resolve conflicts with master

pandas/core/arrays/base.py

@@ -13,9 +13,7 @@
     TYPE_CHECKING,
     Any,
     Callable,
-    Dict,
     Iterator,
-    Optional,
     Sequence,
     TypeVar,
     cast,
@@ -28,6 +26,7 @@
     ArrayLike,
     Dtype,
     NpDtype,
+    PositionalIndexer,
     Shape,
 )
 from pandas.compat import set_function_name
@@ -389,7 +388,7 @@ def __iter__(self) -> Iterator[Any]:
         for i in range(len(self)):
             yield self[i]
 
-    def __contains__(self, item: Any) -> Union[bool, np.bool_]:
+    def __contains__(self, item) -> bool | np.bool_:
         """
         Return for `item in self`.
         """
@@ -428,9 +427,9 @@ def __ne__(self, other: Any) -> ArrayLike:  # type: ignore[override]
 
     def to_numpy(
         self,
-        dtype: Optional[NpDtype] = None,
+        dtype: NpDtype | None = None,
         copy: bool = False,
-        na_value: Optional[Any] = lib.no_default,
+        na_value: Any | None = lib.no_default,
     ) -> np.ndarray:
         """
         Convert to a NumPy ndarray.
@@ -683,9 +682,9 @@ def argmax(self, skipna: bool = True) -> int:
 
     def fillna(
         self,
-        value: Optional[Union[Any, ArrayLike]] = None,
-        method: Optional[Literal["backfill", "bfill", "ffill", "pad"]] = None,
-        limit: Optional[int] = None,
+        value: Any | ArrayLike | None = None,
+        method: Literal["backfill", "bfill", "ffill", "pad"] | None = None,
+        limit: int | None = None,
     ) -> ExtensionArray:
         """
         Fill NA/NaN values using the specified method.
@@ -818,7 +817,7 @@ def searchsorted(
         self,
         value: Sequence[Any],
         side: Literal["left", "right"] = "left",
-        sorter: Optional[Sequence[Any]] = None,
+        sorter: Sequence[Any] | None = None,
     ) -> np.ndarray:
         """
         Find indices where elements should be inserted to maintain order.
@@ -1042,7 +1041,7 @@ def factorize(self, na_sentinel: int = -1) -> tuple[np.ndarray, ExtensionArray]:
     @Appender(_extension_array_shared_docs["repeat"])
     def repeat(
         self,
-        repeats: Union[int, Sequence[int]],
+        repeats: int | Sequence[int],
         axis: Literal[None, 0] = None,
     ) -> ExtensionArray:
         nv.validate_repeat((), {"axis": axis})
@@ -1241,9 +1240,7 @@ def transpose(self, *axes: int) -> ExtensionArray:
     def T(self) -> ExtensionArray:
         return self.transpose()
 
-    def ravel(
-        self, order: Optional[Literal["C", "F", "A", "K"]] = "C"
-    ) -> ExtensionArray:
+    def ravel(self, order: Literal["C", "F", "A", "K"] | None = "C") -> ExtensionArray:
         """
         Return a flattened view on this array.
 
@@ -1323,7 +1320,7 @@ def __hash__(self) -> int:
     # ------------------------------------------------------------------------
     # Non-Optimized Default Methods
 
-    def delete(self, loc: Union[int, Sequence[int]]) -> ExtensionArray:
+    def delete(self, loc: int | Sequence[int]) -> ExtensionArray:
         indexer = np.delete(np.arange(len(self)), loc)
         return self.take(indexer)
 

pandas/core/arrays/boolean.py

@@ -13,7 +13,7 @@
 from pandas._typing import (
     ArrayLike,
     Dtype,
-    DtypeArg,
+    type_t,
 )
 from pandas.compat.numpy import function as nv
 
@@ -309,7 +309,7 @@ def dtype(self) -> BooleanDtype:
 
     @classmethod
     def _from_sequence(
-        cls, scalars, *, dtype: Optional[DtypeArg] = None, copy: bool = False
+        cls, scalars, *, dtype: Dtype | None = None, copy: bool = False
     ) -> BooleanArray:
         if dtype:
             assert dtype == "boolean"

pandas/core/arrays/interval.py

@@ -9,7 +9,6 @@
 from typing import (
     Sequence,
     TypeVar,
-    Union,
     cast,
 )
 
@@ -1519,7 +1518,7 @@ def delete(self: IntervalArrayT, loc) -> IntervalArrayT:
 
