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  • Performance degradation: `DataArray` with `dtype=object` of `DataArray` gets very slow indexing · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
260683252 https://github.com/pydata/xarray/issues/1121#issuecomment-260683252 https://api.github.com/repos/pydata/xarray/issues/1121 MDEyOklzc3VlQ29tbWVudDI2MDY4MzI1Mg== shoyer 1217238 2016-11-15T16:05:20Z 2016-11-15T16:05:20Z MEMBER

Nesting xarray objects was not an intended use case, but I agree, this is ridiculously slow.

Looks the culprit is xarray.core.utils.to_0d_object_array: https://github.com/pydata/xarray/blob/d66f673ab25fe0fc0483bd5d67479fc94a14e46d/xarray/core/utils.py#L198-L212

Specifically, when value is an xarray.DataArray, these lines appear to trigger a iterating over every element of the DataArray, one by one:

result = np.empty((1,), dtype=object) result[:] = [value]

I'm definitely open to fixes here. Creating a NumPy object array can be very fussy -- NumPy tries way too hard to coerce dtypes.

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  Performance degradation: `DataArray` with `dtype=object` of `DataArray` gets very slow indexing 189415576

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