enable reportMissingTypeArgument

Author: cmp0xff

pandas-stubs/_libs/interval.pyi

@@ -26,7 +26,9 @@ VALID_CLOSED: frozenset[str]
 
 _OrderableScalarT = TypeVar("_OrderableScalarT", bound=int | float)
 _OrderableTimesT = TypeVar("_OrderableTimesT", bound=Timestamp | Timedelta)
-_OrderableT = TypeVar("_OrderableT", bound=int | float | Timestamp | Timedelta)
+_OrderableT = TypeVar(
+    "_OrderableT", bound=int | float | Timestamp | Timedelta, default=Any
+)
 
 @type_check_only
 class _LengthDescriptor:

pandas-stubs/_typing.pyi

@@ -76,6 +76,7 @@ from pandas.tseries.offsets import (
 P = ParamSpec("P")
 
 HashableT = TypeVar("HashableT", bound=Hashable)
+HashableT0 = TypeVar("HashableT0", bound=Hashable, default=Any)
 HashableT1 = TypeVar("HashableT1", bound=Hashable)
 HashableT2 = TypeVar("HashableT2", bound=Hashable)
 HashableT3 = TypeVar("HashableT3", bound=Hashable)
@@ -774,7 +775,7 @@ XMLParsers: TypeAlias = Literal["lxml", "etree"]
 HTMLFlavors: TypeAlias = Literal["lxml", "html5lib", "bs4"]
 
 # Interval closed type
-IntervalT = TypeVar("IntervalT", bound=Interval)
+IntervalT = TypeVar("IntervalT", bound=Interval, default=Interval)
 IntervalLeftRight: TypeAlias = Literal["left", "right"]
 IntervalClosedType: TypeAlias = IntervalLeftRight | Literal["both", "neither"]
 
@@ -872,7 +873,11 @@ ExcelWriterMergeCells: TypeAlias = bool | Literal["columns"]
 
 # read_csv: usecols
 UsecolsArgType: TypeAlias = (
-    SequenceNotStr[Hashable] | range | AnyArrayLike | Callable[[HashableT], bool] | None
+    SequenceNotStr[Hashable]
+    | range
+    | AnyArrayLike
+    | Callable[[HashableT0], bool]
+    | None
 )
 
 # maintain the sub-type of any hashable sequence
@@ -918,6 +923,7 @@ PyArrowNotStrDtypeArg: TypeAlias = (
 StrLike: TypeAlias = str | np.str_
 
 ScalarT = TypeVar("ScalarT", bound=Scalar)
+ScalarT0 = TypeVar("ScalarT0", bound=Scalar, default=Scalar)
 # Refine the definitions below in 3.9 to use the specialized type.
 np_num: TypeAlias = np.bool | np.integer | np.floating | np.complexfloating
 np_ndarray_intp: TypeAlias = npt.NDArray[np.intp]
@@ -959,7 +965,10 @@ np_1darray_dt: TypeAlias = np_1darray[np.datetime64]
 np_1darray_td: TypeAlias = np_1darray[np.timedelta64]
 np_2darray: TypeAlias = np.ndarray[tuple[int, int], np.dtype[GenericT]]
 
-NDArrayT = TypeVar("NDArrayT", bound=np.ndarray)
+if sys.version_info >= (3, 11):
+    NDArrayT = TypeVar("NDArrayT", bound=np.ndarray)
+else:
+    NDArrayT = TypeVar("NDArrayT", bound=np.ndarray[Any, Any])
 
 DtypeNp = TypeVar("DtypeNp", bound=np.dtype[np.generic])
 KeysArgType: TypeAlias = Any
@@ -969,7 +978,7 @@ ListLikeExceptSeriesAndStr: TypeAlias = (
 )
 ListLikeU: TypeAlias = Sequence[Any] | np_1darray | Series | Index
 ListLikeHashable: TypeAlias = (
-    MutableSequence[HashableT] | np_1darray | tuple[HashableT, ...] | range
+    MutableSequence[HashableT0] | np_1darray | tuple[HashableT0, ...] | range
 )
 
 class SupportsDType(Protocol[GenericT_co]):
@@ -1010,8 +1019,9 @@ SeriesDType: TypeAlias = (
     | datetime.datetime  # includes pd.Timestamp
     | datetime.timedelta  # includes pd.Timedelta
 )
+S0 = TypeVar("S0", bound=SeriesDType, default=Any)
 S1 = TypeVar("S1", bound=SeriesDType, default=Any)
-# Like S1, but without `default=Any`.
+# Like S0 and S1, but without `default=Any`.
 S2 = TypeVar("S2", bound=SeriesDType)
 S2_contra = TypeVar("S2_contra", bound=SeriesDType, contravariant=True)
 S2_NDT_contra = TypeVar(
@@ -1045,14 +1055,14 @@ IndexingInt: TypeAlias = (
 )
 
