What are the best practices for concurrency in Python 3?

What are the best practices for concurrency in Python 3?

Some best practices include using the asyncio library for asynchronous programming, leveraging threading for I/O-bound tasks, and using multiprocessing for CPU-bound tasks.

Can you explain how asyncio works?

asyncio is a library that allows you to write concurrent code using the async/await syntax. It helps manage I/O-bound tasks efficiently.

What are some common pitfalls to avoid with concurrency?

Common pitfalls include race conditions, deadlocks, and not properly managing shared resources. Always ensure thread safety.

How does the Global Interpreter Lock (GIL) affect concurrency?

The GIL allows only one thread to execute at a time in CPython, which can limit the effectiveness of threading for CPU-bound tasks.