diff options
| -rw-r--r-- | numpy/__init__.pyi | 37 | ||||
| -rw-r--r-- | numpy/typing/tests/data/reveal/dtype.py | 51 |
2 files changed, 50 insertions, 38 deletions
diff --git a/numpy/__init__.pyi b/numpy/__init__.pyi index 7efe73010..95c70d8c7 100644 --- a/numpy/__init__.pyi +++ b/numpy/__init__.pyi @@ -5,7 +5,7 @@ import mmap import array as _array import datetime as dt from abc import abstractmethod -from types import TracebackType +from types import TracebackType, MappingProxyType from contextlib import ContextDecorator from numpy.core._internal import _ctypes @@ -897,7 +897,7 @@ _DTypeScalar_co = TypeVar("_DTypeScalar_co", covariant=True, bound=generic) _ByteOrder = L["S", "<", ">", "=", "|", "L", "B", "N", "I"] class dtype(Generic[_DTypeScalar_co]): - names: Optional[Tuple[str, ...]] + names: None | Tuple[str, ...] # Overload for subclass of generic @overload def __new__( @@ -920,7 +920,7 @@ class dtype(Generic[_DTypeScalar_co]): @overload def __new__(cls, dtype: Type[int], align: bool = ..., copy: bool = ...) -> dtype[int_]: ... @overload - def __new__(cls, dtype: Optional[Type[float]], align: bool = ..., copy: bool = ...) -> dtype[float_]: ... + def __new__(cls, dtype: None | Type[float], align: bool = ..., copy: bool = ...) -> dtype[float_]: ... @overload def __new__(cls, dtype: Type[complex], align: bool = ..., copy: bool = ...) -> dtype[complex_]: ... @overload @@ -1051,19 +1051,23 @@ class dtype(Generic[_DTypeScalar_co]): @overload def __getitem__(self: dtype[void], key: List[str]) -> dtype[void]: ... @overload - def __getitem__(self: dtype[void], key: Union[str, int]) -> dtype[Any]: ... + def __getitem__(self: dtype[void], key: str | SupportsIndex) -> dtype[Any]: ... - # NOTE: In the future 1-based multiplications will also yield `void` dtypes - @overload - def __mul__(self, value: L[0]) -> None: ... # type: ignore[misc] + # NOTE: In the future 1-based multiplications will also yield `flexible` dtypes @overload def __mul__(self: _DType, value: L[1]) -> _DType: ... @overload - def __mul__(self, value: int) -> dtype[void]: ... + def __mul__(self: _FlexDType, value: SupportsIndex) -> _FlexDType: ... + @overload + def __mul__(self, value: SupportsIndex) -> dtype[void]: ... # NOTE: `__rmul__` seems to be broken when used in combination with - # literals as of mypy 0.800. Set the return-type to `Any` for now. - def __rmul__(self, value: int) -> Any: ... + # literals as of mypy 0.902. Set the return-type to `dtype[Any]` for + # now for non-flexible dtypes. + @overload + def __rmul__(self: _FlexDType, value: SupportsIndex) -> _FlexDType: ... + @overload + def __rmul__(self, value: SupportsIndex) -> dtype[Any]: ... def __gt__(self, other: DTypeLike) -> bool: ... def __ge__(self, other: DTypeLike) -> bool: ... @@ -1072,17 +1076,17 @@ class dtype(Generic[_DTypeScalar_co]): @property def alignment(self) -> int: ... @property - def base(self: _DType) -> _DType: ... + def base(self) -> dtype[Any]: ... @property def byteorder(self) -> str: ... @property def char(self) -> str: ... @property - def descr(self) -> List[Union[Tuple[str, str], Tuple[str, str, _Shape]]]: ... + def descr(self) -> List[Tuple[str, str] | Tuple[str, str, _Shape]]: ... @property def fields( self, - ) -> Optional[Mapping[str, Union[Tuple[dtype[Any], int], Tuple[dtype[Any], int, Any]]]]: ... + ) -> None | MappingProxyType[str, Tuple[dtype[Any], int] | Tuple[dtype[Any], int, Any]]: ... @property def flags(self) -> int: ... @property @@ -1098,19 +1102,17 @@ class dtype(Generic[_DTypeScalar_co]): @property def kind(self) -> str: ... @property - def metadata(self) -> Optional[Mapping[str, Any]]: ... + def metadata(self) -> None | MappingProxyType[str, Any]: ... @property def