issue_comments: 905472692

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https://github.com/pydata/xarray/issues/4118#issuecomment-905472692 https://api.github.com/repos/pydata/xarray/issues/4118 905472692 IC_kwDOAMm_X841-Gq0 35968931 2021-08-25T12:50:04Z 2021-08-25T13:02:10Z MEMBER

Thanks @benbovy !

For rich/html reprs, I think that we could take much inspiration from some of the dask reprs shown in this blog post.

I don't know much about HTML, but graphs where you can mouseover nodes to see node information sound awesome!

what is the rationale of having two separate classes DataTree and DataNode?

They aren't separate: DataNode is merely a (perhaps badly-named) pointer to a second init method for the same DataTree class.

The idea was that creating a single node of a tree by specifying only its (name, dataset, parent, children) attributes was conceptually different to "I have loads of datasets, and I want to arrange them all into one big tree using path-like addresses", so I made two different init methods on DataTree to cover that. The idea was from the xarray.Dataset._construct_direct() classmethod, which creates a new instance of a Dataset by directly setting attributes like (variables, coord_names, dims, attrs). That is an internal classmethod though, and isn't externally exposed like DataNode().

We could just merge the two signatures into one __init__ method though, or use a less confusing name (I just didn't want DataTree._init_single_node(name, data, parent) everywhere in my tests.) Also internally it's nice to have a separate ._init_single_node() method because that's (a) closer to the super().__init__() defined by TreeNode, and (b) doesn't require calling the fairly complex getting and setting methods.

Could those classes be merged somehow?

They were originally separate (I had DataTree and DatasetNode, where the former was a subclass of the latter), but then I merged them together in Condense DatasetNode and DataTree into a single DataTree class #11.

Zarr (abstract data store) has no such separate class and uses a regular zarr.hierarchy.Group as the root.

Good to know that other nested structures took a similar approach. I think that as we want to be able to save and load any subtree even after changing parents etc. then we ideally don't want to treat any one node as special.

 
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