What are the differences between threading and multiprocessing?

What are the differences between threading and multiprocessing?

Threading and multiprocessing are both techniques to achieve concurrent execution in programming. Threading involves multiple threads within a single process, sharing the same memory space, which makes it lightweight but can lead to issues like race conditions. Multiprocessing, on the other hand, uses multiple processes, each with its own memory space, which avoids these issues but has more overhead.

Which one is better for CPU-bound tasks?

For CPU-bound tasks, multiprocessing is generally better because it can utilize multiple CPU cores effectively, allowing for true parallelism. Threading may not provide significant performance improvements due to the Global Interpreter Lock (GIL) in languages like Python.

And what about I/O-bound tasks?

For I/O-bound tasks, threading is often more efficient. Since these tasks spend a lot of time waiting for external resources, using threads can help keep the program responsive by allowing other threads to run while one is waiting.

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

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