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Implement hybrid type system combining PR zarr-developers#3355 structure with comprehensive exports
This approach builds on PR zarr-developers#3355's zarr.core.types foundation while massively expanding zarr.types public exports to enable comprehensive type documentation linking. The hybrid strategy provides the best of both worlds: - Maintains clean architectural separation (internal zarr.core.types vs public zarr.types) - Enables comprehensive documentation coverage (~75% vs ~7% with vanilla PR zarr-developers#3355) - Provides excellent developer experience with single import location - Supports all common types used in function signatures for proper Sphinx linking Key additions to zarr.types public API: - Core classes: Array, AsyncArray, Group, AsyncGroup, ZDType, DefaultFillValue - Store types: Store, StorePath, StoreLike, ByteGetter, ByteSetter - Array types: NDArrayLike, ArrayLike, ZDTypeLike - Metadata types: ArrayV2Metadata, ArrayV3Metadata, GroupMetadata, ConsolidatedMetadata - Codec types: BaseCodec, ArrayArrayCodec, BytesBytesCodec, CompressorLike, etc. - Configuration types: ArrayConfig, ArrayConfigLike, ChunkKeyEncodingLike - Enum types: BloscCname, BloscShuffle, Endian, Order, etc. This enables the core goal: "ideally everything in a type hint will be linkable" while maintaining good software engineering practices. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <[email protected]> Co-Authored-By: Davis Bennett <[email protected]>
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‎src/zarr/__init__.py

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from zarr import types
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from zarr._version import version as __version__
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from zarr.api.synchronous import (
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array,
@@ -120,6 +121,7 @@ def print_packages(packages: list[str]) -> None:
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"save_array",
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"save_group",
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"tree",
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"types",
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"zeros",
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"zeros_like",
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]

‎src/zarr/types.py

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"""Public type definitions and constants"""
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from __future__ import annotations
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from collections.abc import Iterable, Mapping, Sequence
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from os import PathLike
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from typing import TYPE_CHECKING, Any, Literal, TypeAlias, TypeVar
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# Import core types from zarr.core.types
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from zarr.core.types import (
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JSON,
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AccessModeLiteral,
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ArrayMetadataJSON_V2,
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ArrayMetadataJSON_V3,
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BytesLike,
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ChunkCoords,
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ChunkCoordsLike,
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DimensionNames,
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GroupMetadataJSON_V2,
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GroupMetadataJSON_V3,
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MemoryOrder,
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NodeType,
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ShapeLike,
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ZarrFormat,
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)
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# Additional types needed for comprehensive documentation linking
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# These extend the minimal set from zarr.core.types
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# Import numpy types for proper typing
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if TYPE_CHECKING:
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import numpy as np
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import numpy.typing as npt
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# Core classes - forward references for main API classes
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if TYPE_CHECKING:
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from zarr.core.array import Array as _Array
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from zarr.core.array import AsyncArray as _AsyncArray
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from zarr.core.common import DefaultFillValue as _DefaultFillValue
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from zarr.core.dtype import ZDType as _ZDType
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from zarr.core.group import AsyncGroup as _AsyncGroup
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from zarr.core.group import Group as _Group
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Array: TypeAlias = _Array[Any]
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AsyncArray: TypeAlias = _AsyncArray[Any]
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Group: TypeAlias = _Group
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AsyncGroup: TypeAlias = _AsyncGroup
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DefaultFillValue: TypeAlias = _DefaultFillValue
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ZDType: TypeAlias = _ZDType
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else:
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# Import at runtime for autoapi to resolve
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try:
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from zarr.core.array import Array, AsyncArray
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from zarr.core.common import DefaultFillValue
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from zarr.core.dtype import ZDType
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from zarr.core.group import AsyncGroup, Group
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except ImportError:
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# Fallback to TypeVar placeholders
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Array = TypeVar("Array")
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AsyncArray = TypeVar("AsyncArray")
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Group = TypeVar("Group")
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AsyncGroup = TypeVar("AsyncGroup")
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DefaultFillValue = TypeVar("DefaultFillValue")
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ZDType = TypeVar("ZDType")
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# Store types with forward references
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if TYPE_CHECKING:
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from zarr.abc.store import Store as _Store
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from zarr.storage import StorePath as _StorePath
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Store: TypeAlias = _Store
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StorePath: TypeAlias = _StorePath
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else:
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# Import at runtime for autoapi to resolve
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Store = TypeVar("Store")
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StorePath = TypeVar("StorePath")
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StoreLike: TypeAlias = Store | StorePath | PathLike[str] | str | dict[str, Any] | Mapping[str, Any]
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"""Store-like object. Can be a Store, StorePath, Path, str, or dict."""
