I personally ran into this issue while working on StringDType back when it
was still a prototype outside the NumPy repo. I wanted to add support for
casting to and from all of the built-in datatypes. But to cast to and from
float16, I had to link against libnpymath. This added a bunch of build
complexity for something that works out of the box for all the other DTypes.

In that case I didn’t care about speed so much as feature-completeness.

On Mon, Nov 24, 2025 at 11:37 AM Amelia Thurdekoos <
[email protected]> wrote:

>
> ...could we at least try to use the bit width in the name such as float16
>> as much as possible?
>
>
>  This is all excellent feedback, thank you! I agree, more explicit is
> better. Planning as best as we can with an eye to future clarity, seems
> reasonable.
>
>
>> The important part here seems to be pushing the goal of getting rid of
>> npy_math, what is the plan for the rest of it here?  Just getting rid
>> of it completely because it is obsolete?
>
>
>
> If we introduce this now users will adopt it in 2-3 years (old NumPy
>> versions don't have it).
>> Now there is no guarantee that e.g. `float16_t` will be generally
>> supported (it's optional anyway) but if the situation around half
>> improves just a little, I wonder if by the time this is useful it won't
>> already be completely obsolete, rather than just mostly.
>
>
> Thanks for the feedback Sebastian! I agree, the overarching goal is
> removing npy_math. This proposal's scope is intentionally limited to the
> float16/halffloat part as one self-contained step in that direction, rather
> than trying to solve the whole npy_math feature at once. I am not going to
> be removing any part of the library as part of this effort.
>
> If float16 improves enough that this API becomes obsolete, or even less
> attractive, this effort still yields a net positive. It will assist with
> reducing the need to link against npy_math.
>
> - Amelia
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