How does threading improve performance in Python?

How does threading improve performance in Python?

Threading can improve performance in Python by allowing multiple threads to run concurrently, which is beneficial for I/O-bound tasks.

Can you explain the difference between threading and multiprocessing?

Sure! Threading uses threads within a single process, while multiprocessing creates separate processes, allowing for true parallelism.

What are some common use cases for threading in Python?

Common use cases include web scraping, handling multiple client connections in servers, and performing background tasks.

Are there any downsides to using threading in Python?

Yes, threading can lead to issues like race conditions and deadlocks, and due to the Global Interpreter Lock (GIL), it may not improve CPU-bound tasks.

How can I implement threading in my Python application?

You can use the threading module in Python. Start by creating a thread using threading.Thread and then call start() to run it.