What are the best practices for concurrency in Python 3.10?

What are the best practices for concurrency in Python 3.10?

In Python 3.10, best practices for concurrency include using the asyncio library for asynchronous programming, leveraging concurrent.futures for parallel execution, and ensuring thread safety when using shared resources.

Can you explain how to use asyncio for managing tasks?

Certainly! You can use asyncio to create coroutines with the async def syntax. Use await to call other coroutines, and asyncio.run() to execute your main coroutine.

What about using threads? When should I prefer them over asyncio?

Threads are useful for I/O-bound tasks where you need to wait for external resources. Use them when you have blocking operations, while asyncio is better for high-level structured network code.

Are there any common pitfalls to avoid with concurrency?

Yes, common pitfalls include race conditions, deadlocks, and not properly handling exceptions in coroutines. Always ensure proper synchronization when accessing shared data.