What is the Python Global Interpreter Lock (GIL), how does it impact multi-threaded CPU-bound programs, and what are the workarounds in Python 3.12+?

The Python Global Interpreter Lock (GIL)

The Global Interpreter Lock (GIL) is a mutex mechanism used by the standard CPython interpreter to synchronize thread execution so that only one native OS thread executes Python bytecode at any given moment.

Why was the GIL introduced?

CPython uses reference counting for automatic memory management. Without the GIL, concurrent threads mutating object references would trigger race conditions and memory corruption unless every inte al memory structure was protected by granular locks.

Impact on CPU vs I/O-Bound Tasks

I/O-Bound Workloads: Threads release the GIL while waiting for OS I/O operations (networking, disk). Concurrency with threading works well.
CPU-Bound Workloads: Threads contend for the single GIL, causing thread thrashing and worse performance than single-threaded execution.

from multiprocessing import Pool

def cpu_task(n):
    retu
 sum(i * i for i in range(n))

if __name__ == '__main__':
    with Pool() as pool:
        results = pool.map(cpu_task, [10_000_000, 10_000_000, 10_000_000])
        print("Completed across separate OS processes bypassing GIL.")