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

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: https://github.com/numpy/numpy/issues/30699
  • PR:
• Exposing hook for np.dot & fixing np.einsum support for user-defined dtypes
  • Tracking Issue: https://github.com/numpy/numpy/issues/30793
  • PR:
• Paths depending on copyswap or copyswapn leading to segfault
  • Tracking Issue: #13 , #7 , https://github.com/numpy/numpy/issues/24859
  • PR:
• Using string form in array printing for user-defined dtypes
  • Tracking Issue: #29 , https://github.com/numpy/numpy/issues/30796
  • 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
• Allowing np.linalg submodule to allow user-defined dtypes routine registration
  • Tracking Issue:
  • PR:

Updates/Fixes in numpy-quaddtype

• Supporting WASM build
  • PR: #66
• casting to quaddtype emits uneccesary warnings
  • Tracking Issues: #25
  • PR:

Start with the checklist in issue #68 and review the linked NumPy tracking issues for the dtype API items, along with PR #66 for the WASM build. No project files or tests are named, so first identify which single checkbox has a defined scope and acceptance criteria; done should be represented by the corresponding completed checklist item and linked PR.