Roadmap: Next milestone for numpy-quaddtype (post v1.0.0)

[SwayamInSync]

For the next iteration we can focus on upgrading the dtype API at NumPy and other performance related issues. Listing down some known ones to track progress.

Dtype API upgrades (requires changes at NumPy)

• string parsing of user-defined dtypes
  • Tracking Issues: ENH: add a hook to the DType API for parsing dtype strings numpy#30699
  • PR:
• Exposing hook for np.dot support for user-defined dtypes
  • Tracking Issue:
  • PR:
• Paths depending on copyswap or copyswapn leading to segfault
  • Tracking Issue: segfault: QuadPrecision(1).byteswap() #13 , np.place segfaults for quaddtype #7 ,
  • PR:
• Using string form in array printing for user-defined dtypes
  • Tracking Issue: QuadPrec scalar repr isn't ideal for display in arrays #29
  • PR:
  • Extra context: Subclassing dtype to the native dtype (like quaddtype < np.floating) seems to give good formatting but not upto the entire precision, that has to be explicitly set via np.printoptions(...) which might not be ideal as we want the printed output to be in native precision (or any other properties) of the dtype by default

Updates/Fixes in numpy-quaddtype

• Supporting WASM build
  • PR: BUILD: Add Pyodide CI and build recipes #66
• casting to quaddtype emits uneccesary warnings
  • Tracking Issues: casting to quaddtype emits uneccesary warnings #25
  • PR:

[SwayamInSync]

I think we can create separate tracking issues for the numpy API fixes in numpy repo and initiate some forward discussion on each and the potential fixes, so that contributors from both numpy and user-dtypes side can come forward as per the interests.

cc: @ngoldbaum @seberg

[ngoldbaum]

Please do open numpy issues for improvements for the user dtype system.