Before we discuss a solution that we can implement to solve the problem of race conditions, let's try to simulate the problem in Python. If you have already downloaded the code for this book from the GitHub page, go ahead and navigate to the Chapter21 folder. Let's take a look at the Chapter21/example1.py file—specifically, the update() function, as follows:
# Chapter21/example1.py
import random
import time
def update():
global counter
current_counter = counter # reading in shared resource
time.sleep(random.randint(0, 1)) # simulating heavy calculations
counter = current_counter + 1 # updating shared resourceThe goal of the preceding update() function is to increment a global variable called counter, and it is to be called by a separate thread in our script. Inside the function, we are interacting with a shared resource—in this case, counter. We then assign the value of counter to another local variable, called current_counter (this...