The multiprocessing module creates separate Python processes that bypass the GIL, enabling true parallel execution for CPU-intensive tasks.
Unlike threading, multiprocessing actually uses multiple CPU cores simultaneously - each process has its own Python interpreter and memory space!
The threading module enables concurrent execution through threads with synchronization primitives like Lock, Event, and Semaphore for safe resource sharing.
Python’s Global Interpreter Lock (GIL) means only one thread executes Python code at once - threading helps with I/O-bound tasks, not CPU-bound ones!
Asyncio enables asynchronous programming with async/await syntax, allowing single-threaded concurrent execution perfect for I/O-bound tasks like web requests and file operations.
Asyncio can handle thousands of concurrent connections with minimal memory overhead - a single asyncio application can often outperform traditional threaded servers by avoiding context switching costs.