Add type hinting for numeric.py (#38)

* Add type hinting for numeric.py

* Code cleanup using Black

* Add ByteString dependency

* Replace default values with "..." to satisfy Flake8

* Add core/numerictypes.pyi

* Make _ArrayLike TypeVar a lot simpler since an array_like can be just about anything.

Author: johanvergeer

.gitignore

@@ -2,3 +2,5 @@
 .pytest_cache
 __pycache__
 numpy_stubs.egg-info/
+venv
+.idea

numpy-stubs/__init__.pyi

@@ -5,6 +5,7 @@ import datetime as dt
 from numpy.core._internal import _ctypes
 from typing import (
     Any,
+    ByteString,
     Container,
     Dict,
     IO,
@@ -82,6 +83,8 @@ _DtypeLike = Union[
 
 _NdArraySubClass = TypeVar("_NdArraySubClass", bound=ndarray)
 
+_ArrayLike = TypeVar("_ArrayLike")
+
 class dtype:
     names: Optional[Tuple[str, ...]]
     def __init__(

numpy-stubs/core/numeric.pyi

@@ -0,0 +1,111 @@
+from types import ModuleType
+from typing import (
+    Sequence,
+    Optional,
+    TypeVar,
+    Union,
+    Tuple,
+    List,
+    Iterable,
+    Callable,
+    Any,
+)
+
+from numpy import ndarray, dtype, _ArrayLike, _ShapeLike
+
+_T = TypeVar("_T")
+
+def zeros_like(
+    a: _ArrayLike,
+    dtype: Optional[dtype] = ...,
+    order: str = ...,
+    subok: bool = ...,
+    shape: Optional[Union[int, Sequence[int]]] = ...,
+) -> ndarray[int]: ...
+def ones(
+    shape: _ShapeLike, dtype: Optional[dtype] = ..., order: str = ...
+) -> ndarray[int]: ...
+def ones_like(
+    a: _ArrayLike,
+    dtype: Optional[dtype] = ...,
+    order: str = ...,
+    subok: bool = ...,
+    shape: Optional[_ShapeLike] = ...,
+) -> ndarray[int]: ...
+def full(
+    shape: _ShapeLike, fill_value: _T, dtype: Optional[dtype] = ..., order: str = ...
+) -> ndarray[_T]: ...
+def full_like(
+    a: _ArrayLike,
+    fill_value: _T,
+    dtype: Optional[dtype] = ...,
+    order: str = ...,
+    subok: bool = ...,
+    shape: Optional[_ShapeLike] = ...,
+) -> ndarray[_T]: ...
+def count_nonzero(
+    a: _ArrayLike, axis: Optional[Union[int, Tuple[int], Tuple[int, int]]] = ...
+) -> Union[int, ndarray[int]]: ...
+def isfortran(a: ndarray) -> bool: ...
+def argwhere(a: _ArrayLike) -> ndarray: ...
+def flatnonzero(a: _ArrayLike) -> ndarray: ...
+def correlate(a: _ArrayLike, v: _ArrayLike, mode: str = ...) -> ndarray: ...
+def convolve(a: _ArrayLike, v: _ArrayLike, mode: str = ...) -> ndarray: ...
+def outer(a: _ArrayLike, b: _ArrayLike, out: ndarray = ...) -> ndarray: ...
+def tensordot(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    axes: Union[
+        int, Tuple[int, int], Tuple[Tuple[int, int], ...], Tuple[List[int, int], ...]
+    ] = ...,
+) -> ndarray: ...
+def roll(
+    a: _ArrayLike,
+    shift: Union[int, Tuple[int, ...]],
+    axis: Optional[Union[int, Tuple[int, ...]]] = ...,
+) -> _T: ...
+def rollaxis(a: _ArrayLike, axis: int, start: int = ...) -> ndarray: ...
+def normalize_axis_tuple(
+    axis: Union[int, Iterable[int]],
+    ndim: int,
+    argname: Optional[str] = ...,
+    allow_duplicate: bool = ...,
+) -> Tuple[int, ...]: ...
+def moveaxis(
+    a: ndarray,
+    source: Union[int, Sequence[int]],
+    destination: Union[int, Sequence[int]],
+) -> ndarray: ...
+def cross(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    axisa: int = ...,
+    axisb: int = ...,
+    axisc: int = ...,
+    axis: Optional[int] = ...,
+) -> ndarray: ...
+def indices(
+    dimensions: Sequence[int], dtype: dtype = ..., sparse: bool = ...
+) -> Union[ndarray, Tuple[ndarray, ...]]: ...
+def fromfunction(function: Callable, shape: Tuple[int, int], **kwargs) -> Any: ...
+def isscalar(element: Any) -> bool: ...
+def binary_repr(num: int, width: Optional[int] = ...) -> str: ...
+def base_repr(number: int, base: int = ..., padding: int = ...) -> str: ...
+def identity(n: int, dtype: Optional[dtype] = ...) -> ndarray: ...
+def allclose(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    rtol: float = ...,
+    atol: float = ...,
+    equal_nan: bool = ...,
+) -> bool: ...
+def isclose(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    rtol: float = ...,
+    atol: float = ...,
+    equal_nan: bool = ...,
+) -> _ArrayLike: ...
+def array_equal(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
+def array_equiv(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
+def extend_all(module: ModuleType): ...

numpy-stubs/core/numerictypes.pyi

@@ -0,0 +1,20 @@
+from typing import Any, Optional, Union, Tuple, List
+
+from numpy import dtype
+
+def maximum_sctype(t: dtype) -> dtype: ...
+def issctype(rep: Any) -> bool: ...
+def obj2sctype(rep: Any, default: Optional[Any] = ...) -> type: ...
+def issubclass_(
+    arg1: type, arg2: Union[type, Tuple[Union[type, Tuple], ...]]
+) -> bool: ...
+def issubsctype(
+    arg1: type, arg2: Union[type, Tuple[Union[type, Tuple], ...]]
+) -> bool: ...
+def issubdtype(
+    arg1: Union[object, type], arg2: Union[type, Tuple[Union[type, Tuple], ...]]
+) -> bool: ...
+def sctype2char(sctype: Any) -> str: ...
+def find_common_type(
+    array_types: Union[dtype, List[dtype]], scalar_types: Union[dtype, List[dtype]]
+) -> dtype: ...