Why Julia is so much slower than Python? Invitation to Euler Project

[gevis]

@DNF

There is nothing special about ‘built-in’ functions, and in fact it is quite expected that you can write your own code that is faster than the built-in functions, because you can exploit special properties of your problem that only you know about; or you can speed things up by trading off numerical accuracy or disregarding edge cases. For example, you could easily write your own sum function that outperforms the ‘built-in’ one.

Well, taking into account that, in Julia, one can look into the implementation of each function, probably, you are right.

[DNF]

Sure, you can look into previous implementations to learn lessons from them, but if you have special knowledge about your problem, such as “this custom array type only contains ones”, then you can write unbeatably-fast maximum and minimum functions (and sum and so on) that look nothing like the ‘built-in’ versions.

[StefanKarpinski]

Issue solved: https://github.com/JuliaLang/julia/pull/37075. This function goes from 55 µs on Julia 1.5 to 1.6 μs on master, so a 35x speedup or so. No deep language changes required