feat(ruff): comply to ANN202, 002, TRY, PT, BLE

pandas-stubs/_testing/__init__.pyi

@@ -176,7 +176,7 @@ def assert_frame_equal(
 def assert_equal(left, right, **kwargs: Any) -> None: ...
 def assert_sp_array_equal(left: SparseArray, right: SparseArray) -> None: ...
 def assert_contains_all(iterable: Iterable[T], dic: Container[T]) -> None: ...
-def assert_copy(iter1: Iterable[T], iter2: Iterable[T], **eql_kwargs) -> None: ...
+def assert_copy(iter1: Iterable[T], iter2: Iterable[T], **eql_kwargs: Any) -> None: ...
 @contextmanager
 def assert_produces_warning(
     expected_warning: (

pandas-stubs/core/arrays/base.pyi

@@ -21,6 +21,8 @@ from pandas._typing import (
 from pandas.core.dtypes.dtypes import ExtensionDtype as ExtensionDtype
 
 class ExtensionArray:
+    def __array__(self, dtype=...) -> np_1darray: ...
+    def __array_ufunc__(self, ufunc, method, *inputs: Any, **kwargs: Any): ...
     @overload
     def __getitem__(self, item: ScalarIndexer) -> Any: ...
     @overload

pandas-stubs/core/arrays/boolean.pyi

@@ -20,7 +20,6 @@ class BooleanArray(BaseMaskedArray):
     ) -> None: ...
     @property
     def dtype(self): ...
-    def __array_ufunc__(self, ufunc, method, *inputs, **kwargs: Any): ...
     def __setitem__(self, key, value) -> None: ...
     def astype(self, dtype, copy: bool = True): ...
     def any(self, *, skipna: bool = ..., **kwargs: Any): ...

pandas-stubs/core/arrays/categorical.pyi

@@ -89,8 +89,6 @@ class Categorical(ExtensionArray):
     @property
     def shape(self): ...
     def shift(self, periods=1, fill_value=...): ...
-    def __array__(self, dtype=...) -> np_1darray: ...
-    def __array_ufunc__(self, ufunc, method, *inputs, **kwargs: Any): ...
     @property
     def T(self): ...
     @property
@@ -112,7 +110,6 @@ class Categorical(ExtensionArray):
     def take(
         self, indexer: TakeIndexer, *, allow_fill: bool = ..., fill_value=...
     ) -> Categorical: ...
-    def __len__(self) -> int: ...
     def __iter__(self): ...
     def __contains__(self, key) -> bool: ...
     @overload

pandas-stubs/core/arrays/datetimelike.pyi

@@ -66,10 +66,8 @@ class DatetimeLikeArrayMixin(ExtensionOpsMixin, ExtensionArray):
     def asi8(self) -> np.ndarray: ...
     @property
     def nbytes(self): ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
     @property
     def size(self) -> int: ...
-    def __len__(self) -> int: ...
     @overload
     def __getitem__(self, key: ScalarIndexer) -> DTScalarOrNaT: ...
     @overload

pandas-stubs/core/arrays/datetimes.pyi

@@ -29,7 +29,6 @@ class DatetimeArray(DatetimeLikeArrayMixin, TimelikeOps, DatelikeOps):
     def tzinfo(self) -> _tzinfo | None: ...
     @property
     def is_normalized(self): ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
     def __iter__(self): ...
     def astype(self, dtype, copy: bool = True): ...
     def tz_convert(self, tz: TimeZones): ...

pandas-stubs/core/arrays/integer.pyi

@@ -1,5 +1,3 @@
-from typing import Any
-
 from pandas.core.arrays.masked import BaseMaskedArray
 
 from pandas._libs.missing import NAType
@@ -19,7 +17,6 @@ class IntegerArray(BaseMaskedArray):
     @property
     def dtype(self) -> _IntegerDtype: ...
     def __init__(self, values, mask, copy: bool = ...) -> None: ...
-    def __array_ufunc__(self, ufunc, method, *inputs, **kwargs: Any): ...
     def __setitem__(self, key, value) -> None: ...
     def astype(self, dtype, copy: bool = True): ...
 

pandas-stubs/core/arrays/interval.pyi

@@ -58,7 +58,6 @@ class IntervalArray(IntervalMixin, ExtensionArray):
         dtype=None,
     ): ...
     def __iter__(self): ...
-    def __len__(self) -> int: ...
     @overload
     def __getitem__(self, key: ScalarIndexer) -> IntervalOrNA: ...
     @overload
@@ -100,7 +99,6 @@ class IntervalArray(IntervalMixin, ExtensionArray):
     def mid(self) -> Index: ...
     @property
     def is_non_overlapping_monotonic(self) -> bool: ...
-    def __array__(self, dtype=...) -> np_1darray: ...
     def __arrow_array__(self, type=...): ...
     def to_tuples(self, na_tuple: bool = True): ...
     def repeat(self, repeats, axis: Axis | None = ...): ...

