can we brainstorm what a ZarrArrayWraper would need to be compatible with the new indexing API?

We will need to write new adapter code to map xarray's explicit indexer classes onto the appropriate zarr methods, e.g., ```python def getitem(self, key): array = self.get_arraay() if isinstance(key, BasicIndexer): return array[key.tuple] elif isinstance(key, VectorizedIndexer): return array.vindex[_replace_slices_with_arrays(key.tuple, self.shape)] else: assert isinstance(key, OuterIndexer) return array.oindex[key.tuple]

untested, but I think this does the appropriate shape munging to make slices

appear as the last axes of the result array

def _replace_slice_with_arrays(key, shape): num_slices = sum(1 for k in key if isinstance(k, slice)) num_arrays = len(shape) - num_slices new_key = [] slice_count = 0 for k, size in zip(key, shape): if isinstance(k, slice): array = np.arange(*k.indices(size)) sl = [np.newaxis] * len(shape) sl[num_arrays + slice_count] = np.newaxis k = array[sl] slice_count += 1 else: assert isinstance(k, numpy.ndarray) k = k[(slice(None),) * num_arrays + (np.newaxis,) * num_slices] new_key.append(k) return tuple(new_key) ```