When asyncio helps and when it does not

What it is

asyncio provides an event loop that runs coroutines (async def functions). A coroutine gives control back to the loop at each await on an I/O operation, so thousands of network connections can be in flight on one thread. asyncio.gather and task groups run coroutines concurrently; asyncio.to_thread moves blocking calls to a worker thread.

Why it matters

Servers and clients that wait on many sockets are the natural fit: waiting is where the time goes, and the loop spends it on other tasks. Code that computes (parsing, hashing, number crunching) gains nothing because only one coroutine runs at a time; such work belongs in threads or processes.

How to apply

• Use async libraries end to end (HTTP client, database driver); one synchronous call in a coroutine blocks every other task for its duration.
• Wrap unavoidable blocking calls with asyncio.to_thread or run_in_executor.
• Bound concurrency with a semaphore so that a burst of tasks does not exhaust connections or memory.
• Set timeouts on every await that talks to the network (asyncio.timeout).

Pitfalls

Forgetting await creates a coroutine object that never runs (Python warns). Cancelling tasks without handling CancelledError can leave resources open. Mixing threads and the loop requires call_soon_threadsafe; touching loop objects from another thread is a data race.