diff --git a/virtualizarr/translators/kerchunk.py b/virtualizarr/translators/kerchunk.py
index d30832b9..374866d1 100644
--- a/virtualizarr/translators/kerchunk.py
+++ b/virtualizarr/translators/kerchunk.py
@@ -11,7 +11,7 @@
     KerchunkArrRefs,
     KerchunkStoreRefs,
 )
-from virtualizarr.zarr import ZAttrs, determine_chunk_grid_shape
+from virtualizarr.zarr import determine_chunk_grid_shape
 
 
 def virtual_vars_and_metadata_from_kerchunk_refs(
@@ -265,6 +265,7 @@ def extract_array_refs(
         )
 
 
+from zarr.core.common import JSON
 from zarr.core.metadata import ArrayV3Metadata
 
 from virtualizarr.zarr import from_kerchunk_refs
@@ -272,7 +273,7 @@ def extract_array_refs(
 
 def parse_array_refs(
     arr_refs: KerchunkArrRefs,
-) -> tuple[dict, ArrayV3Metadata, ZAttrs]:
+) -> tuple[dict, ArrayV3Metadata, dict[str, JSON]]:
     metadata = from_kerchunk_refs(arr_refs.pop(".zarray"))
     zattrs = arr_refs.pop(".zattrs", {})
     chunk_dict = arr_refs
diff --git a/virtualizarr/zarr.py b/virtualizarr/zarr.py
index 597868b7..ec6c68bc 100644
--- a/virtualizarr/zarr.py
+++ b/virtualizarr/zarr.py
@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING, Any, Literal, NewType
+from typing import Any
 
 import numpy as np
 from zarr.abc.codec import ArrayArrayCodec, ArrayBytesCodec, BytesBytesCodec
@@ -6,35 +6,9 @@
 from zarr.core.codec_pipeline import BatchedCodecPipeline
 from zarr.core.common import JSON
 from zarr.core.metadata.v2 import ArrayV2Metadata
-from zarr.core.metadata.v3 import ArrayV3Metadata
-
-if TYPE_CHECKING:
-    try:
-        from zarr.abc.codec import Codec as ZarrCodec
-    except ImportError:
-        pass
-
-# TODO replace these with classes imported directly from Zarr? (i.e. Zarr Object Models)
-ZAttrs = NewType(
-    "ZAttrs", dict[str, Any]
-)  # just the .zattrs (for one array or for the whole store/group)
-FillValueT = bool | str | float | int | list | None
-ZARR_FORMAT = Literal[2, 3]
-
-ZARR_DEFAULT_FILL_VALUE: dict[str, FillValueT] = {
-    # numpy dtypes's hierarchy lets us avoid checking for all the widths
-    # https://numpy.org/doc/stable/reference/arrays.scalars.html
-    np.dtype("bool").kind: False,
-    np.dtype("int").kind: 0,
-    np.dtype("float").kind: 0.0,
-    np.dtype("complex").kind: [0.0, 0.0],
-    np.dtype("datetime64").kind: 0,
-}
-"""
-The value and format of the fill_value depend on the `data_type` of the array.
-See here for spec:
-https://zarr-specs.readthedocs.io/en/latest/v3/core/v3.0.html#fill-value
-"""
+from zarr.core.metadata.v3 import (
+    ArrayV3Metadata,  # just the .zattrs (for one array or for the whole store/group)
+)
 
 
 def ceildiv(a: int, b: int) -> int:
@@ -228,9 +202,10 @@ def to_kerchunk_json(v2_metadata: ArrayV2Metadata) -> str:
 
 def from_kerchunk_refs(decoded_arr_refs_zarray) -> "ArrayV3Metadata":
     """
-    Convert a decoded Zarr array reference to an ArrayV3Metadata object.
+    Convert a decoded zarr array (.zarray) reference to an ArrayV3Metadata object.
     This function processes the given decoded Zarr array reference dictionary,
     to construct and return an ArrayV3Metadata object based on the provided information.
+
     Parameters:
     ----------
     decoded_arr_refs_zarray : dict