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    <p>Let's first understand what the python GIL provides:</p> <p>Any operation/instruction is executed in the interpreter. GIL ensures that interpreter is held by a single thread at <strong>a particular instant of time</strong>. And your python program with multiple threads works in a single interpreter. At any particular instant of time, this interpreter is held by a single thread. It means that only the thread which is holding the interpreter is <strong>running</strong> at <strong>any instant of time</strong>.</p> <p>Now why is that an issue:</p> <p>Your machine could be having multiple cores/processors. And multiple cores allow multiple threads to execute <strong>simultaneously</strong> i.e multiple threads could execute <strong>at any particular instant of time.</strong>. But since the interpreter is held by a single thread, other threads are not doing anything even though they have access to a core. So, you are not getting any advantage provided by multiple cores because at any instant only a single core, which is the core being used by the thread currently holding the interpreter, is being used. So, your program will take as long to execute as if it were a single threaded program.</p> <p>However, potentially blocking or long-running operations, such as I/O, image processing, and NumPy number crunching, happen outside the GIL. Taken from <a href="https://wiki.python.org/moin/GlobalInterpreterLock" rel="nofollow noreferrer">here</a>. So for such operations, a multithreaded operation will still be faster than a single threaded operation despite the presence of GIL. So, GIL is not always a bottleneck.</p> <p>Edit: GIL is an implementation detail of CPython. IronPython and Jython don't have GIL, so a truly multithreaded program should be possible in them, thought I have never used PyPy and Jython and not sure of this.</p>
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    1. POWhat is a global interpreter lock (GIL)?
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    1. USAkshar Raaj
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