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  • losing shallowness of ds.copy() on ds from xr.open_dataset · 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
577889198 https://github.com/pydata/xarray/issues/3718#issuecomment-577889198 https://api.github.com/repos/pydata/xarray/issues/3718 MDEyOklzc3VlQ29tbWVudDU3Nzg4OTE5OA== keewis 14808389 2020-01-23T21:39:04Z 2020-01-23T21:39:04Z MEMBER

I don't know too much about that area, but I believe that's because directly after reading a NetCDF file, you don't work with numpy arrays but with something different. Only once you call some form of np.array (such as np.asarray or np.asanyarray) on it, it becomes a numpy.ndarray.

I'm not sure if the behaviour you encountered is a bug (it probably is), but to fix your example for now, I think you should explicitly load() the dataset after opening it: python with xr.open_dataset('ds.nc').load() as ds: ds2 = ds.copy() print(f'ds.equals = {ds.equals(ds2)}') ds2[varname][0] = 11.0 print(f'ds.equals = {ds.equals(ds2)}')

 
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   losing shallowness of ds.copy() on ds from xr.open_dataset 554376164

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