessing,random,string

def proc_iotask(i,outq):
    i[1] = iotask(i[0])
    outq.put(i)

def proc_cputask(i,outq):
    res = cputask(i[0])
    outq.put((i[0],res))

stats = {}

def process(rep, case=None):
    stats.clear()
    inputs = [[randint(1, 1000), None] for i in range(rep) ]
    outq = multiprocessing.Queue()
    processes = []
    if 'cpu' == case:
        processes.extend([ 
            multiprocessing.Process(target=proc_cputask, args=(i,outq)) 
                for i...