from xarray import align, Dataset ds1 = Dataset(coords={"x": [1, 2, 3], "xb": ("x", [4, 5, 6])}).set_xindex("xb") # Swap two values in only "xb" only ds2 = Dataset(coords={"x": [1, 2, 3], "xb": ("x", [4, 6, 5])}).set_xindex("xb") # Swap two (different) values in both coordinates ds3 = Dataset(coords={"x": [2, 1, 3], "xb": ("x", [4, 6, 5])}).set_xindex("xb") align(ds1, ds2) # --> no error (which is wrong) align(ds1, ds3) # --> AlignmentError (as expected)

# Source: xarray/structure/alignment.py def _get_dim_pos_indexers( self, matching_indexes: dict[MatchingIndexKey, Index], ) -> dict[Hashable, Any]: dim_pos_indexers: dict[Hashable, Any] = {} dim_index: dict[Hashable, Index] = {} for key, aligned_idx in self.aligned_indexes.items(): obj_idx = matching_indexes.get(key) if obj_idx is not None and self.reindex[key]: ####################################################################### # ↓ None of this code is run for indexes that require no reindexing ↓ # ####################################################################### indexers = obj_idx.reindex_like(aligned_idx, **self.reindex_kwargs) for dim, idxer in indexers.items(): if dim in self.exclude_dims: raise AlignmentError( f"cannot reindex or align along dimension {dim!r} because " "it is explicitly excluded from alignment. This is likely caused by " "wrong results returned by the `reindex_like` method of this index:\n" f"{obj_idx!r}" ) if dim in dim_pos_indexers and not np.array_equal( idxer, dim_pos_indexers[dim] ): raise AlignmentError( f"cannot reindex or align along dimension {dim!r} because " "of conflicting re-indexers returned by multiple indexes\n" f"first index: {obj_idx!r}\nsecond index: {dim_index[dim]!r}\n" ) dim_pos_indexers[dim] = idxer dim_index[dim] = obj_idx return dim_pos_indexers