refactor: Separate registry logic from ChunkGrid base class (fixes #3734)

- Remove ChunkGrid.from_dict class method that handled registry dispatch
- Create new parse_chunk_grid function to handle deserialization
- Update ArrayV3Metadata to use parse_chunk_grid instead of ChunkGrid.from_dict
- Follows the same pattern as parse_chunk_key_encoding for consistency
- Improves separation of concerns by removing registry responsibility from base class

Author: Claude Subagent

changes/3734.refactor.md

@@ -0,0 +1,19 @@
+# Refactor: Separate registry logic from ChunkGrid base class (fixes #3734)
+
+## Summary
+The `ChunkGrid` base class previously contained registry logic in its `from_dict` class method, which was responsible for dispatching to the appropriate subclass (e.g., `RegularChunkGrid`) based on the configuration. This violated the separation of concerns principle.
+
+## Changes
+1. **Removed `from_dict` from `ChunkGrid` base class**: The base class no longer handles the dispatch logic.
+2. **Created `parse_chunk_grid` function**: A new module-level function now handles the deserialization and dispatch to appropriate subclasses. This follows the same pattern as other similar functions in the codebase (e.g., `parse_chunk_key_encoding`).
+3. **Updated `ArrayV3Metadata`**: The metadata class now uses `parse_chunk_grid` instead of `ChunkGrid.from_dict`.
+
+## Benefits
+- **Separation of concerns**: The base class is now a pure data structure without registry responsibilities.
+- **Consistency**: The pattern now matches other similar types in the codebase (e.g., chunk key encodings).
+- **Extensibility**: New chunk grid types can be registered without modifying the base class.
+- **Clearer intent**: The registry logic is now explicit via the `parse_chunk_grid` function.
+
+## API Changes
+- **Breaking**: Code that directly called `ChunkGrid.from_dict()` should now call `parse_chunk_grid()` instead.
+- **Non-breaking**: Internal uses within the library have been updated. Public API users may need to update if they were directly using `ChunkGrid.from_dict()`.

src/zarr/core/chunk_grids.py

@@ -155,16 +155,6 @@ def normalize_chunks(chunks: Any, shape: tuple[int, ...], typesize: int) -> tupl
 
 @dataclass(frozen=True)
 class ChunkGrid(Metadata):
-    @classmethod
-    def from_dict(cls, data: dict[str, JSON] | ChunkGrid | NamedConfig[str, Any]) -> ChunkGrid:
-        if isinstance(data, ChunkGrid):
-            return data
-
-        name_parsed, _ = parse_named_configuration(data)
-        if name_parsed == "regular":
-            return RegularChunkGrid._from_dict(data)
-        raise ValueError(f"Unknown chunk grid. Got {name_parsed}.")
-
     @abstractmethod
     def all_chunk_coords(self, array_shape: tuple[int, ...]) -> Iterator[tuple[int, ...]]:
         pass
@@ -205,6 +195,39 @@ def get_nchunks(self, array_shape: tuple[int, ...]) -> int:
         )
 
 
+def parse_chunk_grid(data: dict[str, JSON] | ChunkGrid | NamedConfig[str, Any]) -> ChunkGrid:
+    """
+    Take an implicit specification of a chunk grid and parse it into a ChunkGrid object.
+
+    This function handles the deserialization of chunk grid configurations, dispatching
+    to the appropriate ChunkGrid subclass based on the `name` field.
+
+    Parameters
+    ----------
+    data : dict[str, JSON] | ChunkGrid | NamedConfig[str, Any]
+        The chunk grid specification. Can be:
+        - A ChunkGrid instance (returned as-is)
+        - A dict or NamedConfig with a "name" field specifying the type
+
+    Returns
+    -------
+    ChunkGrid
+        The parsed ChunkGrid instance.
+
+    Raises
+    ------
+    ValueError
+        If the chunk grid type is unknown.
+    """
+    if isinstance(data, ChunkGrid):
+        return data
+
+    name_parsed, _ = parse_named_configuration(data)
+    if name_parsed == "regular":
+        return RegularChunkGrid._from_dict(data)
+    raise ValueError(f"Unknown chunk grid. Got {name_parsed}.")
+
+
 def _guess_num_chunks_per_axis_shard(
     chunk_shape: tuple[int, ...], item_size: int, max_bytes: int, array_shape: tuple[int, ...]
 ) -> int:

src/zarr/core/metadata/v3.py

@@ -24,7 +24,7 @@
 
 from zarr.abc.codec import ArrayArrayCodec, ArrayBytesCodec, BytesBytesCodec, Codec
 from zarr.core.array_spec import ArrayConfig, ArraySpec
-from zarr.core.chunk_grids import ChunkGrid, RegularChunkGrid
+from zarr.core.chunk_grids import ChunkGrid, RegularChunkGrid, parse_chunk_grid
 from zarr.core.chunk_key_encodings import (
     ChunkKeyEncoding,
     ChunkKeyEncodingLike,
@@ -229,7 +229,7 @@ def __init__(
         """
 
         shape_parsed = parse_shapelike(shape)
-        chunk_grid_parsed = ChunkGrid.from_dict(chunk_grid)
+        chunk_grid_parsed = parse_chunk_grid(chunk_grid)
         chunk_key_encoding_parsed = parse_chunk_key_encoding(chunk_key_encoding)
         dimension_names_parsed = parse_dimension_names(dimension_names)
         # Note: relying on a type method is numpy-specific