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> Or "we'll write the bottlenecks in C++"... until you realise that it's all bottleneck. Isn't this exactly how python works with pytorch, polars, and similar
by mejutoco 4y ago
> Or "we'll write the bottlenecks in C++"... until you realise that it's all bottleneck.
Isn't this exactly how python works with pytorch, polars, and similar very fast libraries?
- IshKebab 4y agoYes it works for highly numerical code. Most code is not like that.
- mejutoco 4y agoIf we are pedantic all code running in a computer is numeric, but I get your point for gpu calculations for pytorch or numba, so I won't make that point :) I would describe polars a library to work with data (https://www.pola.rs/ https://www.pola.rs/). So we have a high-performance library in Python to work with generic data. I think that covers a lot of cases, since you can transform arbitrary parts of a program into data. Ask any lisp fan. Typescript is great, and the approach of having native high-performance modules works great for Python. You can offload, if you want to, a big part of your program to high-performance libraries. Maybe it is not the most elegant, but it works. Python is not cpp, but if it fits your use-case, it can be quite performant.