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  • Boolean confusion · 3 ✖
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832454582 https://github.com/pydata/xarray/issues/5254#issuecomment-832454582 https://api.github.com/repos/pydata/xarray/issues/5254 MDEyOklzc3VlQ29tbWVudDgzMjQ1NDU4Mg== DerWeh 22542812 2021-05-05T06:48:46Z 2021-05-05T06:48:46Z NONE

@mathause Indeed, I am using engine="h5netcdf", invalid_netcdf=True.

I would also agree on the point that expanding the isinstance is not the best solution. Duck typing makes reliable instance checks quite painful.

 
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   Boolean confusion 874695249
832253672 https://github.com/pydata/xarray/issues/5254#issuecomment-832253672 https://api.github.com/repos/pydata/xarray/issues/5254 MDEyOklzc3VlQ29tbWVudDgzMjI1MzY3Mg== shoyer 1217238 2021-05-04T21:14:48Z 2021-05-04T21:14:48Z MEMBER

:(

I really wish NumPy didn't have np.bool_ at all. The separate scalar number system is a huge pain.

Rather than expanding isinstance checks, I would prefer to fix this by adding a "normalization" step earlier in the process to ensure that we only have Native Python scalars in attributes.

 
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   Boolean confusion 874695249
832239085 https://github.com/pydata/xarray/issues/5254#issuecomment-832239085 https://api.github.com/repos/pydata/xarray/issues/5254 MDEyOklzc3VlQ29tbWVudDgzMjIzOTA4NQ== mathause 10194086 2021-05-04T20:55:19Z 2021-05-04T20:55:19Z MEMBER

For completeness, here is the error of the second case:

```python-traceback TypeError Traceback (most recent call last) <ipython-input-5-41afac9c294c> in <module> 1 data = xr.Dataset() 2 data.attrs['bool_type'] = np.True_ ----> 3 data.to_netcdf() ~/code/xarray/xarray/core/dataset.py in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute, invalid_netcdf) 1782 from ..backends.api import to_netcdf 1783 -> 1784 return to_netcdf( 1785 self, 1786 path, ~/code/xarray/xarray/backends/api.py in to_netcdf(dataset, path_or_file, mode, format, group, engine, encoding, unlimited_dims, compute, multifile, invalid_netcdf) 1033 # validate Dataset keys, DataArray names, and attr keys/values 1034 _validate_dataset_names(dataset) -> 1035 _validate_attrs(dataset, invalid_netcdf=invalid_netcdf and engine == "h5netcdf") 1036 1037 try: ~/code/xarray/xarray/backends/api.py in _validate_attrs(dataset, invalid_netcdf) 170 # Check attrs on the dataset itself 171 for k, v in dataset.attrs.items(): --> 172 check_attr(k, v, valid_types) 173 174 # Check attrs on each variable within the dataset ~/code/xarray/xarray/backends/api.py in check_attr(name, value, valid_types) 162 163 if not isinstance(value, valid_types): --> 164 raise TypeError( 165 f"Invalid value for attr {name!r}: {value!r}. For serialization to " 166 "netCDF files, its value must be of one of the following types: " TypeError: Invalid value for attr 'bool_type': True. For serialization to netCDF files, its value must be of one of the following types: str, Number, ndarray, number, list, tuple ```

Can you give some more details. The only way I managed to see the round-trip effect you describe is using engine="h5netcdf", invalid_netcdf=True - is that the combination you are using? For all other combinations it returned 1 (netcdf3) or an error (netcdf4). 

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   Boolean confusion 874695249

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