issue_comments: 1005916151

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https://github.com/pydata/xarray/issues/2368#issuecomment-1005916151 https://api.github.com/repos/pydata/xarray/issues/2368 1005916151 IC_kwDOAMm_X8479Q_3 35968931 2022-01-05T17:14:35Z 2022-01-05T17:14:35Z MEMBER

Currently, xarray requires that variables with a name matching a dimension are 1D variables along that dimension, e.g.,

python for dim in dataset.dims: if dim in dataset.variables: assert dataset.variables[dim].dims == (dim,)

I agree that this unnecessarily complicates our data model. There's no particular advantage to this invariant, besides removing the need to check the dimensions of variables used for indexing lookups. I'm sure there are some cases internally where we currently rely on this assumption, but it should be relatively easy to relax.

It seems like this relaxation is compatible with the refactoring of indexes.

@benbovy will the explicit indexes refactor fix this case?

This is mentioned elsewhere (can't find the issue right now) and may be out of scope for this issue but I'm going to say it anyway: opening a NetCDF file with groups was not as easy as I wanted it to be when first starting out with xarray.

@djhoese For anything to do with opening netCDF files with groups see #4118 and the linked issues from there.

If people have example of other weird cases involving groups (like groups within themselves or anything like that) then I would be interested to have those files to test with!

 
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