Hello, when doing asynchronous programming with Python's asyncio library, what role does the event loop play? What are the advantages of using await instead of callbacks? In terms of performance, in which scenarios should async be preferred and in which ones is sync more logical? I'd like to hear about your experiences on the topic.
How does asynchronous Python work with asyncio?
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Without an event loop, asyncio doesn’t really work, which is why you can think of the event loop as a synchronized “core.” The event loop runs pending coroutines (async functions) one after another, letting them continue when I/O operations finish. For example, when you send an API request the loop waits; when the request completes it resumes, so CPU time isn’t wasted. Using `await` instead of callbacks hugely improves readability—you get a linear structure instead of callback hell. With `await` you can write hierarchical, easy‑to‑understand code.
Performance‑wise, asyncio is especially advantageous for I/O‑bound tasks (network requests, file reads, database queries). For CPU‑bound heavy calculations (e.g., NumPy work) sync versions are better because Python’s GIL (Global Interpreter Lock) limits a single thread. I used asyncio in fintech for high‑frequency payment verification systems and saw a 3‑5× speed boost over sync when making hundreds of API requests concurrently. But I prefer the sync version in scenarios where simplicity and easier debugging matter (like small command‑line tools).