<ul><li>Multithreading in Python involves running multiple threads within a single process. Threads share the same memory space, making them lightweight and fast to create.</li><li>Multithreading is best for I/O-bound tasks like waiting for network responses or reading files.</li><li>Multiprocessing in Python involves spawning multiple independent processes, each with its own memory space and Python interpreter. It bypasses the Global Interpreter Lock (GIL) and allows true parallelism for CPU-bound tasks.</li><li>Multiprocessing is best for CPU-bound tasks like mathematical computations or image processing.</li></ul>

Multithreading vs Multiprocessing in Python: When to Use Each?

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