Fix mypy 1.16 errors

error: Unused "type: ignore" comment  [unused-ignore]

Author: DimitriPapadopoulos

src/zarr/api/asynchronous.py

@@ -140,7 +140,7 @@ def _like_args(a: ArrayLike, kwargs: dict[str, Any]) -> dict[str, Any]:
         else:
             # TODO: Remove type: ignore statement when type inference improves.
             # mypy cannot correctly infer the type of a.metadata here for some reason.
-            new["codecs"] = a.metadata.codecs  # type: ignore[unreachable]
+            new["codecs"] = a.metadata.codecs
 
     else:
         # TODO: set default values compressor/codecs

src/zarr/codecs/bytes.py

@@ -107,7 +107,7 @@ async def _encode_single(
         ):
             # type-ignore is a numpy bug
             # see https://github.com/numpy/numpy/issues/26473
-            new_dtype = chunk_array.dtype.newbyteorder(self.endian.name)  # type: ignore[arg-type]
+            new_dtype = chunk_array.dtype.newbyteorder(self.endian.name)
             chunk_array = chunk_array.astype(new_dtype)
 
         nd_array = chunk_array.as_ndarray_like()

src/zarr/core/array.py

@@ -782,7 +782,7 @@ def _create_metadata_v2(
         if dimension_separator is None:
             dimension_separator = "."
         if fill_value is None:
-            fill_value = dtype.default_scalar()  # type: ignore[assignment]
+            fill_value = dtype.default_scalar()
         return ArrayV2Metadata(
             shape=shape,
             dtype=dtype,

src/zarr/core/buffer/core.py

@@ -93,7 +93,7 @@ def ravel(self, order: Literal["K", "A", "C", "F"] = ...) -> Self: ...
 
     def all(self) -> bool: ...
 
-    def __eq__(self, other: object) -> Self:  # type: ignore[explicit-override, override]
+    def __eq__(self, other: object) -> Self:
         """Element-wise equal
 
         Notes
@@ -266,7 +266,7 @@ def as_buffer_like(self) -> BytesLike:
         -------
             An object that implements the Python buffer protocol
         """
-        return memoryview(self.as_numpy_array())  # type: ignore[arg-type]
+        return memoryview(self.as_numpy_array())
 
     def to_bytes(self) -> bytes:
         """Returns the buffer as `bytes` (host memory).

src/zarr/core/dtype/__init__.py

@@ -114,7 +114,7 @@
 
 for dtype in ANY_DTYPE:
     # mypy does not know that all the elements of ANY_DTYPE are subclasses of ZDType
-    data_type_registry.register(dtype._zarr_v3_name, dtype)  # type: ignore[arg-type]
+    data_type_registry.register(dtype._zarr_v3_name, dtype)
 
 
 # TODO: find a better name for this function
@@ -159,4 +159,4 @@ def parse_data_type(
         return get_data_type_from_json(dtype_spec, zarr_format=3)
     # otherwise, we have either a numpy dtype string, or a zarr v3 dtype string, and in either case
     # we can create a numpy dtype from it, and do the dtype inference from that
-    return get_data_type_from_native_dtype(dtype_spec)  # type: ignore[arg-type]
+    return get_data_type_from_native_dtype(dtype_spec)

src/zarr/core/dtype/npy/bytes.py

@@ -152,7 +152,7 @@ class RawBytes(ZDType[np.dtypes.VoidDType[int], np.void], HasLength, HasItemSize
     # np.dtypes.VoidDType is specified in an odd way in numpy
     # it cannot be used to create instances of the dtype
     # so we have to tell mypy to ignore this here
-    dtype_cls = np.dtypes.VoidDType  # type: ignore[assignment]
+    dtype_cls = np.dtypes.VoidDType
     _zarr_v3_name: ClassVar[Literal["raw_bytes"]] = "raw_bytes"
 
