Type inference in the style of Py14

[MaD70]

Hello,

Interesting project! While skimming your documentation, I came across this section in Type hints:

You must use Python-style type hints everywhere. I.e., for variable definitions, function parameters, class data members, and return types.

This reminded me of another Python-to-C++ (14) transpiler, Py14 (the project was archived in 2018), where this restriction is lifted via type inference. In practice, this means introducing type variables through C++ templates and using the auto keyword (and decltype also).

Here's an example from the project README to illustrate how this is implemented:

Example

Original Python version:

def factorial(num):
    if num <= 1:
        return num
    return factorial(num - 1) * num

Transpiled C++ template:

template <typename T1> auto factorial(T1 num) {
    if (num <= 1) {
        return num;
    }
    return factorial(num - 1) * num;
}

While I find an explicitly typed version of the code clearer, it might be interesting to support transpilation of code without type annotations as well—both to speed up the porting of existing Python programs and to enable rapid prototyping. This could complement your plan to introduce type variables, if you haven’t already implemented it.

P.S.: I came across this after reading the thread on r/Compilers on Reddit (I don’t have an account), and I find the naysayers’ comments rather discouraging—they completely missed the potential of this project. Honestly, some of the remarks also seemed quite lacking in technical understanding. If I may, I’d encourage you not to let that discourage you.

P.P.S.: this isn’t really a feature request (which is why I didn’t add that label); it’s more of a suggestion to take a look at that abandoned project and, if appropriate, draw some inspiration from it.

[curtispuetz]

Hello,

Thanks for the feedback, that's very helpful. I wish I had seen this earlier, but unfortunately, I seemed to miss the notification!

You are right, we could do some type inference, but I think there are so many more features like multi-threading and default parameters that are higher priority. So, maybe we can do type inference later.

By the way, you can also use auto in Py++, and it works just like it does in C++. For example: c: auto = defaultdict[int, float](float). So, supporting type inference would just mean giving people the option to omit the : auto.

P.S.: I have put the project on hold while I try to stabilize my finances by creating a video game. I hope I can come back to this Py++ project later because it's probably my favourite project I've ever worked on in my life. I mentioned this halt on the project's X.com page (https://x.com/pypp_main), and if there are any other updates about the project later, I will put them there too.