Not the version, but the build. Did you compile NumPy from source using the same compiler with both Python versions? If not, that remains my strong hunch about performance difference.
Given what your programs do, it sure seems like the large majority of runtime is spent in supporting numeric libraries, not in Python interpreter itself. Profiling is the way to find out. On Sun, Dec 19, 2021, 1:52 PM Tigran Aivazian <aivazian.tig...@gmail.com> wrote: > To eliminate the possibility of being affected by the different versions > of numpy I have just now upgraded numpy in Python 3.8 environment to the > latest version, so both 3.8 and 3.10 and using numpy 1.21.4 and still the > timing is exactly the same. > _______________________________________________ > Python-Dev mailing list -- python-dev@python.org > To unsubscribe send an email to python-dev-le...@python.org > https://mail.python.org/mailman3/lists/python-dev.python.org/ > Message archived at > https://mail.python.org/archives/list/python-dev@python.org/message/THPN4OWM3A335LDO7HVIQSIDFFVO5URZ/ > Code of Conduct: http://python.org/psf/codeofconduct/ >
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