Use implicit fill values for zarr v2

src/zarr/codecs/pipeline.py

@@ -17,6 +17,7 @@
 from zarr.core.common import ChunkCoords, concurrent_map
 from zarr.core.config import config
 from zarr.core.indexing import SelectorTuple, is_scalar, is_total_slice
+from zarr.core.metadata.v2 import default_fill_value
 from zarr.registry import register_pipeline
 
 if TYPE_CHECKING:
@@ -247,7 +248,17 @@ async def read_batch(
                 if chunk_array is not None:
                     out[out_selection] = chunk_array
                 else:
-                    out[out_selection] = chunk_spec.fill_value
+                    fill_value = chunk_spec.fill_value
+
+                    if fill_value is None:
+                        # Zarr V2 allowed `fill_value` to be null in the metadata.
+                        # Zarr V3 requires it to be set. This has already been
+                        # validated when decoding the metadata, but we support reading
+                        # Zarr V2 data and need to support the case where fill_value
+                        # is None.
+                        fill_value = default_fill_value(dtype=chunk_spec.dtype)
+
+                    out[out_selection] = fill_value
         else:
             chunk_bytes_batch = await concurrent_map(
                 [
@@ -274,7 +285,10 @@ async def read_batch(
                         tmp = tmp.squeeze(axis=drop_axes)
                     out[out_selection] = tmp
                 else:
-                    out[out_selection] = chunk_spec.fill_value
+                    fill_value = chunk_spec.fill_value
+                    if fill_value is None:
+                        fill_value = default_fill_value(dtype=chunk_spec.dtype)
+                    out[out_selection] = fill_value
 
     def _merge_chunk_array(
         self,

src/zarr/core/array.py

@@ -376,7 +376,7 @@ async def _create_v2(
             chunks=chunks,
             order=order,
             dimension_separator=dimension_separator,
-            fill_value=0 if fill_value is None else fill_value,
+            fill_value=fill_value,
             compressor=compressor,
             filters=filters,
             attributes=attributes,

src/zarr/core/metadata/v2.py

@@ -284,3 +284,19 @@ def parse_fill_value(fill_value: object, dtype: np.dtype[Any]) -> Any:
             raise ValueError(msg) from e
 
     return fill_value
+
+
+def default_fill_value(dtype: np.dtype[Any]) -> Any:
+    """
+    Get the default fill value for a type.
+
+    Notes
+    -----
+    This differs from :func:`parse_fill_value`, which parses a fill value
+    stored in the Array metadata into an in-memory value. This only gives
+    the default fill value for some type.
+
+    This is useful for reading Zarr V2 arrays, which allow the fill
+    value to be unspecified.
+    """
+    return dtype.type(0)

src/zarr/testing/strategies.py

@@ -140,7 +140,8 @@ def arrays(
     )
 
     assert isinstance(a, Array)
-    assert a.fill_value is not None
+    if a.metadata.zarr_format == 3:
+        assert a.fill_value is not None
     assert isinstance(root[array_path], Array)
     assert nparray.shape == a.shape
     assert chunks == a.chunks

tests/v3/test_metadata/test_v2.py

@@ -28,7 +28,7 @@ def test_parse_zarr_format_invalid(data: Any) -> None:
 @pytest.mark.parametrize("attributes", [None, {"foo": "bar"}])
 @pytest.mark.parametrize("filters", [None, (), (numcodecs.GZip(),)])
 @pytest.mark.parametrize("compressor", [None, numcodecs.GZip()])
-@pytest.mark.parametrize("fill_value", [0, 1])
+@pytest.mark.parametrize("fill_value", [None, 0, 1])
 @pytest.mark.parametrize("order", ["C", "F"])
 @pytest.mark.parametrize("dimension_separator", [".", "/", None])
 def test_metadata_to_dict(

tests/v3/test_v2.py

@@ -31,6 +31,15 @@ def test_simple(store: StorePath) -> None:
     assert np.array_equal(data, a[:, :])
 
 
+def test_implicit_fill_value(store: StorePath) -> None:
+    arr = zarr.open_array(store=store, shape=(4,), fill_value=None, zarr_format=2)
+    assert arr.metadata.fill_value is None
+    assert arr.metadata.to_dict()["fill_value"] is None
+    result = arr[:]
+    expected = np.zeros(arr.shape, dtype=arr.dtype)
+    np.testing.assert_array_equal(result, expected)
+
+
 def test_codec_pipeline() -> None:
     # https://github.com/zarr-developers/zarr-python/issues/2243
     store = MemoryStore(mode="w")