     @Appender(_extension_array_shared_docs["repeat"] % _shared_docs_kwargs)
     def repeat(
-        self: IntervalArrayT, repeats: Union[int, Sequence[int]], axis=None
+        self: IntervalArrayT, repeats: int | Sequence[int], axis=None
     ) -> IntervalArrayT:
         nv.validate_repeat((), {"axis": axis})
         left_repeat = self.left.repeat(repeats)

pandas/core/arrays/string_arrow.py

@@ -227,15 +227,15 @@ def _chk_pyarrow_available(cls) -> None:
             raise ImportError(msg)
 
     @classmethod
-    def _from_sequence(cls, scalars, dtype: Optional[DtypeArg] = None, copy=False):
+    def _from_sequence(cls, scalars, dtype: DtypeArg | None = None, copy: bool = False):
         cls._chk_pyarrow_available()
         # convert non-na-likes to str, and nan-likes to ArrowStringDtype.na_value
         scalars = lib.ensure_string_array(scalars, copy=False)
         return cls(pa.array(scalars, type=pa.string(), from_pandas=True))
 
     @classmethod
     def _from_sequence_of_strings(
-        cls, strings, dtype: Optional[DtypeArg] = None, copy=False
+        cls, strings, dtype: DtypeArg | None = None, copy: bool = False
     ):
         return cls._from_sequence(strings, dtype=dtype, copy=copy)
 
@@ -693,7 +693,7 @@ def value_counts(self, dropna: bool = True) -> Series:
 
     _str_na_value = ArrowStringDtype.na_value
 
-    def _str_map(self, f, na_value=None, dtype: Dtype | None = None):
+    def _str_map(self, f, na_value=None, dtype: DtypeArg | None = None):
         # TODO: de-duplicate with StringArray method. This method is moreless copy and
         # paste.
 

pandas/core/base.py

@@ -436,7 +436,7 @@ def array(self) -> ExtensionArray:
 
     def to_numpy(
         self,
-        dtype: Optional[NpDtype] = None,
+        dtype: NpDtype | None = None,
         copy: bool = False,
         na_value=lib.no_default,
         **kwargs,

pandas/core/dtypes/base.py

@@ -7,11 +7,7 @@
 from typing import (
     TYPE_CHECKING,
     Any,
-    List,
-    Optional,
-    Tuple,
-    Type,
-    Union,
+    TypeVar,
     cast,
 )
 
@@ -33,7 +29,7 @@
     from pandas.core.arrays import ExtensionArray
 
     # To parameterize on same ExtensionDtype
-    E = TypeVar("E", bound="ExtensionDtype")
+    ExtensionDtypeT = TypeVar("ExtensionDtypeT", bound="ExtensionDtype")
 
 
 class ExtensionDtype:
@@ -160,7 +156,7 @@ def na_value(self) -> object:
         return np.nan
 
     @property
-    def type(self) -> type_t[Any]:
+    def type(self) -> type[Any]:
         """
         The scalar type for the array, e.g. ``int``
 
@@ -373,7 +369,7 @@ def _get_common_dtype(self, dtypes: list[DtypeObj]) -> DtypeObj | None:
             return None
 
 
-def register_extension_dtype(cls: type[E]) -> type[E]:
+def register_extension_dtype(cls: type[ExtensionDtypeT]) -> type[ExtensionDtypeT]:
     """
     Register an ExtensionType with pandas as class decorator.
 
@@ -429,7 +425,7 @@ def register(self, dtype: type[ExtensionDtype]) -> None:
 
         self.dtypes.append(dtype)
 
-    def find(self, dtype: Union[Type[ExtensionDtype], str]) -> Optional[ExtensionDtype]:
+    def find(self, dtype: type[ExtensionDtype] | str) -> ExtensionDtype | None:
         """
         Parameters
         ----------

pandas/core/indexes/extension.py

@@ -337,7 +337,10 @@ def _get_unique_index(self):
             return self
 
         result = self._data.unique()
-        return type(self)._simple_new(result, name=self.name)
+        # error: Argument 1 to "_simple_new" of "ExtensionIndex" has incompatible
+        # type "ExtensionArray"; expected "Union[IntervalArray,
+        # NDArrayBackedExtensionArray]"
+        return type(self)._simple_new(result, name=self.name)  # type: ignore[arg-type]
 
     @doc(Index.map)
     def map(self, mapper, na_action=None):

pandas/core/internals/managers.py

@@ -10,7 +10,6 @@
     Hashable,
     Sequence,
     TypeVar,
-    Union,
     cast,
 )
 import warnings
@@ -629,7 +628,7 @@ def copy_func(ax):
     def as_array(
         self,
         transpose: bool = False,
-        dtype: Optional[NpDtype] = None,
+        dtype: NpDtype | None = None,
         copy: bool = False,
         na_value=lib.no_default,
     ) -> np.ndarray: