Merge branch 'main' into coords_fix

docs/index.md

@@ -59,14 +59,9 @@ virtual_ds.virtualize.to_kerchunk('combined.json', format='json')
 Now you can open your shiny new Zarr store instantly:
 
 ```python
-fs = fsspec.filesystem('reference', fo='combined.json')
-m = fs.get_mapper('')
-
-ds = xr.open_dataset(m, engine='kerchunk', chunks={})  # normal xarray.Dataset object, wrapping dask/numpy arrays etc.
+ds = xr.open_dataset('combined.json', engine='kerchunk', chunks={})  # normal xarray.Dataset object, wrapping dask/numpy arrays etc.
 ```
 
-(Since we serialized the cached results using the kerchunk specification then opening this zarr store still requires using fsspec via the kerchunk xarray backend.)
-
 No data has been loaded or copied in this process, we have merely created an on-disk lookup table that points xarray into the specific parts of the original netCDF files when it needs to read each chunk.
 
 See the [Usage docs page](#usage) for more details.

virtualizarr/readers/common.py

@@ -19,10 +19,9 @@
     Variable,
     open_dataset,
 )
-from xarray.backends import AbstractDataStore, BackendArray
+from xarray.backends import AbstractDataStore
 from xarray.core.indexes import PandasIndex
 
-from virtualizarr.manifests import ManifestArray
 from virtualizarr.utils import _FsspecFSFromFilepath
 
 XArrayOpenT = str | os.PathLike[Any] | BufferedIOBase | AbstractDataStore
@@ -34,12 +33,6 @@
         DataTree = Any
 
 
-class ManifestBackendArray(ManifestArray, BackendArray):
-    """Using this prevents xarray from wrapping the KerchunkArray in ExplicitIndexingAdapter etc."""
-
-    ...
-
-
 def open_loadable_vars_and_indexes(
     filepath: str,
     loadable_variables,