When to choose asyncio vs threading in Python?

How to frame this at X (Twitter): Connect your answer to measurable impact, clarity of thought, and trade-offs the team cares about. Below is a strong baseline response you can adapt with your own project examples.

Use asyncio for high-concurrency I/O workloads where tasks spend time waiting on network or disk. It uses cooperative scheduling and a single event loop, which can handle many sockets efficiently.

Use threading for blocking libraries that are not async-aware or when integrating legacy code quickly. For CPU-bound tasks, prefer multiprocessing because Python threads are constrained by the GIL for bytecode execution.

Interview-quality answers mention operational complexity too: async gives throughput but requires end-to-end async stack discipline.