issue_comments: 289916013

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https://github.com/pydata/xarray/issues/1092#issuecomment-289916013 https://api.github.com/repos/pydata/xarray/issues/1092 289916013 MDEyOklzc3VlQ29tbWVudDI4OTkxNjAxMw== 23484003 2017-03-28T21:51:30Z 2017-03-28T21:51:30Z NONE

One important reason to keep the tree-like structure within a dataset is that it provides some assurance to the recipient of the dataset that all the variables 'belong' in the same coordinate space. Constructing a tree (from a nested dictionary, say) whose leaves are datasets or dataArrays doesn't guarantee that the coordinates/dimensions in all the leaves are compatible, whereas a tree within the dataset does make a guarantee about the leaves.

As far as motivation for making trees, I find myself with several dozen variable names such as ds.fluxPoloidalPerturbation and ds.fieldToroidalBackground and various permutations, so it would be logical to be able to write ds.flux.poloidal and get a sub-dataset that contains dataArrays named perturbation and background.

As far as implementation, the DataGroup could really just be syntactic sugar around a flat dataset that is hidden from the user, and has keys like 'flux.poloidal.perturbed,' so that dg.flux.poloidal.perturbed would be an alias to dg.__hiddenDataset__['flux.poloidal.perturbed'], and dg.flux.poloidal would be an alias to dg.__hiddenDataset__[['flux.poloidal.perturbed','flux.poloidal.background']]. Seems like it would require mucking with dg.__getattr__, dg.__setattr__, and dg.__dir__ at a minimum to get it off the ground, but by making the tree virtual, one avoids the difficulties with slicing, etc. The return type of dg.__getattr__ should be another DataGroup as long as there are branches in the output, but it should fall back to a Dataset when there are only leaves.

 
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