Rope VS beartype

Hi, maintainer of rope here. There are a number of different options to use rope in Vim/Neovim, we've documented them in this page https://github.com/python-rope/rope/wiki/Rope-in-Vim-or-Neovim

If you're looking for something with a bigger codebase, then the rope library in which pylsp-rope is based on is also welcoming of contributions.

I think rope is the standard for refactoring, and should provide autoimports soon, though pyright might also be good for that.

rope

If you are interested in discussing this or have ideas you want to sketch out, meet me at rope's GitHub Discussion.

However, my biggest and most popular open source project is one that I don't originally write, but rather I inherited a popular project that has been abandoned by their original author/maintainers. I use Python a lot, so I wanted to contribute to the community in a significant way, so unlike my other projects I do take the time promoting this project as well. I felt it's more like a community service for this project.

I am the maintainer rope and pylsp-rope. They are libraries for automated Python refactoring and to do that from any LSP-capable editors. We are always welcoming contributors of all levels.

Rope has first class support for Vim and it can do a move refactoring, among other refactorings. From this, this feature is available from python-mode and ropevim.

rope

Okay this depends: if your code is static: perfectly possible for example with https://github.com/python-rope/rope (used for example by VS Code). If it's dynamic / generated via metaprogramming: I never tried it but I can't imagine that it'd work there, yes. However java tooling also can't do that because it simply doesn't support metaprogramming in any noteworthy way.

https://github.com/beartype/beartype

I wish more people started using Beartype, it makes Python bearable

I saw this on /r/Python the other day...

As other folks have commented, type hints are now a big deal. For static typing the best checker is pyright. For runtime checking there is typeguard and beartype. These can be integrated with array libraries through jaxtyping. (Which also works for PyTorch/numpy/etc., despite the name.)

Maybe you're looking for https://github.com/beartype/beartype for runtime type enforcement; it's only at function calls, though, but probably a decent solution for codebases that are not completely typed for MyPy or pyright.

It is though, if you add a type checker to your pipeline and use it without any escape hatches such as `Any` or `type: ignore`, you are essentially making the promise that your code is statically typed. But I say it is a matter of perspective because in my opinion runtime type checking should be avoided if we can get away with statically typed code, but there are type checkers that perform runtime type checking via annotations such as [Beartype](https://github.com/beartype/beartype) (with some trickery like assuming homogenous data structures as to not have to check every element of every structure). Anyway the definition of "type safe" is not 100% even in compiled languages.

There is the beartype project.

Personally I find working around mypy's quirks to be more effort than it's worth, so to offer another option: typeguard or beartype can be used to perform run-time type checking.