CLN: Use TypeAlias in code where types are declared (#61504)

Author: Dr-Irv

pandas/core/apply.py

@@ -10,6 +10,7 @@
     TYPE_CHECKING,
     Any,
     Literal,
+    TypeAlias,
     cast,
 )
 
@@ -71,7 +72,7 @@
     from pandas.core.resample import Resampler
     from pandas.core.window.rolling import BaseWindow
 
-ResType = dict[int, Any]
+ResType: TypeAlias = dict[int, Any]
 
 
 class BaseExecutionEngine(abc.ABC):

pandas/core/arrays/datetimelike.py

@@ -10,6 +10,7 @@
     TYPE_CHECKING,
     Any,
     Literal,
+    TypeAlias,
     Union,
     cast,
     final,
@@ -161,7 +162,7 @@
         TimedeltaArray,
     )
 
-DTScalarOrNaT = Union[DatetimeLikeScalar, NaTType]
+DTScalarOrNaT: TypeAlias = DatetimeLikeScalar | NaTType
 
 
 def _make_unpacked_invalid_op(op_name: str):
@@ -386,7 +387,7 @@ def __getitem__(self, key: PositionalIndexer2D) -> Self | DTScalarOrNaT:
         # Use cast as we know we will get back a DatetimeLikeArray or DTScalar,
         # but skip evaluating the Union at runtime for performance
         # (see https://github.com/pandas-dev/pandas/pull/44624)
-        result = cast("Union[Self, DTScalarOrNaT]", super().__getitem__(key))
+        result = cast(Union[Self, DTScalarOrNaT], super().__getitem__(key))
         if lib.is_scalar(result):
             return result
         else:

pandas/core/arrays/interval.py

@@ -9,7 +9,7 @@
 from typing import (
     TYPE_CHECKING,
     Literal,
-    Union,
+    TypeAlias,
     overload,
 )
 
@@ -109,8 +109,8 @@
     )
 
 
-IntervalSide = Union[TimeArrayLike, np.ndarray]
-IntervalOrNA = Union[Interval, float]
+IntervalSide: TypeAlias = TimeArrayLike | np.ndarray
+IntervalOrNA: TypeAlias = Interval | float
 
 _interval_shared_docs: dict[str, str] = {}
 

pandas/core/arrays/string_arrow.py

@@ -4,7 +4,6 @@
 import re
 from typing import (
     TYPE_CHECKING,
-    Union,
 )
 import warnings
 
@@ -63,9 +62,6 @@
     from pandas import Series
 
 
-ArrowStringScalarOrNAT = Union[str, libmissing.NAType]
-
-
 def _chk_pyarrow_available() -> None:
     if pa_version_under10p1:
         msg = "pyarrow>=10.0.1 is required for PyArrow backed ArrowExtensionArray."

pandas/core/groupby/generic.py

@@ -17,8 +17,8 @@
     Any,
     Literal,
     NamedTuple,
+    TypeAlias,
     TypeVar,
-    Union,
     cast,
 )
 import warnings
@@ -102,7 +102,7 @@
     from pandas.core.generic import NDFrame
 
 # TODO(typing) the return value on this callable should be any *scalar*.
-AggScalar = Union[str, Callable[..., Any]]
+AggScalar: TypeAlias = str | Callable[..., Any]
 # TODO: validate types on ScalarResult and move to _typing
 # Blocked from using by https://github.com/python/mypy/issues/1484
 # See note at _mangle_lambda_list

pandas/core/groupby/groupby.py

@@ -26,6 +26,7 @@ class providing the base-class of operations.
 from typing import (
     TYPE_CHECKING,
     Literal,
+    TypeAlias,
     TypeVar,
     Union,
     cast,
@@ -449,13 +450,13 @@ def f(self):
         return attr
 
