issue_comments: 290224441

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https://github.com/pydata/xarray/issues/1092#issuecomment-290224441 https://api.github.com/repos/pydata/xarray/issues/1092 290224441 MDEyOklzc3VlQ29tbWVudDI5MDIyNDQ0MQ== 23484003 2017-03-29T21:00:42Z 2017-03-29T21:04:08Z NONE

@shoyer I see your point about the string manipulation. On the other hand, this is exactly how h5py and netCDF4-python implement the group/subgroup access syntax: just like a filepath.

I'm also having thoughts about the attribute access: if ds['flux']['poloidal'] = subset does not work, then neither does ds.flux.poloidal = subset, correct? If so, it is almost pointless to have the attribute access in the first place. I suppose that is the price to pay for merely making it appear as though there is attribute-access.

For my own understanding, I tried to translate between xarray and netCDF4-python : - nc.Variable <--> xr.Variable - nc.????? <--> xr.DataArray (netCDF doesn't distinguish vars/coords, so no analog is possible) - nc.Group <--> xr.NestableDataset - nc.Dataset <--> xr.NestableDataset

From netCDF4-python

Groups define a hierarchical namespace within a netCDF file. They are analogous to directories in a unix filesystem. Each Group behaves like a Dataset within a Dataset, and can contain it's own variables, dimensions and attributes (and other Groups). Group inherits from Dataset, so all the Dataset class methods and variables are available to a Group instance (except the close method).

It appears that the only things special about a nc.Dataset as compared to an nc.Group are: 1. The file access is tied to the nc.Dataset. 2. The nc.Dataset group has children but no parent.

A big difference between xarray and netCDF4-python datasets is that the children datasets in xarray can go have a life of their own, independent of their parent & the file it represents. It makes sense to me to have just a single xarray type (modified version of xarray.Dataset) to deal with both of these cases.

The nc.Group instances have an attribute groups that lists all the subgroups. So one option I suppose would be to follow that route and actually have Datasets that contain other datasets alongside everything else.

As an aside, it seems that ragged arrays are now supported in netCDF4-python:VLen.

 
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