[mrtranscendence]

Python on 2024 hardware vs C++ on 2004 hardware ... I don't think it's obvious that C++ always wins here, though it would depend on the use case, how much of the Python is underpinned by native libraries, and the specific hardware in question.

[JohnKemeny]

If we allow native libraries, it's not clear that C++ would win, even on modern hardware.

[michaelt]

I think we all know that, when someone writes "C++ is three orders of a magnitude faster than Python" they're not including native libraries.

[mrtranscendence]

You can't not include native libraries, at least if you want your benchmark to be realistic. Almost every Python library where performance matters is written (at least partially) in a compiled language.

[bornfreddy]

Yes, but many people like the sound of "X-times faster than Python" while conveniently forgetting that the same thing can be (and usually is) done in Python + numpy & co. even faster.

I have come to appreciate "slowness" of Python. It trades speed for legibility, which is a great compromise once you have really fast native libraries one import away. Best of both worlds.

[MichaelDickens]

C++ with well-optimized libraries should always outperform Python with well-optimized libraries, right? They should be ~identical in the highly optimized inner loops, but Python has more overhead. But naive hand-written C++ could easily perform worse than something like Numpy.

(I've only tested this once, and my naive hand-written C++ was still twice as fast as Numpy, but that was only on one specific task.)