line-based ignores for PYI030

Author: twoertwein

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ repos:
           --target-version, py38,
           --extend-select, "PYI,UP,RUF100",
           --ignore, "E501,E731,F841,PYI042",
-          --per-file-ignores, "_*.pyi:PYI001, _*.pyi:PYI030",
+          --per-file-ignores, "_*.pyi:PYI001",
           --fix
         ]
 -   repo: https://github.com/codespell-project/codespell

pandas-stubs/_typing.pyi

@@ -91,7 +91,7 @@ DtypeBackend: TypeAlias = Literal["pyarrow", "numpy_nullable"]
 
 BooleanDtypeArg: TypeAlias = (
     # Builtin bool type and its string alias
-    type[bool]
+    type[bool]  # noqa: PYI030
     | Literal["bool"]
     # Pandas nullable boolean type and its string alias
     | pd.BooleanDtype
@@ -105,7 +105,7 @@ BooleanDtypeArg: TypeAlias = (
 )
 IntDtypeArg: TypeAlias = (
     # Builtin integer type and its string alias
-    type[int]
+    type[int]  # noqa: PYI030
     | Literal["int"]
     # Pandas nullable integer types and their string aliases
     | pd.Int8Dtype
@@ -166,7 +166,7 @@ UIntDtypeArg: TypeAlias = (
 )
 StrDtypeArg: TypeAlias = (
     # Builtin str type and its string alias
-    type[str]
+    type[str]  # noqa: PYI030
     | Literal["str"]
     # Pandas nullable string type and its string alias
     | pd.StringDtype
@@ -175,7 +175,7 @@ StrDtypeArg: TypeAlias = (
 BytesDtypeArg: TypeAlias = type[bytes]
 FloatDtypeArg: TypeAlias = (
     # Builtin float type and its string alias
-    type[float]
+    type[float]  # noqa: PYI030
     | Literal["float"]
     # Pandas nullable float types and their string aliases
     | pd.Float32Dtype
@@ -206,7 +206,7 @@ FloatDtypeArg: TypeAlias = (
 )
 ComplexDtypeArg: TypeAlias = (
     # Builtin complex type and its string alias
-    type[complex]
+    type[complex]  # noqa: PYI030
     | Literal["complex"]
     # Numpy complex types and their aliases
     # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.csingle

pandas-stubs/core/indexes/accessors.pyi

@@ -45,17 +45,6 @@ class Properties(PandasDelegate, PandasObject, NoNewAttributesMixin):
 
 _DTFieldOpsReturnType = TypeVar("_DTFieldOpsReturnType", Series[int], _IntIndexType)
 
-class _DatetimeFieldOps(
-    _DayLikeFieldOps[_DTFieldOpsReturnType],  # noqa: F821
-    _MiniSeconds[_DTFieldOpsReturnType],  # noqa: F821
-): ...
-class PeriodIndexFieldOps(
-    _DayLikeFieldOps[_IntIndexType],  # noqa: F821
-    _PeriodProperties[  # noqa: F821
-        DatetimeIndex, _IntIndexType, Index, DatetimeIndex, PeriodIndex
-    ],
-): ...
-
 class _DayLikeFieldOps(Generic[_DTFieldOpsReturnType]):
     @property
     def year(self) -> _DTFieldOpsReturnType: ...
@@ -92,6 +81,10 @@ class _MiniSeconds(Generic[_DTFieldOpsReturnType]):
     @property
     def nanosecond(self) -> _DTFieldOpsReturnType: ...
 
+class _DatetimeFieldOps(
+    _DayLikeFieldOps[_DTFieldOpsReturnType], _MiniSeconds[_DTFieldOpsReturnType]
+): ...
+
 _DTBoolOpsReturnType = TypeVar("_DTBoolOpsReturnType", Series[bool], np_ndarray_bool)
 
 class _IsLeapYearProperty(Generic[_DTBoolOpsReturnType]):
@@ -341,6 +334,10 @@ class _PeriodProperties(
         how: Literal["E", "END", "FINISH", "S", "START", "BEGIN"] = ...,
     ) -> _PeriodPAReturnTypes: ...
 
+class PeriodIndexFieldOps(
+    _DayLikeFieldOps[_IntIndexType],
+    _PeriodProperties[DatetimeIndex, _IntIndexType, Index, DatetimeIndex, PeriodIndex],
+): ...
 class PeriodProperties(
     Properties,
     _PeriodProperties[