Multithreading

Multithreading is similar to running multiple programs concurrently... but better.

Threads within a process share the same data space with the main thread.
Requires less memory overhead and is cheaper than running multiple processes

A thread has a beginning, execution sequence and conclusion. An instruction pointer keeps track of where it is currently running.

Threads can be put to sleep, even while other threads are running.
Threads can also be pre-empted (interrupted)

Multithreading Example:

import time
from threading import Thread 

# Work to be done
def sleeper(i):
    print "thread {:d} sleeps for 5 seconds\n".format(i)
    time.sleep(5)
    print "thread {:d} woke up\n".format(i)

# Creating the workers, and passing individual arguments to each of them
for i in range(10):
    t = Thread(target=sleeper, args=(i,))
    t.start()

thread 0 sleeps for 5 seconds

thread 1 sleeps for 5 seconds
thread 2 sleeps for 5 seconds
thread 3 sleeps for 5 seconds

thread 4 sleeps for 5 seconds


thread 5 sleeps for 5 seconds


thread 6 sleeps for 5 seconds

thread 7 sleeps for 5 seconds
thread 8 sleeps for 5 seconds


thread 9 sleeps for 5 seconds

thread 9 woke up
thread 7 woke up
thread 6 woke up
thread 4 woke up
thread 2 woke up
thread 1 woke up
thread 8 woke up
thread 0 woke up
thread 5 woke up
thread 3 woke up

Your output may not look like mine... that is okay. The time in which the workers start is almost always random due to how concurrent their launch sequences are.

Python

Multithreading