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/1699#issuecomment-609650053,https://api.github.com/repos/pydata/xarray/issues/1699,609650053,MDEyOklzc3VlQ29tbWVudDYwOTY1MDA1Mw==,6213168,2020-04-06T08:26:13Z,2020-04-06T08:26:13Z,MEMBER,still relevant,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,272004812
https://github.com/pydata/xarray/issues/1699#issuecomment-386721846,https://api.github.com/repos/pydata/xarray/issues/1699,386721846,MDEyOklzc3VlQ29tbWVudDM4NjcyMTg0Ng==,6213168,2018-05-04T20:18:48Z,2018-05-04T20:21:10Z,MEMBER,"The key thing is that for most people it would be extremely elegant and practical to be able to duck-type wrappers around numpy, scipy, and numba kernels that automagically work with Variable, DataArray, and Dataset (see my example above).
You'll agree on how ugly my 1-liner above would become:
```
def myfunc(x):
    if isinstance(x, xarray.Dataset):
        dtype = x.dtypes
    else:  # DataArray and Variable
        dtype = x.dtype
    return apply_ufunc(numpy_kernel, x, dask='parallelized', output_dtypes=[dtype])
```
If you don't like ``Dataset.dtype``, then maybe we could add both ``Dataset.dtypes`` and ``DataArray.dtypes`` (which would be just an alias to ``DataArray.dtype``)? I still like the former more though - I find it less confusing.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,272004812
https://github.com/pydata/xarray/issues/1699#issuecomment-384073275,https://api.github.com/repos/pydata/xarray/issues/1699,384073275,MDEyOklzc3VlQ29tbWVudDM4NDA3MzI3NQ==,6213168,2018-04-24T20:42:57Z,2018-04-24T20:42:57Z,MEMBER,"@shoyer that seems counter-intuitive for me - you are returning two datasets after all.
If we go with the ``list(dict)`` notation, we could also add a ``Dataset.dtype`` property, which (coherently with dims and chunks) would return a dict. This would be very handy as, in 99% of the times, people will want to write:
```
def myfunc(x):
    return apply_ufunc(numpy_kernel, x, dask='parallelized', output_dtypes=[x.dtype])
```
which would magically work both when x is a DataArray and when it's a Dataset
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,272004812