 # AxesData is used for data for Index
-AxesData: TypeAlias = Mapping[S3, Any] | Axes | KeysView[S3]
+AxesData: TypeAlias = Mapping[S0, Any] | Axes | KeysView[S0]
 
 # Any plain Python or numpy function
 Function: TypeAlias = np.ufunc | Callable[..., Any]
 # Use a distinct HashableT in shared types to avoid conflicts with
 # shared HashableT and HashableT#. This one can be used if the identical
 # type is need in a function that uses GroupByObjectNonScalar
-_HashableTa = TypeVar("_HashableTa", bound=Hashable)
+_HashableTa = TypeVar("_HashableTa", bound=Hashable, default=Any)
 if TYPE_CHECKING:  # noqa: PYI002
     ByT = TypeVar(
         "ByT",
@@ -1070,7 +1080,7 @@ if TYPE_CHECKING:  # noqa: PYI002
         | Scalar
         | Period
         | Interval[int | float | Timestamp | Timedelta]
-        | tuple,
+        | tuple[Any, ...],
     )
     # Use a distinct SeriesByT when using groupby with Series of known dtype.
     # Essentially, an intersection between Series S1 TypeVar, and ByT TypeVar
@@ -1088,21 +1098,23 @@ if TYPE_CHECKING:  # noqa: PYI002
         | Period
         | Interval[int | float | Timestamp | Timedelta],
     )
-GroupByObjectNonScalar: TypeAlias = (
-    tuple[_HashableTa, ...]
-    | list[_HashableTa]
-    | Function
-    | list[Function]
-    | list[Series]
-    | np_ndarray
-    | list[np_ndarray]
-    | Mapping[Label, Any]
-    | list[Mapping[Label, Any]]
-    | list[Index]
-    | Grouper
-    | list[Grouper]
-)
-GroupByObject: TypeAlias = Scalar | Index | GroupByObjectNonScalar | Series
+    GroupByObjectNonScalar: TypeAlias = (
+        tuple[_HashableTa, ...]
+        | list[_HashableTa]
+        | Function
+        | list[Function]
+        | list[Series]
+        | np_ndarray
+        | list[np_ndarray]
+        | Mapping[Label, Any]
+        | list[Mapping[Label, Any]]
+        | list[Index]
+        | Grouper
+        | list[Grouper]
+    )
+    GroupByObject: TypeAlias = (
+        Scalar | Index | GroupByObjectNonScalar[_HashableTa] | Series
+    )
 
 StataDateFormat: TypeAlias = Literal[
     "tc",
@@ -1125,10 +1137,10 @@ StataDateFormat: TypeAlias = Literal[
 # `DataFrame.replace` also accepts mappings of these.
 ReplaceValue: TypeAlias = (
     Scalar
-    | Pattern
+    | Pattern[Any]
     | NAType
-    | Sequence[Scalar | Pattern]
-    | Mapping[HashableT, ScalarT]
+    | Sequence[Scalar | Pattern[Any]]
+    | Mapping[HashableT0, ScalarT0]
     | Series
     | None
 )

pandas-stubs/core/frame.pyi

@@ -58,7 +58,7 @@ from pandas.core.indexing import (
     _LocIndexer,
 )
 from pandas.core.reshape.pivot import (
-    _PivotAggFunc,
+    _PivotAggFuncTypes,
     _PivotTableColumnsTypes,
     _PivotTableIndexTypes,
     _PivotTableValuesTypes,
@@ -178,7 +178,7 @@ from pandas.plotting import PlotAccessor
 from pandas.plotting._core import _BoxPlotT
 
 _T_MUTABLE_MAPPING_co = TypeVar(
-    "_T_MUTABLE_MAPPING_co", bound=MutableMapping, covariant=True
+    "_T_MUTABLE_MAPPING_co", bound=MutableMapping[Any, Any], covariant=True
 )
 
 class _iLocIndexerFrame(_iLocIndexer, Generic[_T]):
@@ -361,28 +361,23 @@ class _AtIndexerFrame(_AtIndexer):
         ),
     ) -> None: ...
 