pandas-stubs/core/arrays/masked.pyi

@@ -23,7 +23,6 @@ class BaseMaskedArray(ExtensionArray, ExtensionOpsMixin):
     @overload
     def __getitem__(self, item: SequenceIndexer) -> Self: ...
     def __iter__(self): ...
-    def __len__(self) -> int: ...
     def __invert__(self): ...
     def to_numpy(
         self,
@@ -32,7 +31,6 @@ class BaseMaskedArray(ExtensionArray, ExtensionOpsMixin):
         na_value: Scalar = ...,
     ) -> np.ndarray: ...
     __array_priority__: int = ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
     def __arrow_array__(self, type=...): ...
     def isna(self): ...
     @property

pandas-stubs/core/arrays/numpy_.pyi

@@ -1,5 +1,3 @@
-from typing import Any
-
 import numpy as np
 from numpy.lib.mixins import NDArrayOperatorsMixin
 from pandas.core.arrays.base import (
@@ -15,5 +13,4 @@ class PandasDtype(ExtensionDtype):
     @property
     def itemsize(self) -> int: ...
 
-class PandasArray(ExtensionArray, ExtensionOpsMixin, NDArrayOperatorsMixin):
-    def __array_ufunc__(self, ufunc, method, *inputs, **kwargs: Any): ...
+class PandasArray(ExtensionArray, ExtensionOpsMixin, NDArrayOperatorsMixin): ...

pandas-stubs/core/arrays/period.pyi

@@ -1,4 +1,3 @@
-import numpy as np
 from pandas import PeriodDtype
 from pandas.core.arrays.datetimelike import (
     DatelikeOps,
@@ -13,7 +12,6 @@ class PeriodArray(DatetimeLikeArrayMixin, DatelikeOps):
     def __init__(self, values, freq=..., dtype=..., copy: bool = ...) -> None: ...
     @property
     def dtype(self) -> PeriodDtype: ...
-    def __array__(self, dtype=...) -> np.ndarray: ...
     def __arrow_array__(self, type=...): ...
     year: int = ...
     month: int = ...

pandas-stubs/core/arrays/sparse/array.pyi

@@ -5,7 +5,6 @@ from typing import (
     overload,
 )
 
-import numpy as np
 from pandas.core.arrays import (
     ExtensionArray,
     ExtensionOpsMixin,
@@ -33,7 +32,6 @@ class SparseArray(ExtensionArray, ExtensionOpsMixin):
     ) -> None: ...
     @classmethod
     def from_spmatrix(cls, data): ...
-    def __array__(self, dtype=..., copy=...) -> np.ndarray: ...
     def __setitem__(self, key, value) -> None: ...
     @property
     def sp_index(self): ...
@@ -47,7 +45,6 @@ class SparseArray(ExtensionArray, ExtensionOpsMixin):
     def fill_value(self, value) -> None: ...
     @property
     def kind(self) -> str: ...
-    def __len__(self) -> int: ...
     @property
     def nbytes(self) -> int: ...
     @property
@@ -78,5 +75,4 @@ class SparseArray(ExtensionArray, ExtensionOpsMixin):
     def mean(self, axis: int = ..., *args: Any, **kwargs: Any): ...
     @property
     def T(self): ...
-    def __array_ufunc__(self, ufunc, method, *inputs, **kwargs: Any): ...
     def __abs__(self): ...

pandas-stubs/core/indexes/category.pyi

@@ -13,6 +13,7 @@ from typing_extensions import Self
 from pandas._typing import (
     S1,
     DtypeArg,
+    np_1darray,
 )
 
 class CategoricalIndex(ExtensionIndex[S1], accessor.PandasDelegate):
@@ -35,7 +36,7 @@ class CategoricalIndex(ExtensionIndex[S1], accessor.PandasDelegate):
     def __contains__(self, key) -> bool: ...
     def __array__(
         self, dtype: DtypeArg = ..., copy: bool | None = ...
-    ) -> np.ndarray: ...
+    ) -> np_1darray: ...
     @property
     def is_unique(self) -> bool: ...
     @property

pandas-stubs/core/indexes/range.pyi

@@ -74,7 +74,6 @@ class RangeIndex(_IndexSubclassBase[int, np.int64]):
         return_indexers: bool = ...,
         sort: bool = ...,
     ): ...
-    def __len__(self) -> int: ...
     @property
     def size(self) -> int: ...
     def __floordiv__(self, other): ...

