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Discussion on: GIL in Python

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Kimmo Sääskilahti • Edited

Thanks for the article!

The performance of the single-threaded process and the multi-threaded process will be the same in python and this is because of GIL in python.

It's maybe worth stressing here that multi-threading can make execution a lot faster. It requires that threads release the GIL when e.g. waiting on I/O. Well-written libraries like NumPy release the GIL whenever possible, allowing multiple computations to proceed in parallel.

Threading runs on a single processor and therefore only runs one at a time.

Single Python process can use multiple cores at the same time in parallel. Try starting e.g. two threads each making a numerical computation with NumPy and you may see the process CPU usage going up to 200 %.

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Aniket Singh Author

yes, it can be taken into consideration although writing on such advanced topics was quite challenging for me, thanks for your feedback noted it.

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