Why does Python’s GIL limit true parallel execution in threads?

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Why does Python’s GIL limit true parallel execution in threads?

Asked on Oct 30, 2025

Answer

Python's Global Interpreter Lock (GIL) is a mutex that protects access to Python objects, preventing multiple native threads from executing Python bytecodes simultaneously. This design simplifies memory management in CPython but limits true parallel execution in multi-threaded programs, as only one thread can execute Python code at a time.

Example Concept: The GIL ensures that only one thread executes in the interpreter at any given time, which prevents race conditions and simplifies garbage collection. However, it also means that CPU-bound Python programs cannot fully utilize multi-core processors, as threads must wait for the GIL to be released before executing, leading to potential performance bottlenecks.

Additional Comment:

The GIL is less of a limitation for I/O-bound programs, where threads spend time waiting for external resources.
For CPU-bound tasks, consider using multiprocessing, which spawns separate processes with independent GILs.
Alternative Python implementations like Jython or IronPython do not have a GIL, but they come with other trade-offs.
Efforts to remove the GIL in CPython have been challenging due to the complexity it introduces in memory management and compatibility.

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