pandas-stubs/plotting/_misc.pyi

@@ -49,7 +49,7 @@ def radviz(
     ax: Axes | None = None,
     color: _Color | Sequence[_Color] | None = None,
     colormap: str | Colormap | None = None,
-    **kwds,
+    **kwds: Any,
 ) -> Axes: ...
 def andrews_curves(
     frame: DataFrame,
@@ -65,7 +65,7 @@ def bootstrap_plot(
     fig: Figure | None = None,
     size: int = 50,
     samples: int = 500,
-    **kwds,
+    **kwds: Any,
 ) -> Figure: ...
 def parallel_coordinates(
     frame: DataFrame,
@@ -81,7 +81,9 @@ def parallel_coordinates(
     sort_labels: bool = False,
     **kwargs: Any,
 ) -> Axes: ...
-def lag_plot(series: Series, lag: int = 1, ax: Axes | None = None, **kwds) -> Axes: ...
+def lag_plot(
+    series: Series, lag: int = 1, ax: Axes | None = None, **kwds: Any
+) -> Axes: ...
 def autocorrelation_plot(
     series: Series, ax: Axes | None = None, **kwargs: Any
 ) -> Axes: ...

pyproject.toml

@@ -178,7 +178,6 @@ fix = true
 [tool.ruff.lint]
 extend-select = ["ALL"]
 ignore = [
-  # The following rules are ignored permanently for good reasons
   "COM",     # https://docs.astral.sh/ruff/rules/#flake8-commas-com
   "D",       # https://docs.astral.sh/ruff/rules/#pydocstyle-d
   "E501",    # handled by black https://docs.astral.sh/ruff/rules/line-too-long/
@@ -200,14 +199,11 @@ ignore = [
   "PYI001",  # https://docs.astral.sh/ruff/rules/unprefixed-type-param/
   "PYI042",  # https://docs.astral.sh/ruff/rules/snake-case-type-alias/
   "TD003",   # https://docs.astral.sh/ruff/rules/missing-todo-link/
-  "ERA001", "ANN", "PLR0402", "PLC0105"
+  "ERA001", "ANN001", "ANN201", "ANN204", "ANN206", "ANN401", "PLR0402", "PLC0105"
   ]
 "scripts/*" = [
-  # The following rules are ignored permanently for good reasons
   "EM",      # https://docs.astral.sh/ruff/rules/#flake8-errmsg-em
   "S603",    # https://docs.astral.sh/ruff/rules/subprocess-without-shell-equals-true/
-  # The following rules are ignored temporarily. Either fix them or move to the permanent list above.
-  "TRY", "PT", "BLE"
 ]
 "tests/*" = [
   # The following rules are ignored permanently for good reasons
@@ -223,7 +219,7 @@ ignore = [
   "A001",    # https://docs.astral.sh/ruff/rules/builtin-variable-shadowing/
   "PYI042",  # https://docs.astral.sh/ruff/rules/snake-case-type-alias/
   "SLF001",  # https://docs.astral.sh/ruff/rules/private-member-access/
-  "ANN001", "ANN002", "ANN201", "ANN202", "ANN204", "ANN206", "ANN401", "ARG", "ERA", "RUF", "SIM", "TRY", "PT", "NPY", "N", "DTZ", "PLR", "TC", "PGH", "PTH", "S311", "C901"
+  "ANN001", "ANN201", "ANN204", "ANN206", "ANN401", "ARG", "ERA", "RUF", "SIM", "TRY", "PT", "NPY", "N", "DTZ", "PLR", "TC", "PGH", "PTH", "S311", "C901"
 ]
 "tests/test_io.py" = [
   # The following rules are ignored permanently for good reasons

scripts/_job.py

@@ -25,7 +25,7 @@ def __rollback_job(steps: deque[Step]) -> None:
             logger.warning(f"Undoing: {step.name}")
             try:
                 step.rollback()
-            except Exception:
+            except Exception:  # noqa: BLE001
                 logger.error(
                     f"Rollback of Step: '{step.name}' failed! The project could be in a unstable mode."
                 )
@@ -47,7 +47,7 @@ def run_job(steps: list[Step]) -> None:
             rollback_steps.append(step)
             step.run()
 
