issues: 2054280736

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
2054280736 I_kwDOAMm_X856cdYg 8572 Track merging datatree into xarray 35968931 open 0     27 2023-12-22T17:37:20Z 2024-05-02T19:44:29Z   MEMBER      

What is your issue?

Master issue to track progress of merging xarray-datatree into xarray main. Would close https://github.com/pydata/xarray/issues/4118 (and many similar issues), as well as one of the goals of our development roadmap.

Also see the project board for DataTree integration.

On calls in the last few dev meetings, we decided to forget about a temporary cross-repo from xarray import datatree (so this issue supercedes #7418), and just begin merging datatree into xarray main directly.

Weekly meeting

See https://github.com/pydata/xarray/issues/8747

Task list:

To happen in order:

  • [x] open_datatree in xarray. This doesn't need to be performant initially, and ~~it would initially return a datatree.DataTree object.~~ EDIT: We decided it should return an xarray.DataTree object, or even xarray.core.datatree.DataTree object. So we can start by just copying the basic version in datatree/io.py right now which just calls open_dataset many times. #8697
  • [x] Triage and fix issues: figure out which of the issues on xarray-contrib/datatree need to be fixed before the merge (if any).

  • [ ] Merge in code for DataTree class. I suggest we do this by making one PR for each module, and ideally discussing and merging each before opening a PR for the next module. (Open to other workflow suggestions though.) The main aim here being lowering the bus factor on the code, confirming high-level design decisions, and improving details of the implementation as it goes in.

    Suggested order of modules to merge: - [x] datatree/treenode.py - defines the tree structure, without any dimensions/data attached, #8757 - [x] datatree/datatree.py - adds data to the tree structure, #8789 - [x] datatree/iterators.py - iterates over a single tree in various ways, currently copied from anytree, #8879 - [x] datatree/mapping.py - implements map_over_subtree by iterating over N trees at once https://github.com/pydata/xarray/pull/8948, - [ ] datatree/ops.py - uses map_over_subtree to map methods like .mean over whole trees (https://github.com/pydata/xarray/pull/8976), - [x] datatree/formatting_html.py - HTML repr, works but could do with some optimization https://github.com/pydata/xarray/pull/8930, - [x] datatree/{extensions/common}.py - miscellaneous other features e.g. attribute-like access (#8967).

  • [ ] Expose datatree API publicly. Actually expose open_datatree and DataTree in xarray's public API as top-level imports. The full list of things to expose is:

  • [ ] open_datatree
  • [ ] DataTree
  • [ ] map_over_subtree
  • [ ] assert_isomorphic

  • [ ] register_datatree_accessor

  • [ ] Refactor class inheritance - Dataset/DataArray share some mixin classes (e.g. DataWithCoords), and we could probably refactor DataTree to use these too. This is low-priority but would reduce code duplication.

Can happen basically at any time or maybe in parallel with other efforts:

  • [ ] Generalize backends to support groups. Once a basic version of xr.open_datatree exists, we can start refactoring xarray's backend classes to support a general Backend.open_datatree method for any backend that can open multiple groups. Then we can make sure this is more performant than the naive implementation, i.e. only opening the file once. See also #8994.
  • [ ] Support backends other than netCDF and Zarr. - e.g. grib, see https://github.com/pydata/xarray/pull/7437,
  • [ ] Support dask properly - Issue https://github.com/xarray-contrib/datatree/pull/97 and the (stale) PR https://github.com/xarray-contrib/datatree/pull/196 are about dask parallelization over separate nodes in the tree.
  • [ ] Add other new high-level API methods - Things like .reorder_nodes and ideas we've only discussed like https://github.com/xarray-contrib/datatree/issues/79 and https://github.com/xarray-contrib/datatree/issues/254 (cc @dcherian who has had useful ideas here)
  • [ ] Copy xarray-contrib/datatree issues over to xarray's main repository. I think this is quite important and worth doing as a record of why decisions were made. (@jhamman and @TomNicholas)
  • [ ] Copy over any recent bug fixes from original datatree repository
  • [x] Look into merging commit history of xarray-contrib/datatree. I think this would be cool but is less important than keeping the issues. (@jhamman suggested we could do this using some git wizardry that I hadn't heard of before)
  • [ ] xarray.tutorial.open_datatree - I've been meaning to make a tutorial datatree object for ages. There's an issue about it, but actually now I think something close to the CMIP6 ensemble data that @jbusecke and I used in our pangeo blog post would already be pretty good. Once we have this it becomes much easier to write docs about some advanced features.
  • [ ] Merge Docs - I've tried to write these pages so that they should slot neatly into xarray's existing docs structure. Careful reading, additions and improvements would be great though. Summary of what docs exist on this issue https://github.com/xarray-contrib/datatree/issues/61
  • [ ] Write a blog post on the xarray blog highlighting xarray's new functionality, and explicitly thanking the NASA team for their work. Doesn't have to be long, it can just point to the documentation.

Anyone is welcome to help with any of this, including but not limited to @owenlittlejohns , @eni-awowale, @flamingbear (@etienneschalk maybe?).

cc also @shoyer @keewis for any thoughts as to the process.

 
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