name(self) -> str: ... @property - def names(self) -> Optional[Tuple[str, ...]]: ... - @property def num(self) -> int: ... @property def shape(self) -> _Shape: ... @property def ndim(self) -> int: ... @property - def subdtype(self: _DType) -> Optional[Tuple[_DType, _Shape]]: ... + def subdtype(self) -> None | Tuple[dtype[Any], _Shape]: ... def newbyteorder(self: _DType, __new_order: _ByteOrder = ...) -> _DType: ... # Leave str and type for end to avoid having to use `builtins.str` # everywhere. See https://github.com/python/mypy/issues/3775 @@ -1594,6 +1596,7 @@ class _ArrayOrScalarCommon: _DType = TypeVar("_DType", bound=dtype[Any]) _DType_co = TypeVar("_DType_co", covariant=True, bound=dtype[Any]) +_FlexDType = TypeVar("_FlexDType", bound=dtype[flexible]) # TODO: Set the `bound` to something more suitable once we # have proper shape support diff --git a/numpy/typing/tests/data/reveal/dtype.py b/numpy/typing/tests/data/reveal/dtype.py index 215d89ead..eb1489bf3 100644 --- a/numpy/typing/tests/data/reveal/dtype.py +++ b/numpy/typing/tests/data/reveal/dtype.py @@ -1,7 +1,8 @@ import numpy as np -dtype_obj: np.dtype[np.str_] -void_dtype_obj: np.dtype[np.void] +dtype_U: np.dtype[np.str_] +dtype_V: np.dtype[np.void] +dtype_i8: np.dtype[np.int64] reveal_type(np.dtype(np.float64)) # E: numpy.dtype[{float64}] reveal_type(np.dtype(np.int64)) # E: numpy.dtype[{int64}] @@ -36,22 +37,30 @@ reveal_type(np.dtype("S8")) # E: numpy.dtype reveal_type(np.dtype(("U", 10))) # E: numpy.dtype[numpy.void] # Methods and attributes -reveal_type(dtype_obj.base) # E: numpy.dtype[numpy.str_] -reveal_type(dtype_obj.subdtype) # E: Union[Tuple[numpy.dtype[numpy.str_], builtins.tuple[builtins.int]], None] -reveal_type(dtype_obj.newbyteorder()) # E: numpy.dtype[numpy.str_] -reveal_type(dtype_obj.type) # E: Type[numpy.str_] -reveal_type(dtype_obj.name) # E: str -reveal_type(dtype_obj.names) # E: Union[builtins.tuple[builtins.str], None] - -reveal_type(dtype_obj * 0) # E: None -reveal_type(dtype_obj * 1) # E: numpy.dtype[numpy.str_] -reveal_type(dtype_obj * 2) # E: numpy.dtype[numpy.void] - -reveal_type(0 * dtype_obj) # E: Any -reveal_type(1 * dtype_obj) # E: Any -reveal_type(2 * dtype_obj) # E: Any - -reveal_type(void_dtype_obj["f0"]) # E: numpy.dtype[Any] -reveal_type(void_dtype_obj[0]) # E: numpy.dtype[Any] -reveal_type(void_dtype_obj[["f0", "f1"]]) # E: numpy.dtype[numpy.void] -reveal_type(void_dtype_obj[["f0"]]) # E: numpy.dtype[numpy.void] +reveal_type(dtype_U.base) # E: numpy.dtype[Any] +reveal_type(dtype_U.subdtype) # E: Union[None, Tuple[numpy.dtype[Any], builtins.tuple[builtins.int]]] +reveal_type(dtype_U.newbyteorder()) # E: numpy.dtype[numpy.str_] +reveal_type(dtype_U.type) # E: Type[numpy.str_] +reveal_type(dtype_U.name) # E: str +reveal_type(dtype_U.names) # E: Union[None, builtins.tuple[builtins.str]] + +reveal_type(dtype_U * 0) # E: numpy.dtype[numpy.str_] +reveal_type(dtype_U * 1) # E: numpy.dtype[numpy.str_] +reveal_type(dtype_U * 2) # E: numpy.dtype[numpy.str_] + +reveal_type(dtype_i8 * 0) # E: numpy.dtype[numpy.void] +reveal_type(dtype_i8 * 1) # E: numpy.dtype[{int64}] +reveal_type(dtype_i8 * 2) # E: numpy.dtype[numpy.void] + +reveal_type(0 * dtype_U) # E: numpy.dtype[numpy.str_] +reveal_type(1 * dtype_U) # E: numpy.dtype[numpy.str_] +reveal_type(2 * dtype_U) # E: numpy.dtype[numpy.str_] + +reveal_type(0 * dtype_i8) # E: numpy.dtype[Any] +reveal_type(1 * dtype_i8) # E: numpy.dtype[Any] +reveal_type(2 * dtype_i8) # E: numpy.dtype[Any] + +reveal_type(dtype_V["f0"]) # E: numpy.dtype[Any] +reveal_type(dtype_V[0]) # E: numpy.dtype[Any] +reveal_type(dtype_V[["f0", "f1"]]) # E: numpy.dtype[numpy.void] +reveal_type(dtype_V[["f0"]]) # E: numpy.dtype[numpy.void] |