lingua-py VS ruff

ᅠ✅ Recognition of 75 languages

Hi u/dekked_, perhaps you want to add my natural language detection library Lingua to the NLP section of the long tail. It is pretty unique among the natural language detection libraries for Python because it is able to detect multiple languages in mixed-language text. It is also one of the most accurate libraries when detecting the language of short text. I would very much appreciate if you added my library to your list.

I've compared the Python implementation of Lingua with fasttext. Lingua performs clearly better. Look here: https://github.com/pemistahl/lingua-py#4-how-good-is-it

I think I mention this all the time when this comes up, but I learned the most 'best practices' through using ruff.

https://docs.astral.sh/ruff/

I just installed and enabled all the rules by setting

Ruff is a Python linter that helps to identify and remove code smells. Over 700 built-in rules: Ruff includes native re-implementations of popular Flake8 plugins, like flake8-bugbear. And also built-in caching to avoid re-analyzing unchanged files.

Because the Python's "ast" modules is too slow, and lacks proper "format" feature (it has unparse but it removes comments, and forgets the current style completely). I use "ruff" a lot (https://github.com/astral-sh/ruff) which is in Rust. But I want to be able to implement fast custom linters in Go (linters that ruff / fixit lack, and Python linters lack or are too slow).

I think it’s interesting that rye uses ruff (https://github.com/astral-sh/ruff) for linting and formatting. That’s the right call, and it’s also correct to bundle that in for an integrated dev experience.

I had to guess, that’s the path that the Astral team would take as well - expand ruff’s capabilities so it can do everything a Python developer needs. So the vision that Armin is describing here might be achieved by ruff eventually. They’d have an advantage that they’re not a single person maintenance team, but the disadvantage of needing to show a return to their investors.

Adding more weight to ease of setup and configurability, the choice came down on flake8. It is easy to integrate, since its also available through pip and let’s you configure which standards you want to omit by simply stating them as a list via the --ignore switch. Moving to ruff appears quite smooth, so future updates may do so.

I confess I stole the pip recipe from Charlie :D

https://github.com/astral-sh/ruff/blob/main/.github/workflow...

Ruff is an emerging tool in the Python ecosystem that describes itself as "an extremely fast Python linter and code formatter, written in Rust".