TYP: enable reportMissingTypeArgument

pandas-stubs/_libs/interval.pyi

@@ -25,7 +25,9 @@ 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=Hashable)
 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 +873,7 @@ ExcelWriterMergeCells: TypeAlias = bool | Literal["columns"]
 
 # read_csv: usecols
 UsecolsArgType: TypeAlias = (
-    SequenceNotStr[Hashable] | range | AnyArrayLike | Callable[[HashableT], bool] | None
+    SequenceNotStr[Hashable] | range | AnyArrayLike | Callable[[Hashable], bool] | None
 )
 
 # maintain the sub-type of any hashable sequence
@@ -918,6 +919,7 @@ 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 +961,10 @@ 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 +974,7 @@ 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 +1015,9 @@ 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 +1051,14 @@ 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=Hashable)
 if TYPE_CHECKING:  # noqa: PYI002
     ByT = TypeVar(
         "ByT",
@@ -1070,7 +1076,7 @@ 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 +1094,23 @@ 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 +1133,10 @@ 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/arrays/base.pyi

@@ -2,6 +2,7 @@ from collections.abc import (
     Iterator,
     Sequence,
 )
+import sys
 from typing import (
     Any,
     Literal,
@@ -55,8 +56,13 @@ class ExtensionArray:
     def ndim(self) -> int: ...
     @property
     def nbytes(self) -> int: ...
-    @overload
-    def astype(self, dtype: np.dtype, copy: bool = True) -> np_1darray: ...
+    if sys.version_info >= (3, 11):
+        @overload
+        def astype(self, dtype: np.dtype, copy: bool = True) -> np_1darray: ...
+    else:
+        @overload
+        def astype(self, dtype: np.dtype[Any], copy: bool = True) -> np_1darray: ...
+
     @overload
     def astype(self, dtype: ExtensionDtype, copy: bool = True) -> ExtensionArray: ...
     @overload

pandas-stubs/core/arrays/datetimes.pyi

@@ -1,4 +1,6 @@
 from datetime import tzinfo as _tzinfo
+import sys
+from typing import Any
 
 import numpy as np
 from pandas.core.arrays.datetimelike import (
@@ -19,8 +21,13 @@ class DatetimeArray(DatetimeLikeArrayMixin, TimelikeOps, DatelikeOps):
     __array_priority__: int = ...
     def __init__(self, values, dtype=..., freq=..., copy: bool = ...) -> None: ...
     # ignore in dtype() is from the pandas source
-    @property
-    def dtype(self) -> np.dtype | DatetimeTZDtype: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    if sys.version_info >= (3, 11):
+        @property
+        def dtype(self) -> np.dtype | DatetimeTZDtype: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+    else:
+        @property
+        def dtype(self) -> np.dtype[Any] | DatetimeTZDtype: ...  # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
+
     @property
     def tz(self): ...
     @tz.setter

pandas-stubs/core/arrays/numpy_.pyi

@@ -1,3 +1,6 @@
+import sys
+from typing import Any
+
 import numpy as np
 from numpy.lib.mixins import NDArrayOperatorsMixin
 from pandas.core.arrays.base import (
@@ -8,8 +11,13 @@ from pandas.core.arrays.base import (
 from pandas.core.dtypes.dtypes import ExtensionDtype
 
 class PandasDtype(ExtensionDtype):
-    @property
-    def numpy_dtype(self) -> np.dtype: ...
+    if sys.version_info >= (3, 11):
+        @property
+        def numpy_dtype(self) -> np.dtype: ...
+    else:
+        @property
+        def numpy_dtype(self) -> np.dtype[Any]: ...
+
     @property
     def itemsize(self) -> int: ...
 

pandas-stubs/core/computation/ops.pyi

@@ -1,3 +1,4 @@
+import sys
 from typing import Any
 
 import numpy as np
@@ -75,8 +76,12 @@ class UnaryOp(Op):
     func = ...
     def __init__(self, op: str, operand) -> None: ...
     def __call__(self, env): ...
-    @property
-    def return_type(self) -> np.dtype: ...
+    if sys.version_info >= (3, 11):
+        @property
+        def return_type(self) -> np.dtype: ...
+    else:
+        @property
+        def return_type(self) -> np.dtype[Any]: ...
 
 class MathCall(Op):
     func = ...

pandas-stubs/core/construction.pyi

@@ -1,5 +1,9 @@
 from collections.abc import Sequence
-from typing import overload
+import sys
+from typing import (
+    Any,
+    overload,
+)
 
 import numpy as np
 from pandas.core.arrays.base import ExtensionArray
@@ -40,9 +44,19 @@ def array(
     dtype: PandasFloatDtypeArg | None = None,
     copy: bool = True,
 ) -> FloatingArray: ...
-@overload
-def array(
-    data: Sequence[object],
-    dtype: str | np.dtype | ExtensionDtype | None = None,
-    copy: bool = True,
-) -> ExtensionArray: ...
+
+if sys.version_info >= (3, 11):
+    @overload
+    def array(
+        data: Sequence[object],
+        dtype: str | np.dtype | ExtensionDtype | None = None,
+        copy: bool = True,
+    ) -> ExtensionArray: ...
+
+else:
+    @overload
+    def array(
+        data: Sequence[object],
+        dtype: str | np.dtype[Any] | ExtensionDtype | None = None,
+        copy: bool = True,
+    ) -> ExtensionArray: ...

pandas-stubs/core/dtypes/dtypes.pyi

@@ -1,4 +1,5 @@
 import datetime as dt
+import sys
 from typing import (
     Any,
     Literal,
@@ -59,5 +60,9 @@ class PeriodDtype(PandasExtensionDtype):
 
 class IntervalDtype(PandasExtensionDtype):
     def __init__(self, subtype: str | npt.DTypeLike | None = ...) -> None: ...
-    @property
-    def subtype(self) -> np.dtype | None: ...
+    if sys.version_info >= (3, 11):
+        @property
+        def subtype(self) -> np.dtype | None: ...
+    else:
+        @property
+        def subtype(self) -> np.dtype[Any] | None: ...