 
-_KeysArgType = Union[
-    Hashable,
-    list[Hashable],
-    Callable[[Hashable], Hashable],
-    list[Callable[[Hashable], Hashable]],
-    Mapping[Hashable, Hashable],
-]
+_KeysArgType: TypeAlias = (
+    Hashable
+    | list[Hashable]
+    | Callable[[Hashable], Hashable]
+    | list[Callable[[Hashable], Hashable]]
+    | Mapping[Hashable, Hashable]
+)
 
 
 class BaseGroupBy(PandasObject, SelectionMixin[NDFrameT], GroupByIndexingMixin):
@@ -957,9 +958,8 @@ def __iter__(self) -> Iterator[tuple[Hashable, NDFrameT]]:
         level = self.level
         result = self._grouper.get_iterator(self._selected_obj)
         # mypy: Argument 1 to "len" has incompatible type "Hashable"; expected "Sized"
-        if (
-            (is_list_like(level) and len(level) == 1)  # type: ignore[arg-type]
-            or (isinstance(keys, list) and len(keys) == 1)
+        if (is_list_like(level) and len(level) == 1) or (  # type: ignore[arg-type]
+            isinstance(keys, list) and len(keys) == 1
         ):
             # GH#42795 - when keys is a list, return tuples even when length is 1
             result = (((key,), group) for key, group in result)

pandas/core/indexing.py

@@ -5,7 +5,6 @@
 from typing import (
     TYPE_CHECKING,
     Any,
-    TypeVar,
     cast,
     final,
 )
@@ -83,6 +82,7 @@
         Axis,
         AxisInt,
         Self,
+        T,
         npt,
     )
 
@@ -91,7 +91,6 @@
         Series,
     )
 
-T = TypeVar("T")
 # "null slice"
 _NS = slice(None, None)
 _one_ellipsis_message = "indexer may only contain one '...' entry"

pandas/core/tools/datetimes.py

@@ -6,6 +6,7 @@
 from itertools import islice
 from typing import (
     TYPE_CHECKING,
+    TypeAlias,
     TypedDict,
     Union,
     cast,
@@ -93,13 +94,12 @@
 # ---------------------------------------------------------------------
 # types used in annotations
 
-ArrayConvertible = Union[list, tuple, AnyArrayLike]
-Scalar = Union[float, str]
-DatetimeScalar = Union[Scalar, date, np.datetime64]
+ArrayConvertible: TypeAlias = list | tuple | AnyArrayLike
+Scalar: TypeAlias = float | str
+DatetimeScalar: TypeAlias = Scalar | date | np.datetime64
 
-DatetimeScalarOrArrayConvertible = Union[DatetimeScalar, ArrayConvertible]
-
-DatetimeDictArg = Union[list[Scalar], tuple[Scalar, ...], AnyArrayLike]
+DatetimeScalarOrArrayConvertible: TypeAlias = DatetimeScalar | ArrayConvertible
+DatetimeDictArg: TypeAlias = list[Scalar] | tuple[Scalar, ...] | AnyArrayLike
 
 
 class YearMonthDayDict(TypedDict, total=True):

pandas/io/excel/_calamine.py

@@ -9,7 +9,7 @@
 from typing import (
     TYPE_CHECKING,
     Any,
-    Union,
+    TypeAlias,
 )
 
 from pandas.compat._optional import import_optional_dependency
@@ -34,7 +34,7 @@
         StorageOptions,
     )
 
-_CellValue = Union[int, float, str, bool, time, date, datetime, timedelta]
+_CellValue: TypeAlias = int | float | str | bool | time | date | datetime | timedelta
 
 
 class CalamineReader(BaseExcelReader["CalamineWorkbook"]):

pandas/io/formats/printing.py

@@ -14,8 +14,8 @@
 from typing import (
     TYPE_CHECKING,
     Any,
+    TypeAlias,
     TypeVar,
-    Union,
 )
 from unicodedata import east_asian_width
 
@@ -27,7 +27,7 @@
 
 if TYPE_CHECKING:
     from pandas._typing import ListLike
-EscapeChars = Union[Mapping[str, str], Iterable[str]]
+EscapeChars: TypeAlias = Mapping[str, str] | Iterable[str]
 _KT = TypeVar("_KT")
 _VT = TypeVar("_VT")