Hello, ambitious Python programmers! Today, we’ll delve into the complex world of concurrent programming using Python’s threading and multiprocessing features. Python, as you may know, is an extremely strong language for automating and scripting activities, and one of its most important features is its ability to manage and control threads and processes. A thread is a separate execution flow in Python. This means that your software will have numerous things going on at the same time. However, in most Python 3 implementations, the different threads do not actually execute at the same time, just appear to. Processes, on the other hand, are autonomous instances of Python interpreters. Because memory resources are not shared between these processes, it is suitable for tasks requiring CPU resources. Let’s look at a simple example of a multithreaded Python program:
import threading
def print_numbers():
for i in range(10):
print(i)
def print_letters():
for letter in 'abcdefghij':
print(letter)
thread1 = threading.
Thread(target=print_numbers)
thread2 = threading.
Thread(target=print_letters)
thread1. start()
thread2. start()
In this example, we define two functions: one that writes numerals** 0 to 9** and another that prints letters ‘a’ to ‘j’. We then start both threads by creating two threads and assigning each function to a distinct thread.
Exercise
Write a Python program using threading. Create two threads, one which prints the numbers 1 to 10 and another which prints the alphabet letters from ‘a’ to ‘j’. Start both threads.
Conclusion
Bravo! You’ve learned about Python’s multithreading and multiprocessing today. Using many threads or processes can significantly improve the performance and efficiency of your programs, especially for activities that can be divided and executed concurrently. Continue coding and discovering the power of Python!