How can I optimize my Python code for multithreading?

How can I optimize my Python code for multithreading?

To optimize your Python code for multithreading, you can use the threading module. Start by identifying CPU-bound tasks that can run concurrently.

What are some common pitfalls to avoid when using multithreading in Python?

Common pitfalls include race conditions, deadlocks, and excessive context switching. Use locks and semaphores to manage shared resources.

Can you give me an example of using the threading module?

Sure! Here's a simple example:

import threading

def print_numbers():
    for i in range(5):
        print(i)

thread = threading.Thread(target=print_numbers)
thread.start()
thread.join()

How does the Global Interpreter Lock (GIL) affect multithreading in Python?

The GIL allows only one thread to execute at a time in CPython, which can limit the performance of CPU-bound tasks. For I/O-bound tasks, multithreading can still be beneficial.