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That is just not true.
1 - This helps parallelize regular python code too, like the kind that goes into writing web services.
2 - While you'd still write native extensions to get optimum performance for single threaded code, having the thread dispatch layer in python makes parallelizing execution convenient and robust. For example, see this comment from people who maintain scikit-learn: (https://github.com/colesbury/nogil/issues/36#issuecomment-10...). I'd love to see python get composable task parallelism like Julia where you can freely spawn threads within threads without worrying about their lifetimes.
Numpy.
Here's a patch the author himself wrote to fix a spot where this change break's numpy's thread safety: https://github.com/colesbury/numpy/commit/2ad41a1fb8b0c28fa8...
Maybe that's the only one? Maybe it isn't? But I think the point still stands that people saying this has the potential to break existing Python packages in subtle ways are not just being hyperbolic.