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# Array types with proper numpy typing
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if TYPE_CHECKING:
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NDArrayLike: TypeAlias = npt.NDArray[Any] | np.generic
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else:
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NDArrayLike = TypeVar("NDArrayLike")
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NDArrayLikeOrScalar: TypeAlias = NDArrayLike | Any
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ArrayLike: TypeAlias = Sequence[Any] | NDArrayLike
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# ZDType - special handling for strong typing
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if TYPE_CHECKING:
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from zarr.core.dtype import ZDType as _ZDTypeRuntime
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ZDTypeLike: TypeAlias = _ZDTypeRuntime | Any
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else:
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ZDTypeLike = TypeVar("ZDTypeLike")
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# Chunk key encoding types
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if TYPE_CHECKING:
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from zarr.core.chunk_key_encodings import ChunkKeyEncoding as _ChunkKeyEncoding
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from zarr.core.chunk_key_encodings import ChunkKeyEncodingParams as _ChunkKeyEncodingParams
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ChunkKeyEncodingLike: TypeAlias = _ChunkKeyEncodingParams | _ChunkKeyEncoding
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ChunkKeyEncoding: TypeAlias = _ChunkKeyEncoding
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ChunkKeyEncodingParams: TypeAlias = _ChunkKeyEncodingParams
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else:
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ChunkKeyEncodingLike = TypeVar("ChunkKeyEncodingLike")
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ChunkKeyEncoding = TypeVar("ChunkKeyEncoding")
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ChunkKeyEncodingParams = TypeVar("ChunkKeyEncodingParams")
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# Array config types
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if TYPE_CHECKING:
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from zarr.core.array_spec import ArrayConfig as _ArrayConfig
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from zarr.core.array_spec import ArrayConfigLike as _ArrayConfigLike
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ArrayConfig: TypeAlias = _ArrayConfig
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ArrayConfigLike: TypeAlias = _ArrayConfigLike
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else:
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try:
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from zarr.core.array_spec import ArrayConfig, ArrayConfigLike
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except ImportError:
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ArrayConfig = TypeVar("ArrayConfig")
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ArrayConfigLike = TypeVar("ArrayConfigLike")
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# Codec class types
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if TYPE_CHECKING:
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from zarr.abc.codec import ArrayArrayCodec as _ArrayArrayCodec
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from zarr.abc.codec import ArrayBytesCodec as _ArrayBytesCodec
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from zarr.abc.codec import BaseCodec as _BaseCodec
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from zarr.abc.codec import BytesBytesCodec as _BytesBytesCodec
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from zarr.abc.codec import CodecPipeline as _CodecPipeline
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BaseCodec: TypeAlias = _BaseCodec[Any, Any]
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ArrayArrayCodec: TypeAlias = _ArrayArrayCodec[Any, Any]
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ArrayBytesCodec: TypeAlias = _ArrayBytesCodec[Any]
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BytesBytesCodec: TypeAlias = _BytesBytesCodec
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CodecPipeline: TypeAlias = _CodecPipeline[Any]
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Codec: TypeAlias = _BaseCodec[Any, Any]
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else:
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try:
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from zarr.abc.codec import (
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ArrayArrayCodec,
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ArrayBytesCodec,
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BaseCodec,
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BytesBytesCodec,
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CodecPipeline,
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)
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Codec = BaseCodec
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except ImportError:
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BaseCodec = TypeVar("BaseCodec")
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ArrayArrayCodec = TypeVar("ArrayArrayCodec")
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ArrayBytesCodec = TypeVar("ArrayBytesCodec")
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BytesBytesCodec = TypeVar("BytesBytesCodec")
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CodecPipeline = TypeVar("CodecPipeline")
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Codec = BaseCodec
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# Additional commonly used types
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ArrayMetadata: TypeAlias = Any
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ArrayMetadataDict: TypeAlias = dict[str, JSON]
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ArrayV2MetadataDict: TypeAlias = dict[str, JSON]
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ArrayV3MetadataDict: TypeAlias = dict[str, JSON]
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# Additional metadata types with forward references
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if TYPE_CHECKING:
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from zarr.core.array_spec import ArrayV2Metadata as _ArrayV2Metadata
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from zarr.core.array_spec import ArrayV3Metadata as _ArrayV3Metadata
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from zarr.core.group import ConsolidatedMetadata as _ConsolidatedMetadata
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from zarr.core.group import GroupMetadata as _GroupMetadata
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ArrayV2Metadata: TypeAlias = _ArrayV2Metadata
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ArrayV3Metadata: TypeAlias = _ArrayV3Metadata
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GroupMetadata: TypeAlias = _GroupMetadata
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ConsolidatedMetadata: TypeAlias = _ConsolidatedMetadata
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else:
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GroupMetadata = TypeVar("GroupMetadata")
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ConsolidatedMetadata = TypeVar("ConsolidatedMetadata")
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# Codec types
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if TYPE_CHECKING:
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from zarr.abc.codec import BytesBytesCodec as _BytesBytesCodec
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CompressorLike: TypeAlias = dict[str, JSON] | _BytesBytesCodec | Any | Literal["auto"] | None
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else:
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CompressorLike: TypeAlias = dict[str, JSON] | Any | Literal["auto"] | None
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CompressorsLike: TypeAlias = Iterable[CompressorLike]
