mypyc-benchmark-results VS beartype

This looks very cool ! There is also MyPyC which is not in the comparison table, but worth noting.

They have some benchmarks vs regular python here :

https://github.com/mypyc/mypyc-benchmark-results/blob/master...

One difference is that MyPyC compiles your code to a C extension, so your are still dependent on python. On the other hand you can call regular python libraries with the normal syntax while, in LPython, the "break-out" syntax to regular libraries isn't straightforward

In any case super exiting to see work going into AOT python

The post isn't about performance, and is aimed at people using Python for whatever reason, so, sure, retrofit away.

That said, if you care about the performance improvements that typing can give you with Mypy, you might want to look here:

https://github.com/mypyc/mypyc-benchmark-results/blob/master...

It won't be going toe to toe with Rust any time soon, but a 4x to 17x speedup is nothing to sneeze at.

https://github.com/mypyc/mypyc-benchmark-results/blob/master...

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.