It is absolutely true that there is massive amounts of room for performance improvements for Python strings and that performance is generally subpar due to implementation decisions/restrictions.

Strings are immutable, so no efficient truncation, concatenation, or modifications of any time, you're always reallocating.

There's no native support for a view of string, so operations like iteration over windows or ranges have to allocate or throw away all the string abstractions.

By nature of how the interpreter stores objects, Strings are always going to have an extra level of indirection compared to what you can do with a language like C.

Python strings have multiple potential underlying representations, and thus have some overhead for managing and dealing with those multiple representations without exposing those details to user code

stringzilla[1] has 10x perf on some string operations - maybe they don't suck, but there's definitely room for improvement

[1] - https://github.com/ashvardanian/StringZilla?tab=readme-ov-fi...

For numpy applications you have to always box a value to get a new python string. It quite far from fast.