refactor: truediv

Author: cmp0xff

pandas-stubs/_libs/tslibs/timedeltas.pyi

@@ -255,22 +255,24 @@ class Timedelta(timedelta):
     ) -> np_ndarray[ShapeT, np.int_]: ...
     # Override due to more types supported than timedelta
     @overload  # type: ignore[override]
-    def __truediv__(self, other: timedelta | Timedelta | NaTType) -> float: ...
+    # pyrefly: ignore[bad-override]
+    def __truediv__(self, other: Just[int] | Just[float]) -> Self: ...
     @overload
-    def __truediv__(self, other: float) -> Self: ...
+    def __truediv__(self, other: Self | NaTType) -> float: ...
     @overload
     def __truediv__(
         self, other: np_ndarray[ShapeT, np.integer | np.floating]
     ) -> np_ndarray[ShapeT, np.timedelta64]: ...
     @overload
-    def __truediv__(self, other: Series[Timedelta]) -> Series[float]: ...
-    @overload
-    def __truediv__(self, other: Series[int]) -> Series[Timedelta]: ...
+    def __truediv__(
+        self, other: np_ndarray[ShapeT, np.timedelta64]
+    ) -> np_ndarray[ShapeT, np.floating]: ...
     @overload
-    def __truediv__(self, other: Series[float]) -> Series[Timedelta]: ...
+    def __rtruediv__(self, other: Self | NaTType) -> float: ...
     @overload
-    def __truediv__(self, other: Index[int] | Index[float]) -> TimedeltaIndex: ...
-    def __rtruediv__(self, other: timedelta | Timedelta | NaTType) -> float: ...
+    def __rtruediv__(
+        self, other: np_ndarray[ShapeT, np.timedelta64]
+    ) -> np_ndarray[ShapeT, np.floating]: ...
     # Override due to more types supported than timedelta
     @overload
     def __eq__(self, other: timedelta | Timedelta | np.timedelta64) -> bool: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]

pandas-stubs/_typing.pyi

@@ -25,6 +25,7 @@ from typing import (
     overload,
 )
 
+from _typeshed import _T_contra
 import numpy as np
 from numpy import typing as npt
 import pandas as pd
@@ -860,6 +861,9 @@ np_ndarray_td: TypeAlias = npt.NDArray[np.timedelta64]
 # Define shape and generic type variables with defaults similar to numpy
 GenericT = TypeVar("GenericT", bound=np.generic, default=Any)
 GenericT_co = TypeVar("GenericT_co", bound=np.generic, default=Any, covariant=True)
+GenericT_contra = TypeVar(
+    "GenericT_contra", bound=np.generic, default=Any, contravariant=True
+)
 ShapeT = TypeVar("ShapeT", bound=tuple[int, ...], default=tuple[Any, ...])
 # Numpy ndarray with more ergonomic typevar
 np_ndarray: TypeAlias = np.ndarray[ShapeT, np.dtype[GenericT]]
@@ -1114,4 +1118,10 @@ class Just(Protocol, Generic[T]):
     @override
     def __class__(self, t: type[T], /) -> None: ...
 
+class SupportsTrueDiv(Protocol[_T_contra, _T_co]):
+    def __truediv__(self, x: _T_contra, /) -> _T_co: ...
+
+class SupportsRTrueDiv(Protocol[_T_contra, _T_co]):
+    def __rtruediv__(self, x: _T_contra, /) -> _T_co: ...
+
 __all__ = ["npt", "type_t"]

pandas-stubs/core/base.pyi

@@ -3,6 +3,7 @@ from collections.abc import (
     Iterator,
     Sequence,
 )
+from datetime import timedelta
 from typing import (
     Any,
     Generic,
@@ -269,6 +270,38 @@ class ElementOpsMixin(Generic[S2]):
     def _proto_rmul(
         self: ElementOpsMixin[str], other: Just[int] | np.integer
     ) -> ElementOpsMixin[str]: ...
+    @overload
+    def _proto_truediv(
+        self: ElementOpsMixin[int], other: int | np.integer
+    ) -> ElementOpsMixin[float]: ...
+    @overload
+    def _proto_truediv(
+        self: ElementOpsMixin[float], other: float | np.floating
+    ) -> ElementOpsMixin[float]: ...
+    @overload
+    def _proto_truediv(
+        self: ElementOpsMixin[complex], other: complex | np.complexfloating
+    ) -> ElementOpsMixin[complex]: ...
+    @overload
+    def _proto_truediv(
+        self: ElementOpsMixin[Timedelta], other: timedelta | Timedelta | np.timedelta64
+    ) -> ElementOpsMixin[float]: ...
+    @overload
+    def _proto_rtruediv(
+        self: ElementOpsMixin[int], other: int | np.integer
+    ) -> ElementOpsMixin[float]: ...
+    @overload
+    def _proto_rtruediv(
+        self: ElementOpsMixin[float], other: float | np.floating
+    ) -> ElementOpsMixin[float]: ...
+    @overload
+    def _proto_rtruediv(
+        self: ElementOpsMixin[complex], other: complex | np.complexfloating
+    ) -> ElementOpsMixin[complex]: ...
+    @overload
+    def _proto_rtruediv(
+        self: ElementOpsMixin[Timedelta], other: timedelta | Timedelta | np.timedelta64
+    ) -> ElementOpsMixin[float]: ...
 
 @type_check_only
 class Supports_ProtoAdd(Protocol[_T_contra, S2]):
@@ -285,3 +318,11 @@ class Supports_ProtoMul(Protocol[_T_contra, S2]):
 @type_check_only
 class Supports_ProtoRMul(Protocol[_T_contra, S2]):
     def _proto_rmul(self, other: _T_contra, /) -> ElementOpsMixin[S2]: ...
+
+@type_check_only
+class Supports_ProtoTrueDiv(Protocol[_T_contra, S2]):
+    def _proto_truediv(self, other: _T_contra, /) -> ElementOpsMixin[S2]: ...
+
+@type_check_only
+class Supports_ProtoRTrueDiv(Protocol[_T_contra, S2]):
+    def _proto_rtruediv(self, other: _T_contra, /) -> ElementOpsMixin[S2]: ...