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    While Robert's Answer helps cover some bases for potential misunderstandings behind doing this sort of optimization (which fits this question ), I feel this answers the situation a bit more directly and in-line with the Python context. Commented Apr 12, 2019 at 16:43
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    sorry its somewhat short. I don't have time to write more. But I do think Robert is wrong on this one. The best advice with python seems to be to profile as you code. Dont assume it will be performant and only optimise if you find a problem Commented Apr 12, 2019 at 16:49
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    @Ewan: You don't have to write the entire program first to follow my advice. A method or two is more than sufficient to get adequate profiling. Commented Apr 12, 2019 at 18:43
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    you can also try pypy, which is a JITted python Commented Apr 12, 2019 at 20:30
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    @Ewan If you're really worried about the performance overhead of function calls, whatever you're doing is probably not suited for python. But then I really can't think of many examples there. The vast majority of business code is IO limited and the CPU heavy stuff is usually handled by calling out to native libraries (numpy, tensorflow and so on). Commented Apr 12, 2019 at 21:51