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https://github.com/pydata/xarray/issues/4118#issuecomment-1042660100 https://api.github.com/repos/pydata/xarray/issues/4118 1042660100 IC_kwDOAMm_X84-JbsE 1217238 2022-02-17T07:45:24Z 2022-02-17T07:45:24Z MEMBER

One thing that came up in our discussion about this in the developer meeting today is that we could also pretty easily expose a "low level" API for IO using dictionaries of xarray.Variable objects. This intermediate representation could be useful for cleaning up data into a form suitable for conversion into Dataset objects.

On Wed, Feb 16, 2022 at 11:39 PM Alessandro Amici @.***> wrote:

@TomNicholas https://github.com/TomNicholas (cc @mraspaud https://github.com/mraspaud)

Do you have use cases which one of these designs could handle but the other couldn't?

The two main classes of on-disk formats that, I know of, which cannot be always represented in the "group is a Dataset" approach are:

  • in netCDF following the CF conventions for groups https://cfconventions.org/Data/cf-conventions/cf-conventions-1.9/cf-conventions.html#groups, it is legal for an array to refer to a dimension or a coordinate in a different group and so arrays in the same group may have dimensions with the same name, but different size / coordinate values,
  • the current spec for the Next-generation file formats (NGFF) https://ngff.openmicroscopy.org for bio-imaging has all scales of the same 5D data in the same group.

I don't have an example at hand, but my impression is that satellite products that use HDF5 file format also place arrays with inconsistent dimensions / coordinates in the same group.

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