     @classmethod
@@ -176,14 +176,14 @@ def _check_native_dtype(
         Bool
             True if the dtype matches, False otherwise.
         """
-        return cls.dtype_cls is type(dtype) and dtype.fields is None  # type: ignore[has-type]
+        return cls.dtype_cls is type(dtype) and dtype.fields is None
 
     @classmethod
     def from_native_dtype(cls, dtype: TBaseDType) -> Self:
         if cls._check_native_dtype(dtype):
             return cls(length=dtype.itemsize)
         raise DataTypeValidationError(
-            f"Invalid data type: {dtype}. Expected an instance of {cls.dtype_cls}"  # type: ignore[has-type]
+            f"Invalid data type: {dtype}. Expected an instance of {cls.dtype_cls}"
         )
 
     def to_native_dtype(self) -> np.dtypes.VoidDType[int]:

src/zarr/core/dtype/npy/common.py

@@ -138,7 +138,7 @@ def get_endianness_from_numpy_dtype(dtype: np.dtype[np.generic]) -> EndiannessSt
     """
     endianness = dtype.byteorder
     if dtype.byteorder in NUMPY_ENDIANNESS_STR:
-        return endianness_from_numpy_str(endianness)  # type: ignore [arg-type]
+        return endianness_from_numpy_str(endianness)
     raise ValueError(f"The dtype {dtype} has an unsupported endianness: {endianness}")
 
 

src/zarr/core/dtype/npy/complex.py

@@ -54,7 +54,7 @@ def from_native_dtype(cls, dtype: TBaseDType) -> Self:
 
     def to_native_dtype(self) -> TComplexDType_co:
         byte_order = endianness_to_numpy_str(self.endianness)
-        return self.dtype_cls().newbyteorder(byte_order)  # type: ignore[return-value]
+        return self.dtype_cls().newbyteorder(byte_order)
 
     @classmethod
     def _check_json_v2(cls, data: DTypeJSON) -> TypeGuard[DTypeConfig_V2[str, None]]:
@@ -118,7 +118,7 @@ def _check_scalar(self, data: object) -> TypeGuard[ComplexLike]:
         return isinstance(data, ComplexLike)
 
     def _cast_scalar_unchecked(self, data: ComplexLike) -> TComplexScalar_co:
-        return self.to_native_dtype().type(data)  # type: ignore[return-value]
+        return self.to_native_dtype().type(data)
 
     def cast_scalar(self, data: object) -> TComplexScalar_co:
         if self._check_scalar(data):

src/zarr/core/dtype/npy/float.py

@@ -48,7 +48,7 @@ def from_native_dtype(cls, dtype: TBaseDType) -> Self:
 
     def to_native_dtype(self) -> TFloatDType_co:
         byte_order = endianness_to_numpy_str(self.endianness)
-        return self.dtype_cls().newbyteorder(byte_order)  # type: ignore[return-value]
+        return self.dtype_cls().newbyteorder(byte_order)
 
     @classmethod
     def _check_json_v2(cls, data: DTypeJSON) -> TypeGuard[DTypeConfig_V2[str, None]]:
@@ -112,7 +112,7 @@ def _check_scalar(self, data: object) -> TypeGuard[FloatLike]:
         return isinstance(data, FloatLike)
 
     def _cast_scalar_unchecked(self, data: FloatLike) -> TFloatScalar_co:
-        return self.to_native_dtype().type(data)  # type: ignore[return-value]
+        return self.to_native_dtype().type(data)
 
     def cast_scalar(self, data: object) -> TFloatScalar_co:
         if self._check_scalar(data):

src/zarr/core/dtype/npy/int.py

@@ -84,7 +84,7 @@ def _cast_scalar_unchecked(self, data: IntLike) -> TIntScalar_co:
         """
         Create an integer without any type checking of the input.
         """
-        return self.to_native_dtype().type(data)  # type: ignore[return-value]
+        return self.to_native_dtype().type(data)
 
     def cast_scalar(self, data: object) -> TIntScalar_co:
         if self._check_scalar(data):