What are the best practices for multiprocessing in Python?

What are the best practices for multiprocessing in Python?

When using multiprocessing in Python, it's important to follow best practices like avoiding shared state, using queues for communication, and ensuring proper cleanup of processes.

Can you explain why avoiding shared state is important?

Avoiding shared state helps prevent race conditions and makes your code easier to understand and maintain. Each process should operate independently.

What are some common pitfalls to watch out for?

Common pitfalls include not managing process lifecycles properly, using too many processes, and failing to handle exceptions in child processes.

How can I measure the performance of my multiprocessing code?

You can use the time module to measure execution time or profiling tools like cProfile to analyze performance bottlenecks.