Use np array aliases in tests

pandas-stubs/_typing.pyi

@@ -827,7 +827,7 @@ TimeNonexistent: TypeAlias = (
 DropKeep: TypeAlias = Literal["first", "last", False]
 CorrelationMethod: TypeAlias = (
     Literal["pearson", "kendall", "spearman"]
-    | Callable[[np.typing.NDArray[Any], np.typing.NDArray[Any]], float]
+    | Callable[[npt.NDArray[Any], npt.NDArray[Any]], float]
 )
 AlignJoin: TypeAlias = Literal["outer", "inner", "left", "right"]
 DtypeBackend: TypeAlias = Literal["pyarrow", "numpy_nullable"]

pandas-stubs/core/base.pyi

@@ -18,6 +18,7 @@ from typing import (
 
 from _typeshed import _T_contra
 import numpy as np
+import numpy.typing as npt
 from pandas.core.arraylike import OpsMixin
 from pandas.core.arrays import ExtensionArray
 from pandas.core.arrays.categorical import Categorical
@@ -222,7 +223,7 @@ ScalarArrayIndexReal: TypeAlias = (
     float
     | Sequence[float | NumpyRealScalar]
     | NumpyRealScalar
-    | np.typing.NDArray[NumpyRealScalar]
+    | npt.NDArray[NumpyRealScalar]
     | ExtensionArray
     | IndexReal
 )
@@ -235,7 +236,7 @@ ScalarArrayIndexComplex: TypeAlias = (
     complex
     | Sequence[complex | NumpyComplexScalar]
     | NumpyComplexScalar
-    | np.typing.NDArray[NumpyComplexScalar]
+    | npt.NDArray[NumpyComplexScalar]
     | ExtensionArray
     | IndexComplex
 )

pandas-stubs/core/indexes/accessors.pyi

@@ -12,7 +12,6 @@ from typing import (
     type_check_only,
 )
 
-import numpy as np
 from pandas.core.accessor import PandasDelegate
 from pandas.core.arrays.base import ExtensionArray
 from pandas.core.arrays.categorical import Categorical
@@ -45,8 +44,8 @@ from pandas._typing import (
     TimestampConvention,
     TimeUnit,
     TimeZones,
-    np_1darray,
     np_1darray_bool,
+    np_1darray_object,
     np_ndarray_bool,
 )
 
@@ -135,10 +134,10 @@ class _DatetimeObjectOps(
 ): ...
 
 _DTOtherOpsDateReturnType = TypeVar(
-    "_DTOtherOpsDateReturnType", bound=Series[date] | np_1darray[np.object_]
+    "_DTOtherOpsDateReturnType", bound=Series[date] | np_1darray_object
 )
 _DTOtherOpsTimeReturnType = TypeVar(
-    "_DTOtherOpsTimeReturnType", bound=Series[time] | np_1darray[np.object_]
+    "_DTOtherOpsTimeReturnType", bound=Series[time] | np_1darray_object
 )
 
 class _DatetimeOtherOps(Generic[_DTOtherOpsDateReturnType, _DTOtherOpsTimeReturnType]):
@@ -293,7 +292,7 @@ class DatetimeProperties(
         _DTToPeriodReturnType,
     ],
 ):
-    def to_pydatetime(self) -> np_1darray[np.object_]: ...
+    def to_pydatetime(self) -> np_1darray_object: ...
     def isocalendar(self) -> DataFrame: ...
     @property
     def unit(self) -> TimeUnit: ...
@@ -309,7 +308,7 @@ _TDTotalSecondsReturnType = TypeVar(
 class _TimedeltaPropertiesNoRounding(
     Generic[_TDNoRoundingMethodReturnType, _TDTotalSecondsReturnType]
 ):
-    def to_pytimedelta(self) -> np_1darray[np.object_]: ...
+    def to_pytimedelta(self) -> np_1darray_object: ...
     @property
     def components(self) -> DataFrame: ...
     @property
@@ -418,8 +417,8 @@ class DatetimeIndexProperties(
         Index[int],
         np_1darray_bool,
         DatetimeIndex,
-        np_1darray[np.object_],
-        np_1darray[np.object_],
+        np_1darray_object,
+        np_1darray_object,
         BaseOffset,
         DatetimeIndex,
         Index,
@@ -431,7 +430,7 @@ class DatetimeIndexProperties(
     def is_normalized(self) -> bool: ...
     @property
     def tzinfo(self) -> _tzinfo | None: ...
-    def to_pydatetime(self) -> np_1darray[np.object_]: ...
+    def to_pydatetime(self) -> np_1darray_object: ...
     def std(
         self, axis: int | None = ..., ddof: int = ..., skipna: bool = ...
     ) -> Timedelta: ...

