TYP: future annotations

.github/workflows/test.yml

@@ -7,6 +7,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     timeout-minutes: 10
     strategy:
+      fail-fast: false
       matrix:
         os: [ubuntu-latest, windows-latest, macos-latest]
         python-version: ['3.8', '3.9', '3.10']

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
     -   id: pyupgrade
         types_or: [python, pyi]
         types: [text]  # overwrite types: [python]
-        args: [--py38-plus, --keep-runtime-typing]
+        args: [--py38-plus]
 -   repo: https://github.com/PyCQA/flake8
     rev: 4.0.1
     hooks:
@@ -30,7 +30,7 @@ repos:
         - flake8-pyi==22.5.1
         types: [pyi]
         args: [
-          --ignore=E301 E302 E305 E402 E501 E701 E704 F401 F811 W503 Y019 Y022 Y026 Y027 Y034 Y037,
+          --ignore=E301 E302 E305 E402 E501 E701 E704 F401 F811 W503 Y019 Y026 Y027 Y034 Y037,
           # TypeVars in private files are already private
           --per-file-ignores=_*.pyi:Y001
         ]

pandas-stubs/__init__.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import pandas.testing as testing
 
 from . import (

pandas-stubs/_config/__init__.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from .config import (
     describe_option as describe_option,
     get_option as get_option,

pandas-stubs/_config/config.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from contextlib import ContextDecorator
 from typing import (
     Any,

pandas-stubs/_libs/__init__.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from .interval import Interval as Interval
 from .tslibs import (
     NaT as NaT,

pandas-stubs/_libs/indexing.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 class _NDFrameIndexerBase:
     def __init__(self, name: str, obj: object) -> None: ...
     @property

pandas-stubs/_libs/interval.pyi

@@ -4,7 +4,6 @@ from typing import (
     Any,
     Generic,
     TypeVar,
-    Union,
     overload,
 )
 
@@ -79,9 +78,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
     @overload
     def __contains__(self: Interval[_OrderableTimesT], _OrderableTimesT) -> bool: ...
     @overload
-    def __contains__(
-        self: Interval[_OrderableScalarT], key: Union[int, float]
-    ) -> bool: ...
+    def __contains__(self: Interval[_OrderableScalarT], key: int | float) -> bool: ...
     @overload
     def __add__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -91,7 +88,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __add__(self: Interval[float], y: Union[int, float]) -> Interval[float]: ...
+    def __add__(self: Interval[float], y: int | float) -> Interval[float]: ...
     @overload
     def __radd__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -101,7 +98,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __radd__(self: Interval[float], y: Union[int, float]) -> Interval[float]: ...
+    def __radd__(self: Interval[float], y: int | float) -> Interval[float]: ...
     @overload
     def __sub__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -111,7 +108,7 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __sub__(self: Interval[float], y: Union[int, float]) -> Interval[float]: ...
+    def __sub__(self: Interval[float], y: int | float) -> Interval[float]: ...
     @overload
     def __rsub__(
         self: Interval[_OrderableTimesT], y: Timedelta
@@ -121,33 +118,31 @@ class Interval(IntervalMixin, Generic[_OrderableT]):
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __rsub__(self: Interval[float], y: Union[int, float]) -> Interval[float]: ...
+    def __rsub__(self: Interval[float], y: int | float) -> Interval[float]: ...
     @overload
     def __mul__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __mul__(self: Interval[float], y: Union[int, float]) -> Interval[float]: ...
+    def __mul__(self: Interval[float], y: int | float) -> Interval[float]: ...
     @overload
     def __rmul__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __rmul__(self: Interval[float], y: Union[int, float]) -> Interval[float]: ...
+    def __rmul__(self: Interval[float], y: int | float) -> Interval[float]: ...
     @overload
     def __truediv__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __truediv__(self: Interval[float], y: Union[int, float]) -> Interval[float]: ...
+    def __truediv__(self: Interval[float], y: int | float) -> Interval[float]: ...
     @overload
     def __floordiv__(
         self: Interval[int], y: _OrderableScalarT
     ) -> Interval[_OrderableScalarT]: ...
     @overload
-    def __floordiv__(
-        self: Interval[float], y: Union[int, float]
-    ) -> Interval[float]: ...
+    def __floordiv__(self: Interval[float], y: int | float) -> Interval[float]: ...
     def overlaps(self: Interval[_OrderableT], other: Interval[_OrderableT]) -> bool: ...
 
