issue_comments: 1261015002

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https://github.com/pydata/xarray/issues/7099#issuecomment-1261015002 https://api.github.com/repos/pydata/xarray/issues/7099 1261015002 IC_kwDOAMm_X85LKY_a 4160723 2022-09-28T14:39:10Z 2022-09-28T14:39:10Z MEMBER

Or use Indexer objects to group labels + options? This is slightly different than what you suggest:

```python class Dataset:

def sel(
    self,
    indexers: Mapping[Any, Any] | Indexer | Iterable[Indexer],
    **indexers_kwargs: Any,
):
    ...

class Indexer: def init(self, labels=None, options=None, **label_kwargs): ... ```

Let's assume a Dataset with lat / lon coordinates both sharing the same geographic index + another time dimension coordinate, then we could write:

```python indexers = [ Indexer(lon=[2, 15], lat=[45, 48], options={"foo": "bar"}), Indexer(time="2022-01-01"), ]

ds.sel(indexers) ```

This could also be used to avoid code duplication when using common selection options for different indexes.

 
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