8000 ENH: Add a typing protocol for representing nested sequences by BvB93 · Pull Request #19894 · numpy/numpy · GitHub
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Merged
merged 3 commits into from
Sep 20, 2021
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ENH: Add a typing protocol for representing nested sequences #19894

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5580a4c
ENH: Add a protocol for representing nested sequences
Jan 12, 2021
a315d5e
MAINT: Replace the old `_NestedSequence` union and remove `_Recursive…
Jan 12, 2021
0ae66c2
TST: Added tests for `NestedSequence`
Jan 12, 2021
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MAINT: Replace the old _NestedSequence union and remove `_Recursive… 
…Sequence`
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Bas van Beek committed Sep 19, 2021
commit a315d5ee5ab56f434fdf196c3a9fe1dd7e72e5bd
308 changes: 61 additions & 247 deletions numpy/__init__.pyi
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4 changes: 2 additions & 2 deletions numpy/core/multiarray.pyi
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Expand Up @@ -65,7 +65,7 @@ from numpy.typing import (
NDArray,
ArrayLike,
_SupportsArray,
_NestedSequence,
_FiniteNestedSequence,
_ArrayLikeBool_co,
_ArrayLikeUInt_co,
_ArrayLikeInt_co,
Expand All @@ -91,7 +91,7 @@ _DTypeLike = Union[
Type[_SCT],
_SupportsDType[dtype[_SCT]],
]
_ArrayLike = _NestedSequence[_SupportsArray[dtype[_SCT]]]
_ArrayLike = _FiniteNestedSequence[_SupportsArray[dtype[_SCT]]]
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This is used with typevars in def func(a: _ArrayLike[_T]) -> NDArray[_T]: ...-esque expressions, so unfortunately we can't use the new fancy protocol here.


# Valid time units
_UnitKind = L[
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4 changes: 2 additions & 2 deletions numpy/core/shape_base.pyi
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@@ -1,12 +1,12 @@
from typing import TypeVar, overload, List, Sequence, Any, SupportsIndex

from numpy import generic, dtype
from numpy.typing import ArrayLike, NDArray, _NestedSequence, _SupportsArray
from numpy.typing import ArrayLike, NDArray, _FiniteNestedSequence, _SupportsArray

_SCT = TypeVar("_SCT", bound=generic)
_ArrayType = TypeVar("_ArrayType", bound=NDArray[Any])

_ArrayLike = _NestedSequence[_SupportsArray[dtype[_SCT]]]
_ArrayLike = _FiniteNestedSequence[_SupportsArray[dtype[_SCT]]]

__all__: List[str]

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4 changes: 2 additions & 2 deletions numpy/lib/arraypad.pyi
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Expand Up @@ -15,7 +15,7 @@ from numpy.typing import (
ArrayLike,
NDArray,
_ArrayLikeInt,
_NestedSequence,
_FiniteNestedSequence,
_SupportsArray,
)

Expand Down Expand Up @@ -45,7 +45,7 @@ _ModeKind = L[
"empty",
]

_ArrayLike = _NestedSequence[_SupportsArray[dtype[_SCT]]]
_ArrayLike = _FiniteNestedSequence[_SupportsArray[dtype[_SCT]]]

__all__: List[str]

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18 changes: 8 additions & 10 deletions numpy/lib/index_tricks.pyi
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Expand Up @@ -33,7 +33,7 @@ from numpy.typing import (
# Arrays
ArrayLike,
_NestedSequence,
_RecursiveSequence,
_FiniteNestedSequence,
NDArray,
_ArrayLikeInt,

Expand All @@ -59,21 +59,19 @@ _ArrayType = TypeVar("_ArrayType", bound=ndarray[Any, Any])
__all__: List[str]

