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/4241#issuecomment-661847133,https://api.github.com/repos/pydata/xarray/issues/4241,661847133,MDEyOklzc3VlQ29tbWVudDY2MTg0NzEzMw==,14808389,2020-07-21T13:02:20Z,2020-07-21T13:03:52Z,MEMBER,"> cannot be done by just using numpy-like functions

did you look at [apply_ufunc](https://xarray.pydata.org/en/stable/generated/xarray.apply_ufunc.html#xarray.apply_ufunc) ([examples](https://xarray.pydata.org/en/stable/examples/apply_ufunc_vectorize_1d.html)) and [map_blocks](https://xarray.pydata.org/en/stable/generated/xarray.map_blocks.html#xarray.map_blocks)? Functions applied with `apply_ufunc` will receive whatever was wrapped by `dask` while `map_blocks` allows you to work with xarray objects. See also the [docs](https://xarray.pydata.org/en/stable/dask.html#automatic-parallelization-with-apply-ufunc-and-map-blocks).
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