Asynchronous (concurrent) programming allows a program to overlap I/O-bound waiting (e.g., network, disk, database) with other work rather than blocking sequentially, which differs from CPU-bound parallelism. In Python, this concurrency model is implemented via an event loop, a single-threaded scheduler that tracks tasks, checks their completion, and resumes execution once tasks finish, exposed through the `asyncio` library and the `async`/`await` keywords that mark and coordinate concurrent execution. This model exists as an alternative to multi-threading, sidestepping Python's Global Interpreter Lock (GIL) by achieving concurrency without true parallel threads, making single-threaded I/O-bound applications more efficient.
Asynchronous (concurrent) programming allows a program to overlap I/O-bound waiting (e.g., network, disk, database) with other work rather than blocking sequentially, which differs from CPU-bound par…