How do coroutines differ from threads when handling concurrency in Python?

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How do coroutines differ from threads when handling concurrency in Python?

Asked on Jan 08, 2026

Answer

Coroutines in Python, primarily used with the `asyncio` library, provide a way to handle concurrency by allowing the program to pause and resume execution at certain points, whereas threads run concurrently by preemptively sharing CPU time. Coroutines are more lightweight than threads, as they do not require separate memory stacks and are managed by the Python interpreter rather than the operating system.

Example Concept: Coroutines in Python are functions that can pause their execution (await) and yield control back to the event loop, making them efficient for I/O-bound tasks. Unlike threads, which are preemptively scheduled by the OS and can run simultaneously on multiple cores, coroutines are cooperatively scheduled within a single thread, reducing overhead and avoiding many synchronization issues.

Additional Comment:

Coroutines are ideal for I/O-bound and high-level structured network code.
Threads are better suited for CPU-bound tasks that benefit from parallel execution.
Python's Global Interpreter Lock (GIL) limits true parallelism in threads but does not affect coroutines.
Use `async` and `await` keywords to define and work with coroutines in Python.

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