python-multithreading-demo

python-multithreading-demo.py

import threading
from queue import Queue
import time

print_lock = threading.Lock() # special lock we're using to make sure each worker won't pring until it's done with it job

def exampleJob(worker):
    time.sleep(0.5) # let's say a job takes .5s to finish

    with print_lock: # with the lock, print some info. when that's done, release the lock so another worker can print with it
        print(threading.current_thread().name, worker)

def threader():
    while True:
        worker = q.get() # get a worker (thread)
        exampleJob(worker) # run a job with the worker
        q.task_done() # when the job is done, say so - this will release the thread/worker/daemon back into the queue for availability

q = Queue()

for x in range(10): # we have 10 workers to do our jobs
    t = threading.Thread(target = threader)
    t.daemon = True # when the main thread dies, all of the daemons will die with it
    t.start()

start = time.time() # lets see how much time it takes with a linear program vs one with multiple threads in parallel

for worker in range(20): # we have 20 jobs that we want to do
    q.put(worker) # literally putting a worker to work in the queue

q.join() # wait until threads terminate

print('Entire job took:', time.time() - start) # whole program should run for about 1 second because we have 10 workers working on 20 jobs that each take .5s each