pyre-check VS beartype

Did you come across pyre in your search? MIT license and pretty fast.

https://github.com/facebook/pyre-check

Pyre is a performant type-checker developed by Facebook. Pyre can analyse codebases with millions of lines of code incrementally – providing instantaneous feedback to developers as they write code.

Pyre from Meta, pyright from Microsoft and PyType from Google provide additional assistance. They can 'infer' types based on code flow and existing types within the code.

Have you seen Pyre[0]? Not Rust, OCaml, and pretty fast. Made by a team at Meta and open sourced on GitHub. If you use python-lsp, I wrote an extension[1] to enable integration (though I haven't tested it recently, been programming in rust; it is mostly a "for me" extension).

0: https://pyre-check.org/

1: https://github.com/cricalix/python-lsp-pyre

Internally we use Pyre for Python type checking: https://github.com/facebook/pyre-check

Before type hinting, work had intense rules and linters enforcing docstrings with types. Now, type hints and automatic pyre runs take care of all the heavy lifting.

Python now has an optional type system and if you add one of them such as mypy or pyre to your CI process and you can configure GitHub to refuse the pull request until types are added you can make it somewhat strongly typed.

If you have a preexisting codebase I believe the way you can convert it is to add the types that you know on commits and eventually you will have enough types that adding the missing ones should be easy. For the missing ones Any is a good choice.

https://pyre-check.org and https://github.com/python/mypy are popular.

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.