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Commit 9772bea

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rgommersrgommers
authored
Merge pull request #18236 from BvB93/dtype-like
ENH: Add aliases for commonly used dtype-like objects
2 parents b969f8c + d788788 commit 9772bea
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‎numpy/__init__.pyi

Copy file name to clipboardExpand all lines: numpy/__init__.pyi
+2-3Lines changed: 2 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -682,14 +682,13 @@ class dtype(Generic[_DTypeScalar_co]):
682682
align: bool = ...,
683683
copy: bool = ...,
684684
) -> dtype[_DTypeScalar_co]: ...
685-
# TODO: handle _SupportsDType better
686685
@overload
687686
def __new__(
688687
cls,
689-
dtype: _SupportsDType,
688+
dtype: _SupportsDType[dtype[_DTypeScalar_co]],
690689
align: bool = ...,
691690
copy: bool = ...,
692-
) -> dtype[Any]: ...
691+
) -> dtype[_DTypeScalar_co]: ...
693692
# Handle strings that can't be expressed as literals; i.e. s1, s2, ...
694693
@overload
695694
def __new__(

‎numpy/typing/__init__.py

Copy file name to clipboardExpand all lines: numpy/typing/__init__.py
+16-1Lines changed: 16 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -297,7 +297,22 @@ class _8Bit(_16Bit): ... # type: ignore[misc]
297297
_VoidLike_co,
298298
)
299299
from ._shape import _Shape, _ShapeLike
300-
from ._dtype_like import _SupportsDType, _VoidDTypeLike, DTypeLike as DTypeLike
300+
from ._dtype_like import (
301+
DTypeLike as DTypeLike,
302+
_SupportsDType,
303+
_VoidDTypeLike,
304+
_DTypeLikeBool,
305+
_DTypeLikeUInt,
306+
_DTypeLikeInt,
307+
_DTypeLikeFloat,
308+
_DTypeLikeComplex,
309+
_DTypeLikeTD64,
310+
_DTypeLikeDT64,
311+
_DTypeLikeObject,
312+
_DTypeLikeVoid,
313+
_DTypeLikeStr,
314+
_DTypeLikeBytes,
315+
)
301316
from ._array_like import (
302317
ArrayLike as ArrayLike,
303318
_ArrayLike,

‎numpy/typing/_dtype_like.py

Copy file name to clipboardExpand all lines: numpy/typing/_dtype_like.py
+155-6Lines changed: 155 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,7 @@
11
import sys
2-
from typing import Any, List, Sequence, Tuple, Union, TYPE_CHECKING
2+
from typing import Any, List, Sequence, Tuple, Union, Type, TypeVar, TYPE_CHECKING
33

4-
from numpy import dtype
4+
import numpy as np
55
from ._shape import _ShapeLike
66

77
if sys.version_info >= (3, 8):
@@ -15,6 +15,48 @@
1515
else:
1616
HAVE_PROTOCOL = True
1717

18+
from ._char_codes import (
19+
_BoolCodes,
20+
_UInt8Codes,
21+
_UInt16Codes,
22+
_UInt32Codes,
23+
_UInt64Codes,
24+
_Int8Codes,
25+
_Int16Codes,
26+
_Int32Codes,
27+
_Int64Codes,
28+
_Float16Codes,
29+
_Float32Codes,
30+
_Float64Codes,
31+
_Complex64Codes,
32+
_Complex128Codes,
33+
_ByteCodes,
34+
_ShortCodes,
35+
_IntCCodes,
36+
_IntPCodes,
37+
_IntCodes,
38+
_LongLongCodes,
39+
_UByteCodes,
40+
_UShortCodes,
41+
_UIntCCodes,
42+
_UIntPCodes,
43+
_UIntCodes,
44+
_ULongLongCodes,
45+
_HalfCodes,
46+
_SingleCodes,
47+
_DoubleCodes,
48+
_LongDoubleCodes,
49+
_CSingleCodes,
50+
_CDoubleCodes,
51+
_CLongDoubleCodes,
52+
_DT64Codes,
53+
_TD64Codes,
54+
_StrCodes,
55+
_BytesCodes,
56+
_VoidCodes,
57+
_ObjectCodes,
58+
)
59+
1860
_DTypeLikeNested = Any # TODO: wait for support for recursive types
1961

2062
if TYPE_CHECKING or HAVE_PROTOCOL:
@@ -30,9 +72,12 @@ class _DTypeDict(_DTypeDictBase, total=False):
3072
itemsize: int
3173
aligned: bool
3274

75+
_DType_co = TypeVar("_DType_co", covariant=True, bound=np.dtype)
76+
3377
# A protocol for anything with the dtype attribute
34-
class _SupportsDType(Protocol):
35-
dtype: _DTypeLikeNested
78+
class _SupportsDType(Protocol[_DType_co]):
79+
@property
80+
def dtype(self) -> _DType_co: ...
3681