-# With mypy 1.14.1 and python 3.12, the second overload needs a type-ignore statement
-if sys.version_info >= (3, 12):
-    class _GetItemHack:
-        @overload
-        def __getitem__(self, key: Scalar | tuple[Hashable, ...]) -> Series: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
+class _GetItemHack:
+    @overload
+    def __getitem__(self, key: Scalar | tuple[Hashable, ...]) -> Series: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
+    # With mypy 1.14.1 and python 3.12, the second overload needs a type-ignore statement
+    if sys.version_info >= (3, 12):
         @overload
         def __getitem__(  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
             self, key: Iterable[Hashable] | slice
         ) -> Self: ...
-        @overload
-        def __getitem__(self, key: Hashable) -> Series: ...
-
-else:
-    class _GetItemHack:
-        @overload
-        def __getitem__(self, key: Scalar | tuple[Hashable, ...]) -> Series: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
+    else:
         @overload
         def __getitem__(  # pyright: ignore[reportOverlappingOverload]
             self, key: Iterable[Hashable] | slice
         ) -> Self: ...
-        @overload
-        def __getitem__(self, key: Hashable) -> Series: ...
+
+    @overload
+    def __getitem__(self, key: Hashable) -> Series: ...
 
 _AstypeArgExt: TypeAlias = (
     AstypeArg
@@ -484,7 +479,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         self,
         orient: str = ...,
         *,
-        into: type[defaultdict],
+        into: type[defaultdict[Any, Any]],
         index: Literal[True] = True,
     ) -> Never: ...
     @overload
@@ -500,7 +495,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         self,
         orient: Literal["records"],
         *,
-        into: type[dict] = ...,
+        into: type[dict[Any, Any]] = ...,
         index: Literal[True] = True,
     ) -> list[dict[Hashable, Any]]: ...
     @overload
@@ -516,23 +511,23 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         self,
         orient: Literal["index"],
         *,
-        into: OrderedDict | type[OrderedDict],
+        into: OrderedDict[Any, Any] | type[OrderedDict[Any, Any]],
         index: Literal[True] = True,
     ) -> OrderedDict[Hashable, dict[Hashable, Any]]: ...
     @overload
     def to_dict(
         self,
         orient: Literal["index"],
         *,
-        into: type[MutableMapping],
+        into: type[MutableMapping[Any, Any]],
         index: Literal[True] = True,
     ) -> MutableMapping[Hashable, dict[Hashable, Any]]: ...
     @overload
     def to_dict(
         self,
         orient: Literal["index"],
         *,
-        into: type[dict] = ...,
+        into: type[dict[Any, Any]] = ...,
         index: Literal[True] = True,
     ) -> dict[Hashable, dict[Hashable, Any]]: ...
     @overload
@@ -548,23 +543,23 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         self,
         orient: Literal["dict", "list", "series"] = ...,
         *,
-        into: type[dict] = ...,
+        into: type[dict[Any, Any]] = ...,
         index: Literal[True] = True,
     ) -> dict[Hashable, Any]: ...
     @overload
     def to_dict(
         self,
         orient: Literal["split", "tight"],
         *,
-        into: MutableMapping[Any, Any] | type[MutableMapping],
+        into: MutableMapping[Any, Any] | type[MutableMapping[Any, Any]],
         index: bool = ...,
     ) -> MutableMapping[str, list[Any]]: ...
     @overload
     def to_dict(
         self,
         orient: Literal["split", "tight"],
         *,
-        into: type[dict] = ...,
+        into: type[dict[Any, Any]] = ...,
         index: bool = ...,
     ) -> dict[str, list[Any]]: ...
     @classmethod
@@ -583,16 +578,29 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         coerce_float: bool = False,
         nrows: int | None = None,
     ) -> Self: ...
-    def to_records(
-        self,
-        index: _bool = True,
-        column_dtypes: (
-            _str | npt.DTypeLike | Mapping[HashableT1, npt.DTypeLike] | None
-        ) = None,
-        index_dtypes: (
-            _str | npt.DTypeLike | Mapping[HashableT2, npt.DTypeLike] | None
-        ) = None,
-    ) -> np.recarray: ...
+    if sys.version_info >= (3, 11):
+        def to_records(
+            self,
+            index: _bool = True,
+            column_dtypes: (
+                _str | npt.DTypeLike | Mapping[HashableT1, npt.DTypeLike] | None
+            ) = None,
+            index_dtypes: (
+                _str | npt.DTypeLike | Mapping[HashableT2, npt.DTypeLike] | None
+            ) = None,
+        ) -> np.recarray: ...
+    else:
+        def to_records(
+            self,
+            index: _bool = True,
+            column_dtypes: (
+                _str | npt.DTypeLike | Mapping[HashableT1, npt.DTypeLike] | None
+            ) = None,
+            index_dtypes: (
+                _str | npt.DTypeLike | Mapping[HashableT2, npt.DTypeLike] | None
+            ) = None,
+        ) -> np.recarray[Any, Any]: ...
+
     @overload
     def to_stata(
         self,
@@ -1381,7 +1389,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         dropna: _bool = ...,
     ) -> DataFrameGroupBy[Period, Literal[False]]: ...
     @overload
-    def groupby(  # pyright: ignore reportOverlappingOverload
+    def groupby(
         self,
         by: IntervalIndex[IntervalT],
         level: IndexLabel | None = ...,
@@ -1394,7 +1402,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     @overload
     def groupby(
         self,
-        by: IntervalIndex[IntervalT],
+        by: IntervalIndex,
         level: IndexLabel | None = ...,
         as_index: Literal[False] = False,
         sort: _bool = ...,
@@ -1480,9 +1488,7 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
         values: _PivotTableValuesTypes = None,
         index: _PivotTableIndexTypes = None,
         columns: _PivotTableColumnsTypes = None,
-        aggfunc: (
-            _PivotAggFunc | Sequence[_PivotAggFunc] | Mapping[Hashable, _PivotAggFunc]
-        ) = "mean",
+        aggfunc: _PivotAggFuncTypes[Scalar] = "mean",
         fill_value: Scalar | None = None,
         margins: _bool = False,
         dropna: _bool = True,
@@ -2863,8 +2869,12 @@ class DataFrame(NDFrame, OpsMixin, _GetItemHack):
     def __rfloordiv__(
         self, other: float | DataFrame | Series[int] | Series[float] | Sequence[float]
     ) -> Self: ...
-    def __truediv__(self, other: float | DataFrame | Series | Sequence) -> Self: ...
-    def __rtruediv__(self, other: float | DataFrame | Series | Sequence) -> Self: ...
+    def __truediv__(
+        self, other: float | DataFrame | Series | Sequence[Any]
+    ) -> Self: ...
+    def __rtruediv__(
+        self, other: float | DataFrame | Series | Sequence[Any]
+    ) -> Self: ...
     @final
     def __bool__(self) -> NoReturn: ...
 

