use new RegularChunkGridMetadata

.github/workflows/ci.yaml

@@ -38,7 +38,6 @@ jobs:
       fail-fast: false
       matrix:
         python-version:
-          - "3.11"
           - "3.12"
           - "3.13"
           - "3.14"

.python-version

@@ -1 +1 @@
-3.11
+3.12

pyproject.toml

@@ -4,8 +4,8 @@ version = "0.2.0"
 description = "Utilities for accessing N5 data through zarr v3."
 readme = "README.md"
 authors = [{ name = "Chris Barnes", email = "chris.barnes@gerbi-gmb.de" }]
-requires-python = ">=3.11,<4.0"
-dependencies = ["zarr>=3.1.5"]
+requires-python = ">=3.12,<4.0"
+dependencies = ["zarr>=3.2.0"]
 
 [project.entry-points."zarr.codecs"]
 "n5_default" = "zarr_n5:N5DefaultCodec"

src/zarr_n5/codec/default.py

@@ -9,7 +9,7 @@
 from zarr.abc.codec import ArrayBytesCodec, Codec, BytesBytesCodec, CodecPipeline
 from zarr.core.array_spec import ArraySpec
 from zarr.core.buffer.core import Buffer, NDBuffer
-from zarr.core.chunk_grids import ChunkGrid
+from zarr.core.metadata.v3 import ChunkGridMetadata
 from zarr.core.dtype.wrapper import TBaseDType, ZDType, TBaseScalar
 from zarr.core.common import JSON, parse_named_configuration
 from zarr.core.metadata.v3 import parse_codecs
@@ -170,7 +170,7 @@ def validate(
         *,
         shape: tuple[int, ...],
         dtype: ZDType[TBaseDType, TBaseScalar],
-        chunk_grid: ChunkGrid,
+        chunk_grid: ChunkGridMetadata,
     ) -> None:
         expected_ndim = len(self.codecs[0].order)
         if len(shape) != expected_ndim:

src/zarr_n5/metadata.py

@@ -10,7 +10,7 @@
 from zarr.core.metadata.v3 import ArrayV3Metadata
 from zarr.core.dtype import ZDType
 from zarr.core import dtype as zdt
-from zarr.core.chunk_grids import RegularChunkGrid
+from zarr.core.metadata.v3 import RegularChunkGridMetadata
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
 from zarr.abc.codec import BytesBytesCodec
 from zarr.codecs import blosc
@@ -130,7 +130,7 @@ def to_zarr(self, mode: N5Mode = N5Mode.DEFAULT):
         return ArrayV3Metadata(
             shape=self.dimensions,
             data_type=COMPATIBLE_DATA_TYPES[self.data_type][0],
-            chunk_grid=RegularChunkGrid(chunk_shape=self.block_size),
+            chunk_grid=RegularChunkGridMetadata(chunk_shape=tuple(self.block_size)),
             chunk_key_encoding=V2ChunkKeyEncoding("/"),
             fill_value=0,
             dimension_names=None,