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  • fujiisoup · 1 ✖

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  • Hooks for XArray operations · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
368004970 https://github.com/pydata/xarray/issues/1938#issuecomment-368004970 https://api.github.com/repos/pydata/xarray/issues/1938 MDEyOklzc3VlQ29tbWVudDM2ODAwNDk3MA== fujiisoup 6815844 2018-02-23T13:10:30Z 2018-02-23T13:10:30Z MEMBER

Thanks for leading the development of sparse. I'm looking forward to see it in xarray:)

Currently, our logic to support dask.array and numpy.ndarray is hard-coded everywhere. For example, we have many computation paths for nansum, dask.Array, np.ndarray with bottleneck, bare np.ndarray and we use our in-house implementation for object-type arrays. The easiest way to support sparse might be to add a specific path for sparse by hard-coding again, but it is less flexible.

Do we need to be capable of supporting other objects for future extension? If so, we may need to start from (heavy) refactoring.

@shoyer, Could you give any suggestion? I am personally interested in helping this, but I may need to decide the direction first.

 
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