What are the best practices for multiprocessing and threading in Python?

What are the best practices for multiprocessing and threading in Python?

When using multiprocessing, ensure that you avoid shared state and use queues for communication. For threading, keep the Global Interpreter Lock (GIL) in mind and prefer I/O-bound tasks.

Can you explain why avoiding shared state is important?

Avoiding shared state prevents race conditions and makes your code more predictable and easier to debug.

What are some common pitfalls to watch out for?

Common pitfalls include deadlocks, excessive context switching, and not properly managing resources like memory.

How can I effectively manage resources in a multiprocessing environment?

Use context managers to handle resources, and ensure that you clean up processes and threads properly to avoid leaks.