html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/1938#issuecomment-368004970,https://api.github.com/repos/pydata/xarray/issues/1938,368004970,MDEyOklzc3VlQ29tbWVudDM2ODAwNDk3MA==,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.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,299668148