rollback caching

src/nwbinspector/utils/_utils.py

@@ -34,13 +34,13 @@ def _cache_data_retrieval_command(
 
 
 def cache_data_selection(
-    data: Union[h5py.Dataset, zarr.Array, ArrayLike], selection: Union[slice, tuple[slice]]
+    data: Union[h5py.Dataset, ArrayLike], selection: Union[slice, tuple[slice]]
 ) -> np.ndarray:
     """Extract the selection lazily from the data object for efficient caching (most beneficial during streaming)."""
     if isinstance(data, np.memmap):  # np.memmap objects are not hashable - simply return the selection lazily
         return data[selection]
     if not (
-        isinstance(data, (h5py.Dataset, zarr.Array)) or isinstance(data, H5Dataset)
+        isinstance(data, h5py.Dataset) or isinstance(data, H5Dataset)
     ):  # No need to attempt to cache if data is already in-memory
         # Cast as numpy array for efficient fancy indexing
         # Note that this technically copies the entire data, so could use more than 2x RAM for that object