issue_comments: 473496064

@shoyer do you mean that we consider that by default when we deal with Python's int and float we cast them to np.int64 and np.float64 ?

Currently we cast to int32/float64 for netCDF3 files (which don't support int64) and int64/float64 for netCDF4 files.

That default behavior doesn't really make sense if the user provided builtin Python numbers for these attributes.

For example, if I write something like the following, the data for x should probably decode to float32: python ds = xarray.Dataset({'x': np.float32(0)}) encoding = {'x': {'scale_factor': 1, 'add_offset': 1, 'dtype': 'int8'}} ds.to_netcdf('test.nc', encoding=encoding) With the current implementation in this PR, I think the data will come back as float64.

To get something that will decode as float64 without the original data being float64, the user should need to intentionally choose dtypes for scale_factor and add_offsert, e.g., python ds = xarray.Dataset({'x': np.float32(0)}) encoding = {'x': {'scale_factor': np.float64(1), 'add_offset': np.float64(1), 'dtype': 'int8'}} ds.to_netcdf('test.nc', encoding=encoding)

Does this make sense to you? From my perspective, two goals for this change should be: 1. Adhere to CF conventions for deciding how to decode data from disk. 2. Provide a consistent interface for xarray users, so that by default data is restored in the same form that it was written.