3782
else:
3883
_DTypeDict = Any
@@ -61,13 +106,13 @@ class _SupportsDType(Protocol):
61106
# Anything that can be coerced into numpy.dtype.
62107
# Reference: https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html
63108
DTypeLike = Union[
64-
dtype,
109+
np.dtype,
65110
# default data type (float64)
66111
None,
67112
# array-scalar types and generic types
68113
type, # TODO: enumerate these when we add type hints for numpy scalars
69114
# anything with a dtype attribute
70-
_SupportsDType,
115+
"_SupportsDType[np.dtype[Any]]",
71116
# character codes, type strings or comma-separated fields, e.g., 'float64'
72117
str,
73118
_VoidDTypeLike,
@@ -79,3 +124,107 @@ class _SupportsDType(Protocol):
79124
# therefore not included in the Union defining `DTypeLike`.
80125
#
81126
# See https://github.com/numpy/numpy/issues/16891 for more details.
127+
128+
# Aliases for commonly used dtype-like objects.
129+
# Note that the precision of `np.number` subclasses is ignored herein.
130+
_DTypeLikeBool = Union[
131+
Type[bool],
132+
Type[np.bool_],
133+
"np.dtype[np.bool_]",
134+
"_SupportsDType[np.dtype[np.bool_]]",
135+
_BoolCodes,
136+
]
137+
_DTypeLikeUInt = Union[
138+
Type[np.unsignedinteger],
139+
"np.dtype[np.unsignedinteger]",
140+
"_SupportsDType[np.dtype[np.unsignedinteger]]",
141+
_UInt8Codes,
142+
_UInt16Codes,
143+
_UInt32Codes,
144+
_UInt64Codes,
145+
_UByteCodes,
146+
_UShortCodes,
147+
_UIntCCodes,
148+
_UIntPCodes,
149+
_UIntCodes,
150+
_ULongLongCodes,
151+
]
152+
_DTypeLikeInt = Union[
153+
Type[int],
154+
Type[np.signedinteger],
155+
"np.dtype[np.signedinteger]",
156+
"_SupportsDType[np.dtype[np.signedinteger]]",
157+
_Int8Codes,
158+
_Int16Codes,
159+
_Int32Codes,
160+
_Int64Codes,
161+
_ByteCodes,
162+
_ShortCodes,
163+
_IntCCodes,
164+
_IntPCodes,
165+
_IntCodes,
166+
_LongLongCodes,
167+
]
168+
_DTypeLikeFloat = Union[
169+
Type[float],
170+
Type[np.floating],
171+
"np.dtype[np.floating]",
172+
"_SupportsDType[np.dtype[np.floating]]",
173+
_Float16Codes,
174+
_Float32Codes,
175+
_Float64Codes,
176+
_HalfCodes,
177+
_SingleCodes,
178+
_DoubleCodes,
179+
_LongDoubleCodes,
180+
]
181+
_DTypeLikeComplex = Union[
182+
Type[complex],
183+
Type[np.complexfloating],
184+
"np.dtype[np.complexfloating]",
185+
"_SupportsDType[np.dtype[np.complexfloating]]",
186+
_Complex64Codes,
187+
_Complex128Codes,
188+
_CSingleCodes,
189+
_CDoubleCodes,
190+
_CLongDoubleCodes,
191+
]
192+
_DTypeLikeDT64 = Union[
193+
Type[np.timedelta64],
194+
"np.dtype[np.timedelta64]",
195+
"_SupportsDType[np.dtype[np.timedelta64]]",
196+
_TD64Codes,
197+
]
198+
_DTypeLikeTD64 = Union[
199+
Type[np.datetime64],
200+
"np.dtype[np.datetime64]",
201+
"_SupportsDType[np.dtype[np.datetime64]]",
202+
_DT64Codes,
203+
]
204+
_DTypeLikeStr = Union[
205+
Type[str],
206+
Type[np.str_],
207+
"np.dtype[np.str_]",
208+
"_SupportsDType[np.dtype[np.str_]]",
209+
_StrCodes,
210+
]
211+
_DTypeLikeBytes = Union[
212+
Type[bytes],
213+
Type[np.bytes_],
214+
"np.dtype[np.bytes_]",
215+
"_SupportsDType[np.dtype[np.bytes_]]",
216+
_BytesCodes,
217+
]
218+
_DTypeLikeVoid = Union[
219+
Type[np.void],
220+
"np.dtype[np.void]",
221+
"_SupportsDType[np.dtype[np.void]]",
222+
_VoidCodes,
223+
_VoidDTypeLike,
224+
]
225+
_DTypeLikeObject = Union[
226+
type,
227+
"np.dtype[np.object_]",
228+
"_SupportsDType[np.dtype[np.object_]]",
229+
_ObjectCodes,
230+
]

‎numpy/typing/tests/data/fail/dtype.py

Copy file name to clipboardExpand all lines: numpy/typing/tests/data/fail/dtype.py
+9-3Lines changed: 9 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -1,10 +1,16 @@
11
import numpy as np
22

3-
class Test:
4-
not_dtype = float
53

4+
class Test1:
5+
not_dtype = np.dtype(float)
66

7-
np.dtype(Test()) # E: No overload variant of "dtype" matches
7+
8+
class Test2:
9+
dtype = float
10+
11+
12+
np.dtype(Test1()) # E: No overload variant of "dtype" matches
13+
np.dtype(Test2()) # E: incompatible type
814

915
np.dtype( # E: No overload variant of "dtype" matches
1016
{

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