issue_comments: 386721846

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.