Hi All, For scalar operations Numpy first try to extract the underlying C value from a Python Integers. It causes bottleneck because it first converts the Python scalar into its matching NumPy scalar (e.g. PyLong -> int32) and then it extracts the C value from the NumPy scalar.
Its quicker to just extract the value directly from the Python scalar. Raul did it for float but for integers case is different as it get handled by different OS differently. There are basically two standards for long on 64 bit os, Microsoft uses long = int (32 bits), linux uses long = long long (64 bits). Hence, before getting into above mentioned modifications, there is need to have much test case to ensure behaviour of integer remains same. I have written fews at pr #3592 <https://github.com/numpy/numpy/pull/3592> - Arink
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