pandas-stubs/core/groupby/groupby.pyi

@@ -338,7 +338,7 @@ class GroupBy(BaseGroupBy[NDFrameT]):
         random_state: RandomState | None = ...,
     ) -> NDFrameT: ...
 
-_GroupByT = TypeVar("_GroupByT", bound=GroupBy)
+_GroupByT = TypeVar("_GroupByT", bound=GroupBy[Any])
 
 # GroupByPlot does not really inherit from PlotAccessor but it delegates
 # to it using __call__ and __getattr__. We lie here to avoid repeating the
@@ -383,15 +383,15 @@ class BaseGroupBy(SelectionMixin[NDFrameT], GroupByIndexingMixin):
     @final
     def __iter__(self) -> Iterator[tuple[Hashable, NDFrameT]]: ...
     @overload
-    def __getitem__(self: BaseGroupBy[DataFrame], key: Scalar) -> generic.SeriesGroupBy: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
+    def __getitem__(self: BaseGroupBy[DataFrame], key: Scalar) -> generic.SeriesGroupBy[Any, Any]: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     @overload
     def __getitem__(
         self: BaseGroupBy[DataFrame], key: Iterable[Hashable]
-    ) -> generic.DataFrameGroupBy: ...
+    ) -> generic.DataFrameGroupBy[Any, Any]: ...
     @overload
     def __getitem__(
         self: BaseGroupBy[Series[S1]],
         idx: list[str] | Index | Series[S1] | MaskType | tuple[Hashable | slice, ...],
-    ) -> generic.SeriesGroupBy: ...
+    ) -> generic.SeriesGroupBy[Any, Any]: ...
     @overload
     def __getitem__(self: BaseGroupBy[Series[S1]], idx: Scalar) -> S1: ...