@overload
def ix_(*args: _NestedSequence[_SupportsDType[_DType]]) -> Tuple[ndarray[Any, _DType], ...]: ...
def ix_(*args: _FiniteNestedSequence[_SupportsDType[_DType]]) -> Tuple[ndarray[Any, _DType], ...]: ...
@overload
def ix_(*args: _NestedSequence[str]) -> Tuple[NDArray[str_], ...]: ...
def ix_(*args: str | _NestedSequence[str]) -> Tuple[NDArray[str_], ...]: ...
@overload
def ix_(*args: _NestedSequence[bytes]) -> Tuple[NDArray[bytes_], ...]: ...
def ix_(*args: bytes | _NestedSequence[bytes]) -> Tuple[NDArray[bytes_], ...]: ...
@overload
def ix_(*args: _NestedSequence[bool]) -> Tuple[NDArray[bool_], ...]: ...
def ix_(*args: bool | _NestedSequence[bool]) -> Tuple[NDArray[bool_], ...]: ...
@overload
def ix_(*args: _NestedSequence[int]) -> Tuple[NDArray[int_], ...]: ...
def ix_(*args: int | _NestedSequence[int]) -> Tuple[NDArray[int_], ...]: ...
@overload
def ix_(*args: _NestedSequence[float]) -> Tuple[NDArray[float_], ...]: ...
def ix_(*args: float | _NestedSequence[float]) -> Tuple[NDArray[float_], ...]: ...
@overload
def ix_(*args: _NestedSequence[complex]) -> Tuple[NDArray[complex_], ...]: ...
@overload
def ix_(*args: _RecursiveSequence) -> Tuple[NDArray[Any], ...]: ...
def ix_(*args: complex | _NestedSequence[complex]) -> Tuple[NDArray[complex_], ...]: ...

class nd_grid(Generic[_BoolType]):
sparse: _BoolType
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4 changes: 2 additions & 2 deletions numpy/lib/shape_base.pyi
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Expand Up @@ -17,7 +17,7 @@ from numpy.typing import (
ArrayLike,
NDArray,
_ShapeLike,
_NestedSequence,
_FiniteNestedSequence,
_SupportsDType,
_ArrayLikeBool_co,
_ArrayLikeUInt_co,
Expand All @@ -31,7 +31,7 @@ from numpy.core.shape_base import vstack

_SCT = TypeVar("_SCT", bound=generic)

_ArrayLike = _NestedSequence[_SupportsDType[dtype[_SCT]]]
_ArrayLike = _FiniteNestedSequence[_SupportsDType[dtype[_SCT]]]

# The signatures of `__array_wrap__` and `__array_prepare__` are the same;
# give them unique names for the sake of clarity
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4 changes: 2 additions & 2 deletions numpy/lib/stride_tricks.pyi
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Expand Up @@ -6,12 +6,12 @@ from numpy.typing import (
ArrayLike,
_ShapeLike,
_Shape,
_NestedSequence,
_FiniteNestedSequence,
_SupportsArray,
)

_SCT = TypeVar("_SCT", bound=generic)
_ArrayLike = _NestedSequence[_SupportsArray[dtype[_SCT]]]
_ArrayLike = _FiniteNestedSequence[_SupportsArray[dtype[_SCT]]]

__all__: List[str]

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4 changes: 2 additions & 2 deletions numpy/lib/twodim_base.pyi
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Expand Up @@ -33,7 +33,7 @@ from numpy.typing import (
_SupportsDType,
ArrayLike,
NDArray,
_NestedSequence,
_FiniteNestedSequence,
_SupportsArray,
_ArrayLikeInt_co,
_ArrayLikeFloat_co,
Expand All @@ -55,7 +55,7 @@ _DTypeLike = Union[
dtype[_SCT],
_SupportsDType[dtype[_SCT]],
]
_ArrayLike = _NestedSequence[_SupportsArray[dtype[_SCT]]]
_ArrayLike = _FiniteNestedSequence[_SupportsArray[dtype[_SCT]]]

__all__: List[str]

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4 changes: 2 additions & 2 deletions numpy/lib/type_check.pyi
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Expand Up @@ -28,7 +28,7 @@ from numpy.typing import (
_64Bit,
_SupportsDType,
_ScalarLike_co,
_NestedSequence,
_FiniteNestedSequence,
_SupportsArray,
_DTypeLikeComplex,
)
Expand All @@ -39,7 +39,7 @@ _SCT = TypeVar("_SCT", bound=generic)
_NBit1 = TypeVar("_NBit1", bound=NBitBase)
_NBit2 = TypeVar("_NBit2", bound=NBitBase)

