What is the Global Interpreter Lock (GIL) in Python?

This means that in standard CPython (the most common Python implementation), true parallel execution of Python code across multiple CPU cores isn't possible within a single process, even if you use multiple threads.

Why the GIL exists

The GIL simplifies memory management in CPython, since it prevents multiple threads from modifying Python objects simultaneously, avoiding certain categories of bugs and making the interpreter's internals simpler and faster for single-threaded code.

How developers work around it

• Multiprocessing: running separate Python processes (each with its own GIL) instead of threads, to achieve true parallelism
• I/O-bound tasks: threading still helps for tasks that spend most of their time waiting (like network requests), since the GIL is released during I/O waits
• Alternative implementations: some Python implementations, and ongoing work in CPython itself, aim to remove or make the GIL optional in future versions

The GIL is specific to CPython — it's an implementation detail, not a requirement of the Python language itself.