What are some common pitfalls in Python parallelism?

What are some common pitfalls in Python parallelism?

Some common pitfalls include race conditions, deadlocks, and improper use of the Global Interpreter Lock (GIL).

Can you explain race conditions?

Sure! A race condition occurs when two or more threads access shared data and try to change it at the same time.

How can I avoid deadlocks?

To avoid deadlocks, ensure that all threads acquire locks in a consistent order and use timeout mechanisms.

What is the Global Interpreter Lock?

The GIL is a mutex that protects access to Python objects, preventing multiple threads from executing Python bytecodes simultaneously.

Are there any libraries that can help with parallelism in Python?

Yes, libraries like multiprocessing, concurrent.futures, and joblib can help manage parallel tasks effectively.