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/3232#issuecomment-1183301651,https://api.github.com/repos/pydata/xarray/issues/3232,1183301651,IC_kwDOAMm_X85Gh8AT,2448579,2022-07-13T14:31:55Z,2022-07-13T14:32:01Z,MEMBER,"> I'd be happy to turn this into a PR with some tests.

Absolutely!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,482543307
https://github.com/pydata/xarray/issues/3232#issuecomment-606228143,https://api.github.com/repos/pydata/xarray/issues/3232,606228143,MDEyOklzc3VlQ29tbWVudDYwNjIyODE0Mw==,2448579,2020-03-30T20:24:08Z,2020-03-30T20:24:08Z,MEMBER,"Just chiming in quickly. I think there's definitely interest in doing this through NEP-18.

It looks like CUDA has implemented `__array_function__` (https://docs-cupy.chainer.org/en/stable/reference/interoperability.html) so many things may ""just work"". There was some work earlier on plugging in `pydata/sparse`, and there is some ongoing work to plug in `pint`. With both these efforts, a lot of xarray's code should be ""backend-agnostic"" but its not perfect. 

Have you tried creating `DataArrays` with `cupy` arrays yet? I would just try things and see what works vs what doesn't.

Practically, our approach so far has been to add a number of xfailed tests (`test_sparse.py` and `test_units.py`) and slowly start fixing them. So that's one way to proceed if you're up for it.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,482543307