What is eventloop?

The event loop is a programming concept that lets a single thread handle many tasks by repeatedly checking for and processing events (like user clicks, network responses, or timers). Instead of waiting for each task to finish before starting the next, the loop quickly moves from one ready task to another, keeping the program responsive.

Let's break it down

  • Queue: When something happens (an event), a callback function is placed in a queue.
  • Loop: The event loop runs continuously, looking at the queue.
  • Pick & Run: If there’s a callback in the queue, the loop takes the first one and runs it.
  • Repeat: After the callback finishes, the loop goes back to check the queue again.
  • Non‑blocking: While the loop is waiting for new events, it doesn’t sit idle; it can handle other work like rendering UI or processing other callbacks.

Why does it matter?

Because it lets programs (especially web browsers and servers) stay fast and responsive without needing many separate threads. It avoids the complexity and overhead of multithreading while still handling many simultaneous operations like I/O, timers, and user interactions.

Where is it used?

  • JavaScript in browsers (the classic example)
  • Node.js server‑side JavaScript
  • Python’s asyncio library
  • Dart’s async/await model
  • Many UI frameworks (e.g., Android’s Looper, Swift’s RunLoop)

Good things about it

  • Simplicity: One thread, easier to reason about than many threads.
  • Performance: Low memory and CPU overhead compared to spawning many threads.
  • Scalability: Can handle thousands of concurrent I/O operations.
  • Predictable order: Callbacks run in the order they were queued, making debugging easier.

Not-so-good things

  • CPU‑bound tasks block the loop: Heavy calculations can freeze the whole program if not offloaded.
  • Callback hell: Deeply nested callbacks can become hard to read (though promises/async‑await help).
  • Single point of failure: If the loop crashes, the whole application stops.
  • Limited parallelism: It can’t take advantage of multiple CPU cores for compute‑heavy work without extra workers or threads.