Add partial generic support in pyfunctions

Hi,

I am currently developing a crate that export a generic function that is meant to be configured by users at compile time before being exported to python. This looks like this:

trait Config {
    const KEY: [u8; 32];
}

pub fn encrypt<C: Config>(data: &[u8]) -> Vec<u8> {
    // use C::KEY here to encrypt the data  
}

Then the user of that crate would export that function in their python module using wrap_pyfunction! macro.

Currently, this is not possible. I have to export a declarative macro that will construct that function in the user's module, so that it can avoid the generic and use C directly.

Would you accept a PR that will modify the pyfunction proc macro and the wrap_pyfunction! declarative macro to support generics, where the user has to define the name + all the generics of the function in the wrap_pyfunction macro if the function is generic?

This would look like that:

trait Config {
    const KEY: [u8; 32];
}

#[pyfunction]
pub fn encrypt<C: Config>(data: &[u8]) -> Vec<u8> {
    // use C::KEY here to encrypt the data  
}

// -- in user crate --

struct Conf;

impl Config for Conf {
    const KEY: [u8; 32] = [0; 32];
}

#[pymodule]
fn module(m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_function(wrap_pyfunction!("encrypt", encrypt, Conf)?)
}

(The exact syntax can be changed)

Start with the pyfunction proc macro and wrap_pyfunction! declarative macro named in the issue, then trace how a function is converted and registered. Done means a generic #[pyfunction] can be registered with the function name and concrete generic arguments, with the accepted syntax settled.