Apply ruff/flake8-pyi rule PYI055

PYI055 Multiple `type` members in a union. Combine them into one.

pyproject.toml

@@ -211,13 +211,15 @@ extend-select = [
     "I",   # isort
     "ISC", # flake8-implicit-str-concat
     "PGH", # pygrep-hooks
+    "PYI", # flake8-pyi
     "RSE", # flake8-raise
     "RUF",
     "TCH", # flake8-type-checking
     "TRY", # tryceratops
     "UP",  # pyupgrade
 ]
 ignore = [
+    "PYI013",
     "RUF005",
     "TRY003",
     # https://docs.astral.sh/ruff/formatter/#conflicting-lint-rules

src/zarr/abc/store.py

@@ -36,7 +36,7 @@ class Store(ABC):
     _mode: AccessMode
     _is_open: bool
 
-    def __init__(self, mode: AccessModeLiteral = "r", *args: Any, **kwargs: Any):
+    def __init__(self, mode: AccessModeLiteral = "r", *args: Any, **kwargs: Any) -> None:
         self._is_open = False
         self._mode = AccessMode.from_literal(mode)
 

src/zarr/codecs/transpose.py

@@ -96,16 +96,14 @@ async def _decode_single(
         chunk_spec: ArraySpec,
     ) -> NDBuffer:
         inverse_order = np.argsort(self.order)
-        chunk_array = chunk_array.transpose(inverse_order)
-        return chunk_array
+        return chunk_array.transpose(inverse_order)
 
     async def _encode_single(
         self,
         chunk_array: NDBuffer,
         _chunk_spec: ArraySpec,
     ) -> NDBuffer | None:
-        chunk_array = chunk_array.transpose(self.order)
-        return chunk_array
+        return chunk_array.transpose(self.order)
 
     def compute_encoded_size(self, input_byte_length: int, _chunk_spec: ArraySpec) -> int:
         return input_byte_length

src/zarr/core/array.py

@@ -110,7 +110,7 @@ def __init__(
         metadata: ArrayMetadata,
         store_path: StorePath,
         order: Literal["C", "F"] | None = None,
-    ):
+    ) -> None:
         metadata_parsed = parse_array_metadata(metadata)
         order_parsed = parse_indexing_order(order or config.get("array.order"))
 
@@ -331,8 +331,7 @@ def from_dict(
         data: dict[str, JSON],
     ) -> AsyncArray:
         metadata = parse_array_metadata(data)
-        async_array = cls(metadata=metadata, store_path=store_path)
-        return async_array
+        return cls(metadata=metadata, store_path=store_path)
 
     @classmethod
     async def open(

src/zarr/core/attributes.py

@@ -13,7 +13,7 @@
 
 
 class Attributes(MutableMapping[str, JSON]):
-    def __init__(self, obj: Array | Group):
+    def __init__(self, obj: Array | Group) -> None:
         # key=".zattrs", read_only=False, cache=True, synchronizer=None
         self._obj = obj
 

src/zarr/core/buffer/core.py

@@ -136,7 +136,7 @@ class Buffer(ABC):
         array-like object that must be 1-dim, contiguous, and byte dtype.
     """
 
-    def __init__(self, array_like: ArrayLike):
+    def __init__(self, array_like: ArrayLike) -> None:
         if array_like.ndim != 1:
             raise ValueError("array_like: only 1-dim allowed")
         if array_like.dtype != np.dtype("b"):
@@ -313,7 +313,7 @@ class NDBuffer:
         ndarray-like object that is convertible to a regular Numpy array.
     """
 
-    def __init__(self, array: NDArrayLike):
+    def __init__(self, array: NDArrayLike) -> None:
         # assert array.ndim > 0
         assert array.dtype != object
         self._data = array

src/zarr/core/buffer/cpu.py

@@ -45,7 +45,7 @@ class Buffer(core.Buffer):
         array-like object that must be 1-dim, contiguous, and byte dtype.
     """
 
-    def __init__(self, array_like: ArrayLike):
+    def __init__(self, array_like: ArrayLike) -> None:
         super().__init__(array_like)
 
     @classmethod
@@ -143,7 +143,7 @@ class NDBuffer(core.NDBuffer):
         ndarray-like object that is convertible to a regular Numpy array.
     """
 
-    def __init__(self, array: NDArrayLike):
+    def __init__(self, array: NDArrayLike) -> None:
         super().__init__(array)
 