_ArrayLike = _NestedSequence[_SupportsArray[dtype[_SCT]]]
_ArrayLike = _FiniteNestedSequence[_SupportsArray[dtype[_SCT]]]

class _SupportsReal(Protocol[_T_co]):
@property
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4 changes: 2 additions & 2 deletions numpy/typing/__init__.py
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Expand Up @@ -219,6 +219,7 @@ class _32Bit(_64Bit): ... # type: ignore[misc]
class _16Bit(_32Bit): ... # type: ignore[misc]
class _8Bit(_16Bit): ... # type: ignore[misc]


from ._nested_sequence import _NestedSequence
from ._nbit import (
_NBitByte,
Expand Down Expand Up @@ -306,8 +307,7 @@ class _8Bit(_16Bit): ... # type: ignore[misc]
from ._array_like import (
ArrayLike as ArrayLike,
_ArrayLike,
_NestedSequence,
_RecursiveSequence,
_FiniteNestedSequence,
_SupportsArray,
_ArrayLikeInt,
_ArrayLikeBool_co,
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33 changes: 21 additions & 12 deletions numpy/typing/_array_like.py
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Expand Up @@ -18,6 +18,7 @@
str_,
bytes_,
)
from ._nested_sequence import _NestedSequence

_T = TypeVar("_T")
_ScalarType = TypeVar("_ScalarType", bound=generic)
Expand All @@ -32,21 +33,23 @@
class _SupportsArray(Protocol[_DType_co]):
def __array__(self) -> ndarray[Any, _DType_co]: ...

# TODO: Wait for support for recursive types
_NestedSequence = Union[

# TODO: Wait until mypy supports recursive objects in combination with typevars
_FiniteNestedSequence = Union[
_T,
Sequence[_T],
Sequence[Sequence[_T]],
Sequence[Sequence[Sequence[_T]]],
Sequence[Sequence[Sequence[Sequence[_T]]]],
]
_RecursiveSequence = Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]]

# A union representing array-like objects; consists of two typevars:
# One representing types that can be parametrized w.r.t. `np.dtype`
# and another one for the rest
_ArrayLike = Union[
_SupportsArray[_DType],
_NestedSequence[_SupportsArray[_DType]],
_T,
_NestedSequence[_T],
]

Expand All @@ -57,12 +60,9 @@ def __array__(self) -> ndarray[Any, _DType_co]: ...
# is resolved. See also the mypy issue:
#
# https://github.com/python/typing/issues/593
ArrayLike = Union[
_RecursiveSequence,
_ArrayLike[
dtype,
Union[bool, int, float, complex, str, bytes]
],
ArrayLike = _ArrayLike[
dtype,
Union[bool, int, float, complex, str, bytes],
]

# `ArrayLike<X>_co`: array-like objects that can be coerced into `X`
Expand Down Expand Up @@ -95,10 +95,19 @@ def __array__(self) -> ndarray[Any, _DType_co]: ...
"dtype[Union[bool_, integer[Any], timedelta64]]",
Union[bool, int],
]
_ArrayLikeDT64_co = _NestedSequence[_SupportsArray["dtype[datetime64]"]]
_ArrayLikeObject_co = _NestedSequence[_SupportsArray["dtype[object_]"]]
_ArrayLikeDT64_co = Union[
_SupportsArray["dtype[datetime64]"],
_NestedSequence[_SupportsArray["dtype[datetime64]"]],
]
_ArrayLikeObject_co = Union[
_SupportsArray["dtype[object_]"],
_NestedSequence[_SupportsArray["dtype[object_]"]],
]

_ArrayLikeVoid_co = _NestedSequence[_SupportsArray["dtype[void]"]]
_ArrayLikeVoid_co = Union[
_SupportsArray["dtype[void]"],
_NestedSequence[_SupportsArray["dtype[void]"]],
]
_ArrayLikeStr_co = _ArrayLike[
"dtype[str_]",
str,
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4 changes: 2 additions & 2 deletions numpy/typing/tests/data/fail/comparisons.py
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Expand Up @@ -22,7 +22,7 @@
AR_M > AR_m # E: Unsupported operand types

# Unfortunately `NoReturn` errors are not the most descriptive
_1 = AR_i > str() # E: Need type annotation
_1 = AR_i > str() # E: No overload variant
_2 = AR_i > bytes() # E: Need type annotation
_3 = str() > AR_M # E: Need type annotation
_3 = str() > AR_M # E: Unsupported operand types
_4 = bytes() > AR_M # E: Need type annotation
2 changes: 1 addition & 1 deletion numpy/typing/tests/data/fail/multiarray.py
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Expand Up @@ -42,7 +42,7 @@ def func(a: int) -> None: ...

np.busday_offset("2012", 10) # E: incompatible type

np.datetime_as_string("2012") # E: incompatible type
np.datetime_as_string("2012") # E: No overload variant

np.compare_chararrays("a", b"a", "==", False) # E: No overload variant

Expand Down
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