-        except Exception:
+        except Exception:  # noqa: BLE001
             logger.error(f"Step: '{step.name}' failed!")
             __rollback_job(rollback_steps)
             failed = True

scripts/test/__init__.py

@@ -22,9 +22,9 @@
 
 
 def test(
-    src: bool = False,
-    dist: bool = False,
-    type_checker: Literal["", "mypy", "pyright"] = "",
+    src: bool = False,  # noqa: PT028
+    dist: bool = False,  # noqa: PT028
+    type_checker: Literal["", "mypy", "pyright"] = "",  # noqa: PT028
 ) -> None:
     steps = []
     if src:

scripts/test/run.py

@@ -62,7 +62,9 @@ def rename_src() -> None:
     if Path(r"pandas-stubs").exists():
         Path(r"pandas-stubs").rename("_pandas-stubs")
     else:
-        raise FileNotFoundError("'pandas-stubs' folder does not exists.")
+        raise FileNotFoundError(  # noqa: TRY003
+            "'pandas-stubs' folder does not exists."
+        )
 
 
 def mypy_dist() -> None:
@@ -84,7 +86,9 @@ def restore_src() -> None:
     if Path(r"_pandas-stubs").exists():
         Path(r"_pandas-stubs").rename("pandas-stubs")
     else:
-        raise FileNotFoundError("'_pandas-stubs' folder does not exists.")
+        raise FileNotFoundError(  # noqa: TRY003
+            "'_pandas-stubs' folder does not exists."
+        )
 
 
 def nightly_pandas() -> None:

tests/extension/decimal/array.py

@@ -1,10 +1,14 @@
 from __future__ import annotations
 
 from builtins import type as type_t
+from collections.abc import Callable
 import decimal
 import numbers
 import sys
-from typing import Any
+from typing import (
+    Any,
+    cast,
+)
 
 import numpy as np
 from pandas.api.extensions import (
@@ -125,7 +129,9 @@ def to_numpy(
             result = np.asarray([round(x, decimals) for x in result])
         return result
 
-    def __array_ufunc__(self, ufunc: np.ufunc, method: str, *inputs, **kwargs: Any):
+    def __array_ufunc__(
+        self, ufunc: np.ufunc, method: str, *inputs: Any, **kwargs: Any
+    ):
         #
         if not all(
             isinstance(t, self._HANDLED_TYPES + (DecimalArray,)) for t in inputs
@@ -147,7 +153,7 @@ def __array_ufunc__(self, ufunc: np.ufunc, method: str, *inputs, **kwargs: Any):
             if result is not NotImplemented:
                 return result
 
-        def reconstruct(x):
+        def reconstruct(x) -> decimal.Decimal | numbers.Number | DecimalArray:
             if isinstance(x, (decimal.Decimal, numbers.Number)):
                 return x
             return DecimalArray._from_sequence(x)
@@ -220,10 +226,10 @@ def isna(self):
         return np.array([x.is_nan() for x in self._data], dtype=bool)
 
     @property
-    def _na_value(self):
+    def _na_value(self) -> decimal.Decimal:
         return decimal.Decimal("NaN")
 
-    def _formatter(self, boxed=False):
+    def _formatter(self, boxed=False) -> Callable[..., str]:
         if boxed:
             return "Decimal: {}".format
         return repr
@@ -232,7 +238,7 @@ def _formatter(self, boxed=False):
     def _concat_same_type(cls, to_concat):
         return cls(np.concatenate([x._data for x in to_concat]))
 
-    def _reduce(self, name: str, *, skipna: bool = True, **kwargs: Any):
+    def _reduce(self, name: str, *, skipna: bool = True, **kwargs: Any) -> Any:
         if skipna:
             # If we don't have any NAs, we can ignore skipna
             if self.isna().any():
@@ -251,9 +257,9 @@ def _reduce(self, name: str, *, skipna: bool = True, **kwargs: Any):
             ) from err
         return op(axis=0)
 
-    def _cmp_method(self, other, op):
+    def _cmp_method(self, other, op) -> np.ndarray[tuple[int], np.dtype[np.bool_]]:
         # For use with OpsMixin
-        def convert_values(param):
+        def convert_values(param) -> ExtensionArray | list[Any]:
             if isinstance(param, ExtensionArray) or is_list_like(param):
                 ovalues = param
             else:
@@ -268,7 +274,9 @@ def convert_values(param):
         # a TypeError should be raised
         res = [op(a, b) for (a, b) in zip(lvalues, rvalues)]
 
-        return np.asarray(res, dtype=bool)
+        return cast(
+            np.ndarray[tuple[int], np.dtype[np.bool_]], np.asarray(res, dtype=bool)
+        )
 
     def value_counts(self, dropna: bool = True):
         from pandas.core.algorithms import value_counts