pandas-stubs/core/indexes/period.pyi

@@ -22,8 +22,8 @@ from pandas._typing import (
     AxesData,
     Dtype,
     Frequency,
-    np_1darray,
     np_1darray_intp,
+    np_1darray_object,
     np_ndarray_bool,
 )
 
@@ -37,7 +37,7 @@ class PeriodIndex(DatetimeIndexOpsMixin[pd.Period, np.object_], PeriodIndexField
         name: Hashable | None = None,
     ) -> Self: ...
     @property
-    def values(self) -> np_1darray[np.object_]: ...
+    def values(self) -> np_1darray_object: ...
     def __add__(  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
         self, other: datetime.timedelta
     ) -> Self: ...

tests/indexes/arithmetic/bool/test_add.py

@@ -3,8 +3,13 @@
 import pandas as pd
 from typing_extensions import assert_type
 
-from tests import check
-from tests._typing import np_ndarray_int64
+from tests import (
+    check,
+)
+from tests._typing import (
+    np_ndarray_bool,
+    np_ndarray_int64,
+)
 
 # left operand
 left = pd.Index([True, True, False])
@@ -55,7 +60,7 @@ def test_add_numpy_array() -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__radd__` cannot override. At runtime, they return
     # `Index`es with the correct element type.
-    check(assert_type(b + left, "npt.NDArray[np.bool_]"), pd.Index, np.bool_)
+    check(assert_type(b + left, np_ndarray_bool), pd.Index, np.bool_)
     check(assert_type(i + left, np_ndarray_int64), pd.Index, np.integer)
     check(assert_type(f + left, "npt.NDArray[np.float64]"), pd.Index, np.floating)
     check(

tests/indexes/arithmetic/bool/test_mul.py

@@ -17,7 +17,11 @@
     TYPE_CHECKING_INVALID_USAGE,
     check,
 )
-from tests._typing import np_ndarray_int64
+from tests._typing import (
+    np_ndarray_bool,
+    np_ndarray_int64,
+    np_ndarray_td,
+)
 
 
 @pytest.fixture
@@ -92,7 +96,7 @@ def test_mul_numpy_array(left: "pd.Index[bool]") -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__rmul__` cannot override. At runtime, they return
     # `Index` with the correct element type.
-    check(assert_type(b * left, "npt.NDArray[np.bool_]"), pd.Index, np.bool_)
+    check(assert_type(b * left, np_ndarray_bool), pd.Index, np.bool_)
     check(assert_type(i * left, np_ndarray_int64), pd.Index, np.integer)
     check(assert_type(f * left, "npt.NDArray[np.float64]"), pd.Index, np.floating)
     check(
@@ -102,7 +106,7 @@ def test_mul_numpy_array(left: "pd.Index[bool]") -> None:
     )
     if TYPE_CHECKING_INVALID_USAGE:
         assert_type(s * left, Any)
-        assert_type(d * left, "npt.NDArray[np.timedelta64]")
+        assert_type(d * left, np_ndarray_td)
 
 
 def test_mul_pd_index(left: "pd.Index[bool]") -> None:

tests/indexes/arithmetic/complex/test_add.py

@@ -4,7 +4,10 @@
 from typing_extensions import assert_type
 
 from tests import check
-from tests._typing import np_ndarray_int64
+from tests._typing import (
+    np_ndarray_bool,
+    np_ndarray_int64,
+)
 
