issue_comments: 472129555

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https://github.com/pydata/xarray/issues/2807#issuecomment-472129555 https://api.github.com/repos/pydata/xarray/issues/2807 472129555 MDEyOklzc3VlQ29tbWVudDQ3MjEyOTU1NQ== 1217238 2019-03-12T18:37:03Z 2019-03-12T18:37:03Z MEMBER

In the first version of apply_ufunc, I experimented with applying functions that take and return xarray objects.

The challenge is that with dask's lazy evaluation, we don't know the structure of the returned objects until after evaluating the wrapped functions. So we can't rebuild xarray objects unless we require redundantly specify all the coordinates and attributes from the return values.

The alternative would be to make a parallel but eagerly evaluated version of apply_ufunc, e.g., by calling compute on each chunk and then reassembling the result (e.g., ttps://github.com/pydata/xarray/pull/2616). The downside is that this will load your data into memory, but maybe that's acceptable for your purposes.

 
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