 def intervals_to_interval_bounds(

pandas-stubs/_libs/json.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 def decode(*args, **kwargs): ...
 def dumps(*args, **kwargs): ...
 def encode(*args, **kwargs): ...

pandas-stubs/_libs/lib.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 no_default = None
 
 def infer_dtype(value: object, skipna: bool = ...) -> str: ...

pandas-stubs/_libs/missing.pyi

@@ -1,7 +1,5 @@
 from __future__ import annotations
 
-from typing import Union
-
 class NAType:
     def __new__(cls, *args, **kwargs) -> NAType: ...
     def __format__(self, format_spec: str) -> str: ...
@@ -36,9 +34,9 @@ class NAType:
     def __invert__(self, other) -> NAType: ...
     def __pow__(self, other) -> NAType: ...
     def __rpow__(self, other) -> NAType: ...
-    def __and__(self, other) -> Union[None, NAType]: ...
+    def __and__(self, other) -> NAType | None: ...
     __rand__ = __and__
-    def __or__(self, other) -> Union[bool, NAType]: ...
+    def __or__(self, other) -> bool | NAType: ...
     __ror__ = __or__
     def __xor__(self, other) -> NAType: ...
     __rxor__ = __xor__

pandas-stubs/_libs/ops_dispatch.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 DISPATCHED_UFUNCS = ...
 REVERSED_NAMES = ...
 UFUNC_ALIASES = ...

pandas-stubs/_libs/properties.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from typing import Callable
 
 class CachedProperty:

pandas-stubs/_libs/sparse.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 class SparseIndex: ...
 class BlockIndex(SparseIndex): ...
 class IntIndex(SparseIndex): ...

pandas-stubs/_libs/tslibs/__init__.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 __all__ = [
     "Period",
     "Timestamp",

pandas-stubs/_libs/tslibs/base.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from datetime import datetime
 
 class ABCTimestamp(datetime): ...

pandas-stubs/_libs/tslibs/ccalendar.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from typing import Sequence
 
 def dayofweek(y: int, m: int, d: int) -> int: ...

pandas-stubs/_libs/tslibs/conversion.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from datetime import datetime
 
 def localize_pydatetime(dt: datetime, tz: object) -> datetime: ...

pandas-stubs/_libs/tslibs/dtypes.pyi

@@ -1,5 +1,6 @@
+from __future__ import annotations
+
 from enum import Enum
-from typing import Dict
 
 from .offsets import BaseOffset
 
@@ -13,7 +14,7 @@ class PeriodDtypeBase:
     @classmethod
     def from_date_offset(cls, offset: BaseOffset) -> PeriodDtypeBase: ...
 
-attrname_to_abbrevs: Dict[str, str]
+attrname_to_abbrevs: dict[str, str]
 
 class FreqGroup:
     FR_ANN: int

pandas-stubs/_libs/tslibs/nattype.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from datetime import (
     datetime,
     timedelta,

pandas-stubs/_libs/tslibs/np_datetime.pyi

@@ -1 +1,3 @@
+from __future__ import annotations
+
 class OutOfBoundsDatetime(ValueError): ...

pandas-stubs/_libs/tslibs/offsets.pyi

@@ -204,7 +204,7 @@ class _CustomBusinessMonth(BusinessMixin):
         n: int = ...,
         normalize: bool = ...,
         offset: timedelta = ...,
-        holidays: None | list = ...,
+        holidays: list | None = ...,
     ): ...
 
