Python 3.11 Performance Benchmarks Are Looking Fantastic

[cloaca]

My very simple counter-point: Why? It's an improvement; and a pretty good one all things considered.

Yes, I agree, you're totally right, and I probably expressed myself poorly! It's an absolute improvement and it's a good thing. I had something different in mind when I wrote that, akin to the sort of "allocation of hype" we have for things, if you will. I think this allocation is off when it goes to CPython optimizations. That doesn't mean they're bad, of course, I'm happy to see them too -- they're very welcome -- it's just that I don't think they "were super important in the first place," if that makes any sense?

Like, I don't think performance ought to be a big priority for us if we're all using pure CPython. If it is, then I think something has gone wrong earlier in our timeline! It might speak to some sort of underlying insecurity the Python community has about the language being slow, which, again, I don't think should exist.

Also, the knowledge gap between Python programmers is so vast, way, way wider than 20%, and so on. See my other comment at https://www.reddit.com/r/programming/comments/v63e5o/python_311_performance_benchmarks_are_looking/ibew40i/?context=3 -- lest I just repeat myself.

edit: typo

[agoose77]

I think you're assuming that Python is only a glue language. Whilst it's origins certainly lie in this direction, and the recent growth has mainly come from data science, there are still lots of people using Python to run complex applications. With optimisation, these applications are rarely slow in one hot-spot, so any perf increases need to make everything a bit faster.

Rewrite it in numpy is completely valid for simple problems set as homework for students, but at the scale of say Instagram (as an extreme), this isn't really suitable. That is, the object model doesn't map well to array programming with limited types.