Comment by ModernMech 5 days ago
Yes, I'm consistent in that. What I don't get is if that's the case, why is there such a focus on improving Python perf? At best they're getting marginal improvements on something that most Python devs claim they don't care about, and which they say is not important for Python as a language due to JIT, C interop, and so on.
I agree, I think that's probably the hope. It's interesting you bring up Julia here because I was just reading the post about the 1.12 release and this comment struck me:
https://news.ycombinator.com/item?id=45524485
Particularly this part is relevent to the Python discussion:
What is Julia's central conceit? It aims to solve "the two language" problem, i.e. the problem where prototyping or rapid development is done in a dynamic and interactive language like Python or MATLAB, and then moved for production to a faster and less flexible language like Rust or C++.
This is exactly what the speaker in the talk addresses. They are still using Julia for prototyping, but their production use of Julia was replaced with Rust. I've heard several more anecdotal stories of the exact same thing occurring. Here's another high profile instance of Julia not making it to production:
https://discourse.julialang.org/t/julia-used-to-prototype-wh...
Julia is failing at its core conceit.
The reason I bring this up is because there's a lot of "cake having/eating" floating around these types of conversations -- that's it's possible to be all the things, without a healthy discussion of what the tradeoffs are in going that direction, and what that would me mean for the people who are happy with the way things are. These little % gains are all Python is going to achieve without actually asking the developer to sacrifice their development process in some way.
I think Julia has largely not solved it because it is clunky to use for purposes other than scientific computing. Python can't be argued to be that, it's very nice for web development as well as scientific computing, the issue is just that for non-scientific computing use cases the perf. isn't great.
I think perhaps their hope is that eventually Python can get to Go-level if not Rust-level performance if they keep up the optimizations. I do personally believe this to be possible. The motivating example is Julia, which is a high level language with low-level language's performance. After arriving there, developers will care.