 class CustomBusinessDay(BusinessDay):
@@ -224,7 +224,7 @@ class CustomBusinessHour(BusinessHour):
         start: str = ...,
         end: str = ...,
         offset: timedelta = ...,
-        holidays: None | list = ...,
+        holidays: list | None = ...,
     ): ...
 
 class CustomBusinessMonthEnd(_CustomBusinessMonth): ...

pandas-stubs/_libs/tslibs/parsing.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from typing import Any
 
 def parse_time_string(*args, **kwargs) -> Any: ...

pandas-stubs/_libs/tslibs/strptime.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from typing import Any
 
 def array_strptime(*args, **kwargs) -> Any: ...

pandas-stubs/_libs/tslibs/timedeltas.pyi

@@ -1,8 +1,9 @@
+from __future__ import annotations
+
 from datetime import timedelta
 from typing import (
     ClassVar,
     Literal,
-    Type,
     TypeVar,
     overload,
 )
@@ -80,7 +81,7 @@ class Timedelta(timedelta):
     resolution: ClassVar[Timedelta]
     value: int  # np.int64
     def __new__(
-        cls: Type[_S],
+        cls: type[_S],
         value=...,
         unit: str = ...,
         **kwargs: int | float | np.integer | np.floating,
@@ -130,7 +131,7 @@ class Timedelta(timedelta):
     @overload
     def __rfloordiv__(self, other: timedelta | str) -> int: ...
     @overload
-    def __rfloordiv__(self, other: None | NaTType) -> NaTType: ...
+    def __rfloordiv__(self, other: NaTType | None) -> NaTType: ...
     @overload
     def __rfloordiv__(self, other: np.ndarray) -> npt.NDArray[np.timedelta64]: ...
     @overload

pandas-stubs/_libs/tslibs/timestamps.pyi

@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 from datetime import (
     date as _date,
     datetime,
@@ -40,8 +42,8 @@ class Timestamp(datetime):
         | _date
         | datetime
         | np.datetime64 = ...,
-        freq: int | None | str | BaseOffset = ...,
-        tz: str | _tzinfo | None | int = ...,
+        freq: int | str | BaseOffset | None = ...,
+        tz: str | _tzinfo | int | None = ...,
         unit: str | int | None = ...,
         year: int | None = ...,
         month: int | None = ...,

pandas-stubs/_libs/tslibs/tzconversion.pyi

@@ -1 +1,3 @@
+from __future__ import annotations
+
 def tz_convert_from_utc_single(val: int, tz: str) -> int: ...

pandas-stubs/_libs/tslibs/vectorized.pyi

@@ -1,23 +1,19 @@
-from typing import (
-    List,
-    Optional,
-    Sequence,
-)
+from __future__ import annotations
+
+from typing import Sequence
 
 import numpy as np
 
 from .dtypes import Resolution
 
 def normalize_i8_timestamps(
-    stamps: Sequence[int], tz: Optional[str] = ...
-) -> List[int]: ...
-def is_date_array_normalized(
-    stamps: Sequence[int], tz: Optional[str] = ...
-) -> bool: ...
+    stamps: Sequence[int], tz: str | None = ...
+) -> list[int]: ...
+def is_date_array_normalized(stamps: Sequence[int], tz: str | None = ...) -> bool: ...
 def dt64arr_to_periodarr(
-    stamps: Sequence[int], freq: int, tz: Optional[str] = ...
-) -> List[int]: ...
+    stamps: Sequence[int], freq: int, tz: str | None = ...
+) -> list[int]: ...
 def ints_to_pydatetime(
     arr: Sequence[int], tz: str = ..., freq: str = ..., fold: bool = ..., box: str = ...
 ) -> np.ndarray: ...
-def get_resolution(stamps: Sequence[int], tz: Optional[str] = ...) -> Resolution: ...
+def get_resolution(stamps: Sequence[int], tz: str | None = ...) -> Resolution: ...