refactor broadcast for flexible indexes
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- Dominant language
- Python
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Description
What is your issue?
From @benbovy in https://github.com/pydata/xarray/pull/6477
- extract common indexes and explicitly pass them to the Dataset and DataArray constructors (when implemented) that are called in the broadcast helper functions (there are some temporary and ugly hacks in create_default_index_implicit so that it works now with pandas multi-indexes wrapped in coordinate variables without the need to pass those indexes explicitly)
- extract common indexes based on the dimension(s) of their coordinates and not their name (e.g., case of non-dimension but indexed coordinate)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the broadcast helper functions and create_default_index_implicit, the entry points named in the issue. Check how common indexes are identified and passed to Dataset and DataArray constructors. Done means common indexes are explicitly handled by coordinate dimensions, including non-dimension indexed coordinates and pandas multi-indexes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pandas, python
- Domain
- data
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100