marshal.ts VS mypy

zod or yup gets you quite a bit of the way there in practice - when you would reach for a Typescript type, making it in zod instead is more verbose but gives that runtime layer.

But for those who actually want full-stack non-stripped runtime type reflection based on Typescript syntax alone... https://deepkit.io/ - https://deepkit.io/blog/introducing-deepkit-framework - is a really promising and cool project.

It patches the typescript compiler (which pointedly considers runtime type information out of scope) with its own type compiler that emits a bespoke bytecode that is executed in a bespoke VM to communicate runtime type information to both server and client as needed. https://docs.deepkit.io/english/runtime-types.html

And from that baseline, there are very cool things you can do like an ORM entirely based on type annotations https://docs.deepkit.io/english/database.html or strongly-typed RPCs https://docs.deepkit.io/english/rpc.html .

It's very much in the alpha stage, but it's really well thought out - there's a tremendous degree of care the developer is taking towards code cleanliness and developer experience. I'm torn between wishing this project to have a fully funded team and take the world by storm, vs. "letting them cook" so to speak and seeing the developer experience unfold organically. Either way, it's a breath of fresh air into the Typescript ecosystem!

Deepkit (listed in the article) is a fascinating project and really deserves to be more popular.

It also demonstrates that what is being asked for is actually practical.

https://deepkit.io/

Checkout deepkit One of the things it has is a really fast BSON parser, that is faster than the JSON one to my understanding. Interesting work with TS types too

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Take a look at restfuncs then. Or deepkit or telefunc.

Both work out of the box very well with Deepkit. You can either construct your own types in runtime or mix TS types with runtime information. See for example https://github.com/deepkit/deepkit-framework/blob/master/packages/framework/src/crud.ts where this is done

Yes, you can directly use the interfaces and types as is with Deepkit (https://deepkit.io) and the library deepkit-openapi. You get also full route documentation if you use the deepkit/http router where you can use interfaces and type aliases plus validation thpes for route parameters (query parameters, body, etc). It still in alpha, but approaches soon beta.

https://deepkit.io/ may be of interest to you! It deeply patches the TS type compiler to make all types visible at runtime, enabling a lot of annotation-style workflows and dependency injection possible completely within the type annotation system: https://docs.deepkit.io/english/runtime-types.html

Previous discussion: https://news.ycombinator.com/item?id=31663298 - it's downright mindblowing that all this seems to be the work of primarily a single developer.

For a less intrusive solution, https://github.com/jquense/yup is a great library to reach for whenever you're defining the shape of a network-transmitted object and don't want to introduce compilation stages.

It's got type annotations and mypy has a discussion about it here as well: https://github.com/python/mypy/issues/1282

There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.

And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.

And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.

[0] https://nuitka.net/

[1] https://github.com/python/mypy/tree/master/mypyc

In Python there is MyPy that can help with this. https://www.mypy-lang.org/

It's funny you should say this.

Reading this article prompted me to future-proof a program I maintain for fun that deals with time; it had one use of utcnow, which I fixed.

And then I tripped over a runtime type problem in an unrelated area of the code, despite the code being green under "mypy --strict". (and "100% coverage" from tests, except this particular exception only occured in a "# pragma: no-cover" codepath so it wasn't actually covered)

It turns out that because of some core decisions about how datetime objects work, `datetime.date.today() < datetime.datetime.now()` type-checks but gives a TypeError at runtime. Oops. (cause discussed at length in https://github.com/python/mypy/issues/9015 but without action for 3 years)

One solution is apparently to use `datetype` for type annotations (while continuing to use `datetime` objects at runtime): https://github.com/glyph/DateType

PEP 695 is great. I've been using mypy every day at work in last couple years or so with very strict parameters (no any type etc) and I have experience writing real life programs with Rust, Agda, and some Haskell before, so I'm familiar with strict type systems. I'm sure many will disagree with me but these are my very honest opinions as a professional who uses Python types every day:

* Some types are better than no types. I love Python types, and I consider them required. Even if they're not type-checked they're better than no types. If they're type-checked it's even better. If things are typed properly (no any etc) and type-checked that's even better. And so on...

* Having said this, Python's type system as checked by mypy feels like a toy type system. It's very easy to fool it, and you need to be careful so that type-checking actually fails badly formed programs.

* The biggest issue I face are exceptions. Community discussed this many times [1] [2] and the overall consensus is to not check exceptions. I personally disagree as if you have a Python program that's meticulously typed and type-checked exceptions still cause bad states and since Python code uses exceptions liberally, it's pretty easy to accidentally go to a bad state. E.g. in the linked github issue JukkaL (developer) claims checking things like "KeyError" will create too many false positives, I strongly disagree. If a function can realistically raise a "KeyError" the program should be properly written to accept this at some level otherwise something that returns type T but 0.01% of the time raises "KeyError" should actually be typed "Raises[T, KeyError]".

* PEP 695 will help because typing things particularly is very helpful. Often you want to pass bunch of Ts around but since this is impractical some devs resort to passing "dict[str, Any]"s around and thus things type-check but you still get "KeyError" left and right. It's better to have "SomeStructure[T]" types with "T" as your custom data type (whether dataclass, or pydantic, or traditional class) so that type system has more opportunities to reject bad programs.

* Overall, I'm personally very optimistic about the future of types in Python!

[1] https://github.com/python/mypy/issues/1773

# is fixed: https://github.com/python/mypy/issues/12987.

You probably already know but you can add type hints and then check for consistency with https://github.com/python/mypy in python.

Modern Python with things like https://learnpython.com/blog/python-match-case-statement/ + mypy + Ruff for linting https://github.com/astral-sh/ruff can get pretty good results.

I found typed dataclasses (https://docs.python.org/3/library/dataclasses.html) in python using mypy to give me really high confidence when building data representations.