GIL ensures only one thread executes python byte at a time, limiting multi-threading efficiency.

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Accepted Answer

Yes, the Global Interpreter Lock (GIL) in Python ensures only one thread can execute Python bytecode at a time, limiting the efficiency of multi-threading.

GIL is a mutex that protects access to Python objects, preventing multiple threads from executing Python bytecodes simultaneously.
This means that even on multi-core systems, Python threads cannot fully utilize all available CPU cores for parallel processing.
However, GIL does not prevent multi-threading for I/O-bound tasks or when using external libraries that release the GIL, such as NumPy or Pandas.
To overcome GIL limitations, developers can use multiprocessing or asynchronous programming with libraries like asyncio or concurrent.futures.

GIL ensures only one thread executes python byte at a time, limiting multi-threading efficiency.

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