     @classmethod

src/zarr/core/buffer/gpu.py

@@ -48,7 +48,7 @@ class Buffer(core.Buffer):
         array-like object that must be 1-dim, contiguous, and byte dtype.
     """
 
-    def __init__(self, array_like: ArrayLike):
+    def __init__(self, array_like: ArrayLike) -> None:
         if cp is None:
             raise ImportError(
                 "Cannot use zarr.buffer.gpu.Buffer without cupy. Please install cupy."
@@ -137,7 +137,7 @@ class NDBuffer(core.NDBuffer):
         ndarray-like object that is convertible to a regular Numpy array.
     """
 
-    def __init__(self, array: NDArrayLike):
+    def __init__(self, array: NDArrayLike) -> None:
         if cp is None:
             raise ImportError(
                 "Cannot use zarr.buffer.gpu.NDBuffer without cupy. Please install cupy."

src/zarr/core/group.py

@@ -54,7 +54,7 @@ def parse_zarr_format(data: Any) -> ZarrFormat:
 def parse_attributes(data: Any) -> dict[str, Any]:
     if data is None:
         return {}
-    elif isinstance(data, dict) and all(isinstance(v, str) for v in data.keys()):
+    elif isinstance(data, dict) and all(isinstance(k, str) for k in data):
         return data
     msg = f"Expected dict with string keys. Got {type(data)} instead."
     raise TypeError(msg)
@@ -104,7 +104,9 @@ def to_buffer_dict(self, prototype: BufferPrototype) -> dict[str, Buffer]:
                 ),
             }
 
-    def __init__(self, attributes: dict[str, Any] | None = None, zarr_format: ZarrFormat = 3):
+    def __init__(
+        self, attributes: dict[str, Any] | None = None, zarr_format: ZarrFormat = 3
+    ) -> None:
         attributes_parsed = parse_attributes(attributes)
         zarr_format_parsed = parse_zarr_format(zarr_format)
 
@@ -202,11 +204,10 @@ def from_dict(
         store_path: StorePath,
         data: dict[str, Any],
     ) -> AsyncGroup:
-        group = cls(
+        return cls(
             metadata=GroupMetadata.from_dict(data),
             store_path=store_path,
         )
-        return group
 
     async def getitem(
         self,
@@ -888,8 +889,7 @@ def members(self, max_depth: int | None = 0) -> tuple[tuple[str, Array | Group],
         """
         _members = self._sync_iter(self._async_group.members(max_depth=max_depth))
 
-        result = tuple((kv[0], _parse_async_node(kv[1])) for kv in _members)
-        return result
+        return tuple((kv[0], _parse_async_node(kv[1])) for kv in _members)
 
     def __contains__(self, member: str) -> bool:
         return self._sync(self._async_group.contains(member))

src/zarr/core/indexing.py

@@ -54,7 +54,7 @@ class ArrayIndexError(IndexError):
 class BoundsCheckError(IndexError):
     _msg = ""
 
-    def __init__(self, dim_len: int):
+    def __init__(self, dim_len: int) -> None:
         self._msg = f"index out of bounds for dimension with length {dim_len}"
 
 
@@ -255,7 +255,7 @@ class IntDimIndexer:
     dim_chunk_len: int
     nitems: int = 1
 
-    def __init__(self, dim_sel: int, dim_len: int, dim_chunk_len: int):
+    def __init__(self, dim_sel: int, dim_len: int, dim_chunk_len: int) -> None:
         object.__setattr__(self, "dim_sel", normalize_integer_selection(dim_sel, dim_len))
         object.__setattr__(self, "dim_len", dim_len)
         object.__setattr__(self, "dim_chunk_len", dim_chunk_len)
@@ -279,7 +279,7 @@ class SliceDimIndexer:
     stop: int
     step: int
 
-    def __init__(self, dim_sel: slice, dim_len: int, dim_chunk_len: int):
+    def __init__(self, dim_sel: slice, dim_len: int, dim_chunk_len: int) -> None:
         # normalize
         start, stop, step = dim_sel.indices(dim_len)
         if step < 1:
@@ -453,7 +453,7 @@ def __init__(
         selection: BasicSelection,
         shape: ChunkCoords,
         chunk_grid: ChunkGrid,
-    ):
+    ) -> None:
         chunk_shape = get_chunk_shape(chunk_grid)
         # handle ellipsis
         selection_normalized = replace_ellipsis(selection, shape)
@@ -509,7 +509,7 @@ class BoolArrayDimIndexer:
     nitems: int
     dim_chunk_ixs: npt.NDArray[np.intp]
 