 # left operand
 left = pd.Index([1j, 2j, 3j])
@@ -55,7 +58,7 @@ def test_add_numpy_array() -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__radd__` cannot override. At runtime, they return
     # `Index`es with the correct element type.
-    check(assert_type(b + left, "npt.NDArray[np.bool_]"), pd.Index, np.complexfloating)
+    check(assert_type(b + left, np_ndarray_bool), pd.Index, np.complexfloating)
     check(assert_type(i + left, np_ndarray_int64), pd.Index, np.complexfloating)
     check(
         assert_type(f + left, "npt.NDArray[np.float64]"), pd.Index, np.complexfloating

tests/indexes/arithmetic/complex/test_mul.py

@@ -17,7 +17,11 @@
     TYPE_CHECKING_INVALID_USAGE,
     check,
 )
-from tests._typing import np_ndarray_int64
+from tests._typing import (
+    np_ndarray_bool,
+    np_ndarray_int64,
+    np_ndarray_td,
+)
 
 
 @pytest.fixture
@@ -92,7 +96,7 @@ def test_mul_numpy_array(left: "pd.Index[complex]") -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__rmul__` cannot override. At runtime, they return
     # `Index` with the correct element type.
-    check(assert_type(b * left, "npt.NDArray[np.bool_]"), pd.Index, np.complexfloating)
+    check(assert_type(b * left, np_ndarray_bool), pd.Index, np.complexfloating)
     check(assert_type(i * left, np_ndarray_int64), pd.Index, np.complexfloating)
     check(
         assert_type(f * left, "npt.NDArray[np.float64]"), pd.Index, np.complexfloating
@@ -104,7 +108,7 @@ def test_mul_numpy_array(left: "pd.Index[complex]") -> None:
     )
     if TYPE_CHECKING_INVALID_USAGE:
         assert_type(s * left, Any)
-        assert_type(d * left, "npt.NDArray[np.timedelta64]")
+        assert_type(d * left, np_ndarray_td)
 
 
 def test_mul_pd_index(left: "pd.Index[complex]") -> None:

tests/indexes/arithmetic/float/test_add.py

@@ -3,8 +3,13 @@
 import pandas as pd
 from typing_extensions import assert_type
 
-from tests import check
-from tests._typing import np_ndarray_int64
+from tests import (
+    check,
+)
+from tests._typing import (
+    np_ndarray_bool,
+    np_ndarray_int64,
+)
 
 # left operand
 left = pd.Index([1.0, 2.0, 3.0])
@@ -55,7 +60,7 @@ def test_add_numpy_array() -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__radd__` cannot override. At runtime, they return
     # `Index`es with the correct element type.
-    check(assert_type(b + left, "npt.NDArray[np.bool_]"), pd.Index, np.floating)
+    check(assert_type(b + left, np_ndarray_bool), pd.Index, np.floating)
     check(assert_type(i + left, np_ndarray_int64), pd.Index, np.floating)
     check(assert_type(f + left, "npt.NDArray[np.float64]"), pd.Index, np.floating)
     check(

tests/indexes/arithmetic/float/test_floordiv.py

@@ -5,6 +5,7 @@
 from typing import Any
 
 import numpy as np
+import numpy.typing as npt  # noqa: F401
 import pandas as pd
 import pytest
 from typing_extensions import (
@@ -16,6 +17,9 @@
     TYPE_CHECKING_INVALID_USAGE,
     check,
 )
+from tests._typing import (
+    np_ndarray_int64,
+)
 
 
 @pytest.fixture
@@ -92,16 +96,14 @@ def test_floordiv_numpy_array(left: "pd.Index[float]") -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__rfloordiv__` cannot override. At runtime, they lead to
     # errors or pd.Index.
-    check(assert_type(b // left, "np.typing.NDArray[np.int8]"), pd.Index, np.floating)
-    check(assert_type(i // left, "np.typing.NDArray[np.int64]"), pd.Index, np.floating)
-    check(
-        assert_type(f // left, "np.typing.NDArray[np.float64]"), pd.Index, np.floating
-    )
+    check(assert_type(b // left, "npt.NDArray[np.int8]"), pd.Index, np.floating)
+    check(assert_type(i // left, np_ndarray_int64), pd.Index, np.floating)
+    check(assert_type(f // left, "npt.NDArray[np.float64]"), pd.Index, np.floating)
     if TYPE_CHECKING_INVALID_USAGE:
         assert_type(c // left, Any)
         assert_type(s // left, Any)
     check(
-        assert_type(d // left, "np.typing.NDArray[np.int64]"),
+        assert_type(d // left, np_ndarray_int64),
         pd.TimedeltaIndex,
         pd.Timedelta,
     )

tests/indexes/arithmetic/float/test_mul.py

@@ -17,7 +17,11 @@
     TYPE_CHECKING_INVALID_USAGE,
     check,
 )
-from tests._typing import np_ndarray_int64
+from tests._typing import (
+    np_ndarray_bool,
+    np_ndarray_int64,
+    np_ndarray_td,
+)
 