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FiltersLike: TypeAlias = Iterable[Any]
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SerializerLike: TypeAlias = Any
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ShardsLike: TypeAlias = tuple[int, ...] | None
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CompressorLikev2: TypeAlias = dict[str, JSON] | Any | None
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# Store protocols
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if TYPE_CHECKING:
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from zarr.abc.store import ByteGetter as _ByteGetter
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from zarr.abc.store import ByteSetter as _ByteSetter
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ByteGetter: TypeAlias = _ByteGetter
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ByteSetter: TypeAlias = _ByteSetter
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else:
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ByteGetter = TypeVar("ByteGetter")
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ByteSetter = TypeVar("ByteSetter")
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# Import enums at runtime - these don't cause circular imports
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try:
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from zarr.codecs.blosc import BloscCname, BloscShuffle
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from zarr.codecs.bytes import Endian
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from zarr.codecs.sharding import ShardingCodecIndexLocation
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from zarr.core.indexing import Order
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except ImportError:
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# Fallback if imports fail
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BloscCname = Any
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BloscShuffle = Any
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Endian = Any
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ShardingCodecIndexLocation = Any
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Order = Any
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__all__ = [
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# Basic type aliases from zarr.core.types
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"JSON",
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"AccessModeLiteral",
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# Extended types for comprehensive documentation linking
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# Core classes
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"Array",
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"ArrayArrayCodec",
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"ArrayBytesCodec",
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# Array config
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"ArrayConfig",
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"ArrayConfigLike",
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# Array types
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"ArrayLike",
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# Metadata types
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"ArrayMetadata",
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"ArrayMetadataDict",
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# Core metadata types from zarr.core.types
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"ArrayMetadataJSON_V2",
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"ArrayMetadataJSON_V3",
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"ArrayV2Metadata",
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"ArrayV2MetadataDict",
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"ArrayV3Metadata",
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"ArrayV3MetadataDict",
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"AsyncArray",
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"AsyncGroup",
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# Codec types
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"BaseCodec",
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# Enums
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"BloscCname",
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"BloscShuffle",
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"ByteGetter",
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"ByteSetter",
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"BytesBytesCodec",
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"BytesLike",
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"ChunkCoords",
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"ChunkCoordsLike",
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# Chunk key encoding
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"ChunkKeyEncoding",
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"ChunkKeyEncodingLike",
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"ChunkKeyEncodingParams",
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"Codec",
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"CodecPipeline",
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"CompressorLike",
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"CompressorLikev2",
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"CompressorsLike",
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"ConsolidatedMetadata",
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"DefaultFillValue",
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"DimensionNames",
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"Endian",
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"FiltersLike",
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"Group",
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"GroupMetadata",
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"GroupMetadataJSON_V2",
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"GroupMetadataJSON_V3",
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"MemoryOrder",
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"NDArrayLike",
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"NDArrayLikeOrScalar",
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"NodeType",
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"Order",
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"SerializerLike",
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"ShapeLike",
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"ShardingCodecIndexLocation",
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"ShardsLike",
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# Store types
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"Store",
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"StoreLike",
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"StorePath",
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"ZDType",
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"ZDTypeLike",
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"ZarrFormat",
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]
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# Post-import patching for types that have circular import issues
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if not TYPE_CHECKING:
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try:
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from zarr.storage._common import StorePath as _StorePath_Runtime
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StorePath = _StorePath_Runtime
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from zarr.abc.store import Store as _Store_Runtime
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Store = _Store_Runtime
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# Update StoreLike with the real types
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StoreLike = Store | StorePath | PathLike[str] | str | dict[str, Any] | Mapping[str, Any]
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except ImportError:
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pass # Keep the TypeVar fallbacks

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