-    def __init__(self, dim_sel: npt.NDArray[np.bool_], dim_len: int, dim_chunk_len: int):
+    def __init__(self, dim_sel: npt.NDArray[np.bool_], dim_len: int, dim_chunk_len: int) -> None:
         # check number of dimensions
         if not is_bool_array(dim_sel, 1):
             raise IndexError("Boolean arrays in an orthogonal selection must be 1-dimensional only")
@@ -626,7 +626,7 @@ def __init__(
         wraparound: bool = True,
         boundscheck: bool = True,
         order: Order = Order.UNKNOWN,
-    ):
+    ) -> None:
         # ensure 1d array
         dim_sel = np.asanyarray(dim_sel)
         if not is_integer_array(dim_sel, 1):
@@ -766,7 +766,7 @@ class OrthogonalIndexer(Indexer):
     is_advanced: bool
     drop_axes: tuple[int, ...]
 
-    def __init__(self, selection: Selection, shape: ChunkCoords, chunk_grid: ChunkGrid):
+    def __init__(self, selection: Selection, shape: ChunkCoords, chunk_grid: ChunkGrid) -> None:
         chunk_shape = get_chunk_shape(chunk_grid)
 
         # handle ellipsis
@@ -880,7 +880,9 @@ class BlockIndexer(Indexer):
     shape: ChunkCoords
     drop_axes: ChunkCoords
 
-    def __init__(self, selection: BasicSelection, shape: ChunkCoords, chunk_grid: ChunkGrid):
+    def __init__(
+        self, selection: BasicSelection, shape: ChunkCoords, chunk_grid: ChunkGrid
+    ) -> None:
         chunk_shape = get_chunk_shape(chunk_grid)
 
         # handle ellipsis
@@ -1005,7 +1007,9 @@ class CoordinateIndexer(Indexer):
     chunk_shape: ChunkCoords
     drop_axes: ChunkCoords
 
-    def __init__(self, selection: CoordinateSelection, shape: ChunkCoords, chunk_grid: ChunkGrid):
+    def __init__(
+        self, selection: CoordinateSelection, shape: ChunkCoords, chunk_grid: ChunkGrid
+    ) -> None:
         chunk_shape = get_chunk_shape(chunk_grid)
 
         cdata_shape: ChunkCoords
@@ -1122,7 +1126,7 @@ def __iter__(self) -> Iterator[ChunkProjection]:
 
 @dataclass(frozen=True)
 class MaskIndexer(CoordinateIndexer):
-    def __init__(self, selection: MaskSelection, shape: ChunkCoords, chunk_grid: ChunkGrid):
+    def __init__(self, selection: MaskSelection, shape: ChunkCoords, chunk_grid: ChunkGrid) -> None:
         # some initial normalization
         selection_normalized = cast(tuple[MaskSelection], ensure_tuple(selection))
         selection_normalized = cast(tuple[MaskSelection], replace_lists(selection_normalized))

src/zarr/registry.py

@@ -107,7 +107,7 @@ def fully_qualified_name(cls: type) -> str:
 
 
 def register_codec(key: str, codec_cls: type[Codec]) -> None:
-    if key not in __codec_registries.keys():
+    if key not in __codec_registries:
         __codec_registries[key] = Registry()
     __codec_registries[key].register(codec_cls)
 
@@ -158,7 +158,7 @@ def get_pipeline_class(reload_config: bool = False) -> type[CodecPipeline]:
     if pipeline_class:
         return pipeline_class
     raise BadConfigError(
-        f"Pipeline class '{path}' not found in registered pipelines: {list(__pipeline_registry.keys())}."
+        f"Pipeline class '{path}' not found in registered pipelines: {list(__pipeline_registry)}."
     )
 
 
@@ -172,7 +172,7 @@ def get_buffer_class(reload_config: bool = False) -> type[Buffer]:
     if buffer_class:
         return buffer_class
     raise BadConfigError(
-        f"Buffer class '{path}' not found in registered buffers: {list(__buffer_registry.keys())}."
+        f"Buffer class '{path}' not found in registered buffers: {list(__buffer_registry)}."
     )
 