 
 @pytest.fixture
@@ -92,7 +96,7 @@ def test_mul_numpy_array(left: "pd.Index[float]") -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__rmul__` cannot override. At runtime, they return
     # `Index` with the correct element type.
-    check(assert_type(b * left, "npt.NDArray[np.bool_]"), pd.Index, np.floating)
+    check(assert_type(b * left, np_ndarray_bool), pd.Index, np.floating)
     check(assert_type(i * left, np_ndarray_int64), pd.Index, np.floating)
     check(assert_type(f * left, "npt.NDArray[np.float64]"), pd.Index, np.floating)
     check(
@@ -103,7 +107,7 @@ def test_mul_numpy_array(left: "pd.Index[float]") -> None:
     if TYPE_CHECKING_INVALID_USAGE:
         assert_type(s * left, Any)
     check(
-        assert_type(d * left, "npt.NDArray[np.timedelta64]"),
+        assert_type(d * left, np_ndarray_td),
         pd.TimedeltaIndex,
         pd.Timedelta,
     )

tests/indexes/arithmetic/int/test_add.py

@@ -3,8 +3,13 @@
 import pandas as pd
 from typing_extensions import assert_type
 
-from tests import check
-from tests._typing import np_ndarray_int64
+from tests import (
+    check,
+)
+from tests._typing import (
+    np_ndarray_bool,
+    np_ndarray_int64,
+)
 
 # left operand
 left = pd.Index([1, 2, 3])
@@ -55,7 +60,7 @@ def test_add_numpy_array() -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__radd__` cannot override. At runtime, they return
     # `Index`es with the correct element type.
-    check(assert_type(b + left, "npt.NDArray[np.bool_]"), pd.Index, np.integer)
+    check(assert_type(b + left, np_ndarray_bool), pd.Index, np.integer)
     check(assert_type(i + left, np_ndarray_int64), pd.Index, np.integer)
     check(assert_type(f + left, "npt.NDArray[np.float64]"), pd.Index, np.floating)
     check(

tests/indexes/arithmetic/int/test_floordiv.py

@@ -5,6 +5,7 @@
 from typing import Any
 
 import numpy as np
+import numpy.typing as npt  # noqa:F401
 import pandas as pd
 import pytest
 from typing_extensions import (
@@ -16,6 +17,9 @@
     TYPE_CHECKING_INVALID_USAGE,
     check,
 )
+from tests._typing import (
+    np_ndarray_int64,
+)
 
 
 @pytest.fixture
@@ -92,16 +96,14 @@ def test_floordiv_numpy_array(left: "pd.Index[int]") -> None:
     # `numpy` typing gives the corresponding `ndarray`s in the static type
     # checking, where our `__rfloordiv__` cannot override. At runtime, they lead to
     # errors or pd.Index.
-    check(assert_type(b // left, "np.typing.NDArray[np.int8]"), pd.Index, np.integer)
-    check(assert_type(i // left, "np.typing.NDArray[np.int64]"), pd.Index, np.integer)
-    check(
-        assert_type(f // left, "np.typing.NDArray[np.float64]"), pd.Index, np.floating
-    )
+    check(assert_type(b // left, "npt.NDArray[np.int8]"), pd.Index, np.integer)
+    check(assert_type(i // left, np_ndarray_int64), pd.Index, np.integer)
+    check(assert_type(f // left, "npt.NDArray[np.float64]"), pd.Index, np.floating)
     if TYPE_CHECKING_INVALID_USAGE:
         assert_type(c // left, Any)
         assert_type(s // left, Any)
     check(
-        assert_type(d // left, "np.typing.NDArray[np.int64]"),
+        assert_type(d // left, np_ndarray_int64),
         pd.TimedeltaIndex,
         pd.Timedelta,
     )