If you have good manners, Python codebases can easily grow over 100kloc mark. Static type annotations, using descriptive variable and class names, type checks on user input(esp. libraries) makes growth safe and simple.

I do something similar daily, and it works fine, as we have a strong test suite.

You can't disassociate dynamically typed languages from (strong) test suites, so one needs to qualify:

> Good luck making changes to a 100kloc Python codebase without test suite

versus

> Good luck making changes to a 100kloc Python codebase with a good test suite

In context, the first case is no different from "Good lucking making changes to a 100kloc Rust spaghetti-coded codebase", and one can't meaningfully judge a something based on a poor use of it.

did that on 50k code base with the help of runtime automatic type annotators (e.g.https://github.com/Instagram/MonkeyType) it's absolutely doable, it took a few days total.

You could perhaps start by adding type annotation. They are not perfect, but they help.

No problem. I do it every day.