Replace flake8 and pyupgrade with ruff

Author: twoertwein

.pre-commit-config.yaml

@@ -10,29 +10,16 @@ repos:
     rev: 5.12.0
     hooks:
     -   id: isort
--   repo: https://github.com/asottile/pyupgrade
-    rev: v3.9.0
+-   repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.0.278
     hooks:
-    -   id: pyupgrade
-        types_or: [python, pyi]
-        types: [text]  # overwrite types: [python]
-        args: [--py38-plus]
--   repo: https://github.com/PyCQA/flake8
-    rev: 6.0.0
-    hooks:
-    -   id: flake8
-        name: flake8 (py)
-        types: [python]
-        args: [--ignore=E501 F841]
-    -   id: flake8
-        name: flake8 (pyi)
-        additional_dependencies:
-        - flake8-pyi==23.6.0
-        types: [pyi]
+    -   id: ruff
         args: [
-          --ignore=E301 E302 E305 E402 E501 E701 E704 F401 F811 F821 W503 Y042,
-          # TypeVars in private files are already private
-          --per-file-ignores=_*.pyi:Y001
+          --exit-non-zero-on-fix,
+          --target-version, py38,
+          --extend-select, "PYI,UP,RUF100",
+          --ignore, "E501,E731,F841,PYI042",
+          --per-file-ignores, "_*.pyi:PYI001, _*.pyi:PYI030"
         ]
 -   repo: https://github.com/codespell-project/codespell
     rev: v2.2.5

pandas-stubs/_libs/tslibs/period.pyi

@@ -20,13 +20,12 @@ from pandas.core.series import (
 from typing_extensions import TypeAlias
 
 from pandas._libs.tslibs import NaTType
+from pandas._libs.tslibs.offsets import BaseOffset
 from pandas._libs.tslibs.timestamps import Timestamp
 from pandas._typing import npt
 
 class IncompatibleFrequency(ValueError): ...
 
-from pandas._libs.tslibs.offsets import BaseOffset
-
 _PeriodAddSub: TypeAlias = (
     Timedelta | datetime.timedelta | np.timedelta64 | np.int64 | int | BaseOffset
 )

pandas-stubs/_typing.pyi

@@ -80,7 +80,7 @@ DtypeArg: TypeAlias = Dtype | Mapping[Any, Dtype]
 DtypeBackend: TypeAlias = Literal["pyarrow", "numpy_nullable"]
 BooleanDtypeArg: TypeAlias = (
     # Builtin bool type and its string alias
-    type[bool]  # noqa: Y030
+    type[bool]
     | Literal["bool"]
     # Pandas nullable boolean type and its string alias
     | pd.BooleanDtype
@@ -90,7 +90,7 @@ BooleanDtypeArg: TypeAlias = (
 )
 IntDtypeArg: TypeAlias = (
     # Builtin integer type and its string alias
-    type[int]  # noqa: Y030
+    type[int]
     | Literal["int"]
     # Pandas nullable integer types and their string aliases
     | pd.Int8Dtype
@@ -117,7 +117,7 @@ IntDtypeArg: TypeAlias = (
 )
 StrDtypeArg: TypeAlias = (
     # Builtin str type and its string alias
-    type[str]  # noqa: Y030
+    type[str]
     | Literal["str"]
     # Pandas nullable string type and its string alias
     | pd.StringDtype
@@ -126,7 +126,7 @@ StrDtypeArg: TypeAlias = (
 BytesDtypeArg: TypeAlias = type[bytes]
 FloatDtypeArg: TypeAlias = (
     # Builtin float type and its string alias
-    type[float]  # noqa: Y030
+    type[float]
     | Literal["float"]
     # Pandas nullable float types and their string aliases
     | pd.Float32Dtype
@@ -140,7 +140,7 @@ FloatDtypeArg: TypeAlias = (
 )
 ComplexDtypeArg: TypeAlias = (
     # Builtin complex type and its string alias
-    type[complex]  # noqa: Y030
+    type[complex]
     | Literal["complex"]
     # Numpy complex types and their aliases
     | type[np.complex64]

pandas-stubs/core/generic.pyi

@@ -18,6 +18,7 @@ import numpy as np
 from pandas import Index
 from pandas.core.base import PandasObject
 import pandas.core.indexing as indexing
+from pandas.core.series import Series
 import sqlalchemy.engine
 
 from pandas._typing import (
@@ -479,5 +480,3 @@ class NDFrame(PandasObject, indexing.IndexingMixin):
     ) -> NDFrame: ...
     def first_valid_index(self): ...
     def last_valid_index(self): ...
-
-from pandas.core.series import Series

pandas-stubs/core/indexes/accessors.pyi

@@ -46,11 +46,14 @@ class Properties(PandasDelegate, PandasObject, NoNewAttributesMixin):
 _DTFieldOpsReturnType = TypeVar("_DTFieldOpsReturnType", Series[int], _IntIndexType)
 
 class _DatetimeFieldOps(
-    _DayLikeFieldOps[_DTFieldOpsReturnType], _MiniSeconds[_DTFieldOpsReturnType]
+    _DayLikeFieldOps[_DTFieldOpsReturnType],  # noqa: F821
+    _MiniSeconds[_DTFieldOpsReturnType],  # noqa: F821
 ): ...
 class PeriodIndexFieldOps(
-    _DayLikeFieldOps[_IntIndexType],
-    _PeriodProperties[DatetimeIndex, _IntIndexType, Index, DatetimeIndex, PeriodIndex],
+    _DayLikeFieldOps[_IntIndexType],  # noqa: F821
+    _PeriodProperties[  # noqa: F821
+        DatetimeIndex, _IntIndexType, Index, DatetimeIndex, PeriodIndex
+    ],
 ): ...
 
 class _DayLikeFieldOps(Generic[_DTFieldOpsReturnType]):

tests/test_timefuncs.py

@@ -1,12 +1,10 @@
-# flake8: noqa: F841
 from __future__ import annotations
 
 import datetime as dt
 from typing import (
     TYPE_CHECKING,
     Any,
     Optional,
-    Union,
 )
 
 import numpy as np
@@ -43,11 +41,9 @@
 )
 
 if TYPE_CHECKING:
-    from pandas.core.series import (
-        PeriodSeries,
-        TimedeltaSeries,
-        TimestampSeries,
-    )
+    from pandas.core.series import PeriodSeries  # noqa: F401
+    from pandas.core.series import TimedeltaSeries  # noqa: F401
+    from pandas.core.series import TimestampSeries  # noqa: F401
 
 if TYPE_CHECKING:
     from pandas.core.indexes.base import _IntIndexType
@@ -310,15 +306,15 @@ def test_to_datetime_nat() -> None:
     check(
         assert_type(
             pd.to_datetime("2021-03-01", errors="coerce"),
-            "Union[pd.Timestamp, NaTType]",
+            "pd.Timestamp | NaTType",
         ),
         pd.Timestamp,
     )
 
     check(
         assert_type(
             pd.to_datetime("not a date", errors="coerce"),
-            "Union[pd.Timestamp, NaTType]",
+            "pd.Timestamp | NaTType",
         ),
         NaTType,
     )