Writing NetCDF file fails with ValueError

[tylere]

Using Xee to write a netCDF file may yield the following error:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-7-0bc080b1dc4b>](https://localhost:8080/#) in <cell line: 1>()
----> 1 ds.to_netcdf("out.nc")

7 frames
[/usr/local/lib/python3.10/dist-packages/xarray/core/dataset.py](https://localhost:8080/#) in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute, invalid_netcdf, auto_complex)
   2344         from xarray.backends.api import to_netcdf
   2345 
-> 2346         return to_netcdf(  # type: ignore[return-value]  # mypy cannot resolve the overloads:(
   2347             self,
   2348             path,

[/usr/local/lib/python3.10/dist-packages/xarray/backends/api.py](https://localhost:8080/#) in to_netcdf(dataset, path_or_file, mode, format, group, engine, encoding, unlimited_dims, compute, multifile, invalid_netcdf, auto_complex)
   1870         # TODO: allow this work (setting up the file for writing array data)
   1871         # to be parallelized with dask
-> 1872         dump_to_store(
   1873             dataset, store, writer, encoding=encoding, unlimited_dims=unlimited_dims
   1874         )

[/usr/local/lib/python3.10/dist-packages/xarray/backends/api.py](https://localhost:8080/#) in dump_to_store(dataset, store, writer, encoder, encoding, unlimited_dims)
   1917         variables, attrs = encoder(variables, attrs)
   1918 
-> 1919     store.store(variables, attrs, check_encoding, writer, unlimited_dims=unlimited_dims)
   1920 
   1921 

[/usr/local/lib/python3.10/dist-packages/xarray/backends/common.py](https://localhost:8080/#) in store(self, variables, attributes, check_encoding_set, writer, unlimited_dims)
    373         variables, attributes = self.encode(variables, attributes)
    374 
--> 375         self.set_attributes(attributes)
    376         self.set_dimensions(variables, unlimited_dims=unlimited_dims)
    377         self.set_variables(

[/usr/local/lib/python3.10/dist-packages/xarray/backends/common.py](https://localhost:8080/#) in set_attributes(self, attributes)
    390         """
    391         for k, v in attributes.items():
--> 392             self.set_attribute(k, v)
    393 
    394     def set_variables(self, variables, check_encoding_set, writer, unlimited_dims=None):

[/usr/local/lib/python3.10/dist-packages/xarray/backends/scipy_.py](https://localhost:8080/#) in set_attribute(self, key, value)
    226     def set_attribute(self, key, value):
    227         self._validate_attr_key(key)
--> 228         value = encode_nc3_attr_value(value)
    229         setattr(self.ds, key, value)
    230 

[/usr/local/lib/python3.10/dist-packages/xarray/backends/netcdf3.py](https://localhost:8080/#) in encode_nc3_attr_value(value)
     94         value = value.encode(STRING_ENCODING)
     95     else:
---> 96         value = coerce_nc3_dtype(np.atleast_1d(value))
     97         if value.ndim > 1:
     98             raise ValueError("netCDF attributes must be 1-dimensional")

[/usr/local/lib/python3.10/dist-packages/xarray/backends/netcdf3.py](https://localhost:8080/#) in coerce_nc3_dtype(arr)
     81         cast_arr = arr.astype(new_dtype)
     82         if not (cast_arr == arr).all():
---> 83             raise ValueError(
     84                 COERCION_VALUE_ERROR.format(dtype=dtype, new_dtype=new_dtype)
     85             )

ValueError: could not safely cast array from int64 to int32. While it is not always the case, a common reason for this is that xarray has deemed it safest to encode np.datetime64[ns] or np.timedelta64[ns] values with int64 values representing units of 'nanoseconds'. This is either due to the fact that the times are known to require nanosecond precision for an accurate round trip, or that the times are unknown prior to writing due to being contained in a chunked array. Ways to work around this are either to use a backend that supports writing int64 values, or to manually specify the encoding['units'] and encoding['dtype'] (e.g. 'seconds since 1970-01-01' and np.dtype('int32')) on the time variable(s) such that the times can be serialized in a netCDF3 file (note that depending on the situation, however, this latter option may result in an inaccurate round trip).

This can be resolved by installing the netCDF4 Python package, which is not available by default in Google Colab.

!pip install netCDF4

Notebook demonstrating the error and workaround:
https://colab.research.google.com/gist/tylere/798f73d6ebfb0eb92bb92bb79a6ae390/netcdf-file-writing-issue.ipynb

[tylere]

Idea: Add this information to a troubleshooting section of the Xee docs.