aufdenkampe
commented
11 months ago @sjordan29, if this enables us to more easily leverage Dask, then it may be connected to
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That said, there really does appear to be substantially less development activity at https://github.com/pydata/sparse compared to https://github.com/scipy/scipy, especially given that scipy v1.11 introduced "A new public base class scipy.sparse.sparray was introduced, allowing further extension of the sparse array API.". See https://docs.scipy.org/doc/scipy/release/1.11.0-notes.html#scipy-sparse-improvements
Given that Dask implements numpy.ndarray under the hood, then it may be that Dask would work perfectly well with the new scipy.sparse.sparray.
This person is wondering the same thing: https://dask.discourse.group/t/confused-about-working-with-sparse-arrays/1762
It appears that the PyData/sparse library more natively integrates with Xarray and Dask than the scipy.sparce subpackage, because it was designed from the ground up to natively use arrays instead of matrices. See:
It's possible that this is being solved by the recent refactoring of scipy.sparce, but Xarray and Dask are already integrated with PyData/sparse.
It might be worth exploring if migrating to PyData/sparse would provide any benefits to performance or code simplicity.
On the other hand, development doesn't appear very active, so it's possible that momentum has shifted away from this effort. See: https://sparse.pydata.org/en/stable/changelog.html