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[Python-Dev] Benchmarks why we need PEP 576/579/580

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I did exactly the same benchmark again with Python 3.7 and the results are similar. I'm copying and editing the original post for completeness:I finally managed to get some real-life benchmarks for why we need afaster C calling protocol (see PEPs 576, 579, 580).I focused on the Cython compilation of SageMath. By default, a functionin Cython is an instance of builtin_function_or_method (analogously,method_descriptor for a method), which has special optimizations in theCPython interpreter. But the option "binding=True" changes those to acustom class which is NOT optimized.I ran the full SageMath testsuite several times on Python 2.7 without and with binding=True to find out any significant differences. I then checked if those differences could be reproduced on Python 3.7 (SageMath has not been fully ported to Python 3 yet). The most dramatic difference is multiplication for generic matrices. More precisely, with the following command:python3 -m timeit -s "from sage.all import MatrixSpace, GF; M =MatrixSpace(GF(9), 200).random_element()" "M * M"With binding=False, I got1 loop, best of 5: 1.19 sec per loopWith binding=True, I got1 loop, best of 5: 1.83 sec per loopThis is a big regression which should be gone completely with PEP 580.I used Python 3.7, SageMath 8.3.rc1 (plus a few patches to make it work with binding=True and with Python 3.7) and Cython 0.28.4.I hope that this finally shows that the problems mentioned in PEP 579are real.Jeroen.

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