xarray (https://github.com/pydata/xarray)+ xarray/tests/test_parallelcompat.py: note: In member "compute" of class "DummyChunkManager":+ xarray/tests/test_parallelcompat.py:93: error: Return type "tuple[ndarray[tuple[int, ...], dtype[Any]], ...]" of "compute" incompatible with return type "tuple[ndarray[Any, _DType_co], ...]" in supertype "ChunkManagerEntrypoint"  [override]+ xarray/tests/test_parallelcompat.py: note: At top level:dedupe (https://github.com/dedupeio/dedupe)- dedupe/api.py:551: error: Unused "type: ignore" comment  [unused-ignore]optuna (https://github.com/optuna/optuna)+ optuna/_hypervolume/hssp.py:108: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[signedinteger[Any]]]", variable has type "ndarray[tuple[int], dtype[signedinteger[Any]]]")  [assignment]+ optuna/_hypervolume/box_decomposition.py:92: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int, int, int], dtype[Any]]")  [assignment]+ tests/hypervolume_tests/test_wfg.py:26: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int, int], dtype[Any]]")  [assignment]pandas (https://github.com/pandas-dev/pandas)- pandas/core/_numba/executor.py:90: error: Incompatible redefinition (redefinition with type "Callable[[ndarray[Any, Any], ndarray[Any, Any], ndarray[Any, Any], int, VarArg(Any)], Any]", original type "Callable[[ndarray[Any, Any], ndarray[Any, Any], int, int, VarArg(Any)], Any]")  [misc]+ pandas/core/window/numba_.py:238: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int, int], dtype[float64]]")  [assignment]+ pandas/core/_numba/executor.py:90: error: Incompatible redefinition (redefinition with type "Callable[[ndarray[tuple[int, ...], dtype[Any]], ndarray[tuple[int, ...], dtype[Any]], ndarray[tuple[int, ...], dtype[Any]], int, VarArg(Any)], Any]", original type "Callable[[ndarray[tuple[int, ...], dtype[Any]], ndarray[tuple[int, ...], dtype[Any]], int, int, VarArg(Any)], Any]")  [misc]+ pandas/core/util/hashing.py:327: error: Incompatible types in assignment (expression has type "CategoricalDtype", variable has type "dtype[Any]")  [assignment]+ pandas/core/util/hashing.py:328: error: Argument 2 to "_simple_new" of "Categorical" has incompatible type "dtype[Any]"; expected "CategoricalDtype"  [arg-type]+ pandas/core/nanops.py:656: error: Unused "type: ignore" comment  [unused-ignore]+ pandas/core/construction.py:687: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[Any]]")  [assignment]+ pandas/core/construction.py:689: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[Any]]")  [assignment]+ pandas/core/arrays/_utils.py:48: error: Item "dtype[Any]" of "ExtensionDtype | dtype[Any]" has no attribute "na_value"  [union-attr]+ pandas/core/arrays/_utils.py:56: error: Item "dtype[Any]" of "ExtensionDtype | dtype[Any]" has no attribute "na_value"  [union-attr]+ pandas/core/arrays/datetimes.py:816: error: Argument 1 to "view" of "ndarray" has incompatible type "dtype[datetime64[date | int | None]] | DatetimeTZDtype"; expected "dtype[Any] | _HasDType[dtype[Any]]"  [arg-type]+ pandas/core/arrays/_mixins.py:150: error: Argument "dtype" to "view" of "ndarray" has incompatible type "ExtensionDtype | dtype[Any]"; expected "dtype[Any] | _HasDType[dtype[Any]]"  [arg-type]+ pandas/core/arrays/categorical.py:1858: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[signedinteger[Any]]]")  [assignment]+ pandas/io/pytables.py:3306: error: Unused "type: ignore" comment  [unused-ignore]+ pandas/io/pytables.py:3306: error: "ExtensionArray" has no attribute "asi8"  [attr-defined]+ pandas/io/pytables.py:3306: note: Error code "attr-defined" not covered by "type: ignore" comment+ pandas/io/pytables.py:3312: error: Unused "type: ignore" comment  [unused-ignore]+ pandas/io/pytables.py:3312: error: "ExtensionArray" has no attribute "tz"  [attr-defined]+ pandas/io/pytables.py:3312: note: Error code "attr-defined" not covered by "type: ignore" comment+ pandas/io/pytables.py:5196: error: Unused "type: ignore" comment  [unused-ignore]+ pandas/core/frame.py:11368: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[float64]]", variable has type "ndarray[tuple[int, int], dtype[float64]]")  [assignment]+ pandas/core/reshape/merge.py:1737: error: Item "ExtensionArray" of "ExtensionArray | Any" has no attribute "all"  [union-attr]+ pandas/core/reshape/merge.py:1757: error: Item "ExtensionArray" of "ExtensionArray | Any" has no attribute "all"  [union-attr]static-frame (https://github.com/static-frame/static-frame)- static_frame/core/join.py:98: error: Argument 1 to "nonzero_1d" has incompatible type "numpy.bool[builtins.bool] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]"; expected "ndarray[Any, Any]"  [arg-type]+ static_frame/core/join.py:98: error: Argument 1 to "nonzero_1d" has incompatible type "numpy.bool[builtins.bool] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]"; expected "ndarray[tuple[int, ...], dtype[Any]]"  [arg-type]+ static_frame/core/frame.py:7524: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[Any]]")  [assignment]spark (https://github.com/apache/spark)- python/pyspark/pandas/namespace.py:1139: note:     def [IntStrT: (int, str)] read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: list[IntStrT], *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[Any, Any] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> dict[IntStrT, DataFrame]+ python/pyspark/pandas/namespace.py:1139: note:     def [IntStrT: (int, str)] read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: list[IntStrT], *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[tuple[int, ...], dtype[Any]] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> dict[IntStrT, DataFrame]- python/pyspark/pandas/namespace.py:1139: note:     def read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: None, *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[Any, Any] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> dict[str, DataFrame]+ python/pyspark/pandas/namespace.py:1139: note:     def read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: None, *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[tuple[int, ...], dtype[Any]] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> dict[str, DataFrame]- python/pyspark/pandas/namespace.py:1139: note:     def read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: list[int | str], *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[Any, Any] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> dict[int | str, DataFrame]+ python/pyspark/pandas/namespace.py:1139: note:     def read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: list[int | str], *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[tuple[int, ...], dtype[Any]] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> dict[int | str, DataFrame]- python/pyspark/pandas/namespace.py:1139: note:     def read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: int | str = ..., *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[Any, Any] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> DataFrame+ python/pyspark/pandas/namespace.py:1139: note:     def read_excel(io: str | PathLike[str] | ReadBuffer[bytes] | ExcelFile | Any | Any | Any | Any, sheet_name: int | str = ..., *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[tuple[int, ...], dtype[Any]] | tuple[Any, ...] | range | None = ..., index_col: int | Sequence[int] | str | None = ..., usecols: str | SequenceNotStr[Hashable] | range | ExtensionArray | ndarray[Any, Any] | Index[Any] | Series[Any] | Callable[[Any], bool] | None = ..., dtype: str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object] | Mapping[str, str | ExtensionDtype | str | dtype[generic[Any]] | type[str] | type[complex] | type[bool] | type[object]] | None = ..., engine: Literal['xlrd', 'openpyxl', 'odf', 'pyxlsb', 'calamine'] | None = ..., converters: Mapping[int | str, Callable[[object], object]] | None = ..., true_values: Iterable[Hashable] | None = ..., false_values: Iterable[Hashable] | None = ..., skiprows: int | Sequence[int] | Callable[[object], bool] | None = ..., nrows: int | None = ..., na_values: Sequence[str] | dict[str | int, Sequence[str]] = ..., keep_default_na: bool = ..., na_filter: bool = ..., verbose: bool = ..., parse_dates: bool | Sequence[int] | Sequence[Sequence[str] | Sequence[int]] | dict[str, Sequence[int] | list[str]] = ..., date_format: dict[Hashable, str] | str | None = ..., thousands: str | None = ..., decimal: str = ..., comment: str | None = ..., skipfooter: int = ..., storage_options: dict[str, Any] | None = ..., dtype_backend: Literal['pyarrow', 'numpy_nullable'] | Literal[_NoDefault.no_default] = ...) -> DataFrame+ python/pyspark/ml/linalg/__init__.py:1145: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[Any]]")  [assignment]+ python/pyspark/mllib/linalg/__init__.py:1327: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[Any]]")  [assignment]scikit-learn (https://github.com/scikit-learn/scikit-learn)+ sklearn/model_selection/tests/test_search.py:2894: error: Unused "type: ignore" comment  [unused-ignore]pandera (https://github.com/pandera-dev/pandera)- pandera/strategies/pandas_strategies.py:71: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[Any, Any] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[True], axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> None+ pandera/strategies/pandas_strategies.py:71: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[tuple[int, ...], dtype[Any]] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[True], axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> None- pandera/strategies/pandas_strategies.py:71: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[Any, Any] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[False] = ..., axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> Series[Any]+ pandera/strategies/pandas_strategies.py:71: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[tuple[int, ...], dtype[Any]] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[False] = ..., axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> Series[Any]- pandera/strategies/pandas_strategies.py:73: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[Any, Any] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[True], axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> None+ pandera/strategies/pandas_strategies.py:73: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[tuple[int, ...], dtype[Any]] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[True], axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> None- pandera/strategies/pandas_strategies.py:73: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[Any, Any] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[False] = ..., axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> Series[Any]+ pandera/strategies/pandas_strategies.py:73: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[tuple[int, ...], dtype[Any]] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[False] = ..., axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> Series[Any]- pandera/strategies/pandas_strategies.py:74: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[Any, Any] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[True], axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> None+ pandera/strategies/pandas_strategies.py:74: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[tuple[int, ...], dtype[Any]] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[True], axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> None- pandera/strategies/pandas_strategies.py:74: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[Any, Any] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[False] = ..., axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> Series[Any]+ pandera/strategies/pandas_strategies.py:74: note:     def mask(self, cond: Series[Any] | Series[bool] | ndarray[tuple[int, ...], dtype[Any]] | Callable[[Series[Any]], Series[bool]] | Callable[[Any], bool], other: str | bytes | date | datetime | timedelta | <12 more items> | None = ..., *, inplace: Literal[False] = ..., axis: Literal['index', 0] | None = ..., level: Hashable | int | None = ...) -> Series[Any]arviz (https://github.com/arviz-devs/arviz)- arviz/stats/ecdf_utils.py:83: error: Incompatible return value type (got "tuple[float | ndarray[tuple[int, ...], dtype[float64]], float | ndarray[tuple[int, ...], dtype[float64]]]", expected "tuple[ndarray[Any, Any], ndarray[Any, Any]]")  [return-value]+ arviz/stats/ecdf_utils.py:83: error: Incompatible return value type (got "tuple[float | ndarray[tuple[int, ...], dtype[float64]], float | ndarray[tuple[int, ...], dtype[float64]]]", expected "tuple[ndarray[tuple[int, ...], dtype[Any]], ndarray[tuple[int, ...], dtype[Any]]]")  [return-value]