Apply ruff/flake8-annotations rule ANN204

ANN204 Missing return type annotation for special method `__init__`

Author: DimitriPapadopoulos

src/zarr/abc/store.py

@@ -35,7 +35,7 @@ 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/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"))
 

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

@@ -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)
 

src/zarr/core/indexing.py

@@ -55,7 +55,7 @@ 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}"
 
 
@@ -247,7 +247,7 @@ 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)
@@ -271,7 +271,7 @@ 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:
@@ -445,7 +445,7 @@ 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)
@@ -501,7 +501,7 @@ 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")
@@ -618,7 +618,7 @@ 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):
@@ -758,7 +758,7 @@ 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
@@ -865,7 +865,9 @@ 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
@@ -990,7 +992,9 @@ 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
@@ -1107,7 +1111,7 @@ 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/store/common.py

@@ -31,7 +31,7 @@ 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 ""
 

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)