 
@@ -185,7 +185,7 @@ def get_ndbuffer_class(reload_config: bool = False) -> type[NDBuffer]:
     if ndbuffer_class:
         return ndbuffer_class
     raise BadConfigError(
-        f"NDBuffer class '{path}' not found in registered buffers: {list(__ndbuffer_registry.keys())}."
+        f"NDBuffer class '{path}' not found in registered buffers: {list(__ndbuffer_registry)}."
     )
 
 

src/zarr/store/common.py

@@ -23,15 +23,14 @@ def _dereference_path(root: str, path: str) -> str:
     assert isinstance(path, str)
     root = root.rstrip("/")
     path = f"{root}/{path}" if root else path
-    path = path.rstrip("/")
-    return path
+    return path.rstrip("/")
 
 
 class StorePath:
     store: Store
     path: str
 
-    def __init__(self, store: Store, path: str | None = None):
+    def __init__(self, store: Store, path: str | None = None) -> None:
         self.store = store
         self.path = path or ""
 
@@ -265,8 +264,7 @@ async def contains_array(store_path: StorePath, zarr_format: ZarrFormat) -> bool
             except (ValueError, KeyError):
                 return False
     elif zarr_format == 2:
-        result = await (store_path / ZARRAY_JSON).exists()
-        return result
+        return await (store_path / ZARRAY_JSON).exists()
     msg = f"Invalid zarr_format provided. Got {zarr_format}, expected 2 or 3"
     raise ValueError(msg)
 

src/zarr/store/local.py

@@ -79,7 +79,7 @@ class LocalStore(Store):
 
     root: Path
 
-    def __init__(self, root: Path | str, *, mode: AccessModeLiteral = "r"):
+    def __init__(self, root: Path | str, *, mode: AccessModeLiteral = "r") -> None:
         super().__init__(mode=mode)
         if isinstance(root, str):
             root = Path(root)

src/zarr/store/memory.py

@@ -30,7 +30,7 @@ def __init__(
         store_dict: MutableMapping[str, Buffer] | None = None,
         *,
         mode: AccessModeLiteral = "r",
-    ):
+    ) -> None:
         super().__init__(mode=mode)
         if store_dict is None:
             store_dict = {}
@@ -80,8 +80,7 @@ async def get_partial_values(
         async def _get(key: str, byte_range: tuple[int, int | None]) -> Buffer | None:
             return await self.get(key, prototype=prototype, byte_range=byte_range)
 
-        vals = await concurrent_map(key_ranges, _get, limit=None)
-        return vals
+        return await concurrent_map(key_ranges, _get, limit=None)
 
     async def exists(self, key: str) -> bool:
         return key in self._store_dict
@@ -137,7 +136,7 @@ async def list_dir(self, prefix: str) -> AsyncGenerator[str, None]:
             prefix = prefix[:-1]
 
         if prefix == "":
-            keys_unique = set(k.split("/")[0] for k in self._store_dict.keys())
+            keys_unique = set(k.split("/")[0] for k in self._store_dict)
         else:
             # Our dictionary doesn't contain directory markers, but we want to include
             # a pseudo directory when there's a nested item and we're listing an
@@ -166,7 +165,7 @@ def __init__(
         store_dict: MutableMapping[str, Buffer] | None = None,
         *,
         mode: AccessModeLiteral = "r",
-    ):
+    ) -> None:
         super().__init__(mode=mode)
         if store_dict:
             self._store_dict = {k: gpu.Buffer.from_buffer(store_dict[k]) for k in iter(store_dict)}

src/zarr/store/remote.py

@@ -39,7 +39,7 @@ def __init__(
         mode: AccessModeLiteral = "r",
         path: str = "/",
         allowed_exceptions: tuple[type[Exception], ...] = ALLOWED_EXCEPTIONS,
-    ):
+    ) -> None:
         """
         Parameters
         ----------
@@ -49,6 +49,7 @@ def __init__(
             keys, rather than some other IO failure
         storage_options: passed on to fsspec to make the filesystem instance. If url is a UPath,
             this must not be used.
+
         """
         super().__init__(mode=mode)
         self.fs = fs

src/zarr/testing/strategies.py

@@ -171,5 +171,4 @@ def key_ranges(keys: SearchStrategy = node_names) -> SearchStrategy[list]:
         st.none() | st.integers(min_value=0), st.none() | st.integers(min_value=0)
     )
     key_tuple = st.tuples(keys, byte_ranges)
-    key_range_st = st.lists(key_tuple, min_size=1, max_size=10)
-    return key_range_st
+    return st.lists(key_tuple, min_size=1, max_size=10)