I was so into Python for 10 years, was enjoyable to work in. But have deleted 100k+ lines this year already moving them to faster languages in a post AI codebot world. Mostly moving to go these days.
the funny thing is that everyone, including myself, posited that python would be the winner of the ai coding wars, because of how much training data there is for it. My experience has been the opposite.
From this example:
Do we finally have "lazy imports" in Python? I think I missed this change. Is this also something from Python 3.15 or earlier?Yes, 3.15+
I was so into Python for 10 years, was enjoyable to work in. But have deleted 100k+ lines this year already moving them to faster languages in a post AI codebot world. Mostly moving to go these days.
Thats very intersting, If I may ask was it from professional projects or personal projects?
Same, I’m not sure how Python survives this outside of machine learning.
All of our services we were our are significantly faster and more reliable. We used Rust, it wasn’t hard to do
the funny thing is that everyone, including myself, posited that python would be the winner of the ai coding wars, because of how much training data there is for it. My experience has been the opposite.
a lot of the training data is either for python 2 or just generally very low quality
You can test on the device directly, without needing to recompile to try something.
Go is terrible for scientific/ML work though, the libraries just aren't there. The wrapping C API story is weak too even with LLMs to assist.
Try and write a signal processing thing with filters, windowing, overlap, etc. - there's no easy way to do it at all with the libraries that exist.
I think the purpose of go is to write CRUD. Stray from that and you're on your own.