What are the differences between multiprocessing and threading in Python?

What are the differences between multiprocessing and threading in Python?

Multiprocessing uses multiple processes, while threading uses multiple threads within a single process. Multiprocessing can take advantage of multiple CPU cores, making it better for CPU-bound tasks, whereas threading is more suitable for I/O-bound tasks.

Can you give me an example of when to use each?

Sure! Use multiprocessing for tasks like image processing or data analysis that require heavy computation. Use threading for tasks like web scraping or network requests where waiting for I/O is common.

What are the performance implications of each?

Multiprocessing can lead to better performance for CPU-bound tasks due to parallel execution, but it has higher overhead. Threading is lighter on resources but may suffer from the Global Interpreter Lock (GIL) in Python, limiting true parallelism.

How do I implement both in Python?

You can use the multiprocessing module for multiprocessing and the threading module for threading. Each has its own set of functions and classes to manage processes or threads.