68_multithreading.py

# ******************************************************
# Python threading tutorial
# ******************************************************
# thread =  a flow of execution. Like a separate order of instructions.
#           However each thread takes a turn running to achieve concurrency
#           GIL = (global interpreter lock),
#           allows only one thread to hold the control of the Python interpreter at any one time

# cpu bound = program/task spends most of it's time waiting for internal events (CPU intensive)
#             use multiprocessing

# io bound = program/task spends most of it's time waiting for external events (user input, web scraping)
#            use multithreading

import threading
import time

def eat_breakfast():
    time.sleep(3)
    print("you eat breakfast")

def drink_coffee():
    time.sleep(4)
    print("you drank coffee")

def study():
    time.sleep(5)
    print("you finished study")

x = threading.Thread(target=eat_breakfast, args=())
x.start()

y = threading.Thread(target=drink_coffee, args=())
y.start()

z = threading.Thread(target=study, args=())
z.start()

x.join()
y.join()


# eat_breakfast()
# drink_coffee()
# study()


print(threading.active_count())
print(threading.enumerate())
print(time.perf_counter())