What are the performance issues with locks in Python?

What are the performance issues with locks in Python?

Locks in Python can lead to performance bottlenecks, especially in multi-threaded applications. They can cause thread contention, where multiple threads are waiting for a lock to be released, leading to increased latency.

How can I mitigate these performance issues?

You can mitigate performance issues by using lock-free data structures, reducing the scope of locks, or using higher-level abstractions like concurrent.futures or asyncio.

Are there alternatives to using locks?

Yes, alternatives include using semaphores, condition variables, or even message passing to avoid shared state altogether.

What are the trade-offs of using these alternatives?

The trade-offs include complexity in code, potential for increased latency, and the need for careful design to avoid race conditions.