Hi all, I am a long time user of astropy.units, which allows one to define quantities with physical units as follows:
>>> from astropy import units as u >>> 10 << u.cm <Quantity 10. cm> >>> np.sqrt(4 << u.m ** 2) <Quantity 2. m> >>> ([1, 1, 0] << u.m) @ ([0, 10, 20] << u.cm / u.s) <Quantity 10. cm m / s> >>> (([1, 1, 0] << u.m) * ([0, 10, 20] << u.cm / u.s)).to(u.m ** 2 / u.s) <Quantity [0. , 0.1, 0. ] m2 / s> The mechanism works by subclassing numpy.ndarray and leveraging __array_function__ support aka NEP 18. Internally it is something like this: >>> v = np.array(10, dtype=np.float64, copy=False, order=None, subok=True, ndmin=0) >>> vu = v.view(u.Quantity) >>> vu._set_unit(u.cm) >>> vu <Quantity 10. cm> However, over the years I have been constantly annoyed by the fact that it is tremendously slow. I'm not critizing Astropy devs, the problem seems objectively difficult: although some code paths could be optimized at the cost of losing some syntactic sugar or breaking backwards compatibility, `isinstance` calls and introspection in general are slow. Setting aside the question of trying to make astropy.units faster (which may or may not be possible), I was thinking how feasible could it be to implement something similar, but using a compiled language instead (C, Cython, Rust, whatever) and leveraging "modern" dispatch mechanisms. But after reading about NEP 18, NEP 47, uarray, and various pull requests and issues here and there (https://labs.quansight.org/blog/2021/11/pydata-extensibility-vision/ and https://github.com/scipy/scipy/issues/10204#issuecomment-787067947 among others) I don't fully grasp the differences between the approaches, and I don't know if what I am proposing is feasible at all. Since IIUC the numpy function or ufunc is passed to __array_function__ and __array_ufunc__ respectively, I am not sure how would that interact with the code being in a foreign language (I assume the NumPy C API would have to be used). If folks have advice, ideas, or suggestions for a direction, I'll be happy to read them. Best!
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