fix: apply suggestions from pre-commit hooks

[jwilliams-ocient]

SUMMARY

BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF

(.venv) jwilliams@jwilliams-dev0:/ocient/db/superset (master)$ tox -e pre-commit
pre-commit installed: apache-superset==0.0.0.dev0,backports.entry-points-selectable==1.1.0,build==0.8.0,cfgv==3.3.0,click==8.0.4,distlib==0.3.2,filelock==3.0.12,identify==2.2.13,nodeenv==1.6.0,packaging==21.3,pep517==0.11.0,pip-compile-multi==2.6.1,pip-tools==6.8.0,platformdirs==2.2.0,pluggy==0.13.1,pre-commit==2.14.0,py==1.10.0,pyparsing==3.0.6,PyYAML==5.4.1,six==1.16.0,toml==0.10.2,tomli==1.2.1,toposort==1.6,tox==3.25.1,virtualenv==20.7.2
pre-commit run-test-pre: PYTHONHASHSEED='1889047509'
pre-commit run-test: commands[0] | pre-commit run --all-files
isort....................................................................Passed
mypy.....................................................................Failed
- hook id: mypy
- exit code: 1

superset/utils/pandas_postprocessing/utils.py:176: error: Argument 1 to "partial" has incompatible type "object"; expected "Callable[..., Any]"
superset/utils/pandas_postprocessing/flatten.py:88: error: Call to untyped function "is_sequence" in typed context
superset/utils/pandas_postprocessing/boxplot.py:60: error: No overload variant matches argument types "Any", "int", "str"
superset/utils/pandas_postprocessing/boxplot.py:60: note: Possible overload variants:
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> floating[Any]
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> complexfloating[Any, Any]
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> timedelta64
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[datetime64]], _NestedSequence[_SupportsArray[dtype[datetime64]]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> datetime64
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> Any
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[floating[Any]]]
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[complexfloating[Any, Any]]]
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[timedelta64]]
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[datetime64]], _NestedSequence[_SupportsArray[dtype[datetime64]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[datetime64]]
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[object_]]
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def (a: Union[Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: Optional[Union[SupportsIndex, Sequence[SupportsIndex]]] = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: bool = ...) -> Any
superset/utils/pandas_postprocessing/boxplot.py:60: note:     def [_ArrayType <: ndarray[Any, dtype[Any]]] (a: Union[Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: Optional[Union[SupportsIndex, Sequence[SupportsIndex]]] = ..., out: _ArrayType = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: bool = ...) -> _ArrayType
superset/utils/pandas_postprocessing/boxplot.py:63: error: No overload variant matches argument types "Any", "int", "str"
superset/utils/pandas_postprocessing/boxplot.py:63: note: Possible overload variants:
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> floating[Any]
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> complexfloating[Any, Any]
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> timedelta64
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[datetime64]], _NestedSequence[_SupportsArray[dtype[datetime64]]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> datetime64
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]], q: Union[Union[Union[bool, bool_], int, integer[Any]], float, floating[Any]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> Any
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[floating[Any]]]
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[complexfloating[Any, Any]]]
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[timedelta64]]
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[datetime64]], _NestedSequence[_SupportsArray[dtype[datetime64]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[datetime64]]
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: None = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: Literal[False] = ...) -> ndarray[Any, dtype[object_]]
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def (a: Union[Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: Optional[Union[SupportsIndex, Sequence[SupportsIndex]]] = ..., out: None = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: bool = ...) -> Any
superset/utils/pandas_postprocessing/boxplot.py:63: note:     def [_ArrayType <: ndarray[Any, dtype[Any]]] (a: Union[Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any], complexfloating[Any, Any]]]]], bool, int, float, complex, _NestedSequence[Union[bool, int, float, complex]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], timedelta64]]]], bool, int, _NestedSequence[Union[bool, int]]], Union[_SupportsArray[dtype[object_]], _NestedSequence[_SupportsArray[dtype[object_]]]]], q: Union[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]], _NestedSequence[_SupportsArray[dtype[Union[bool_, integer[Any], floating[Any]]]]], bool, int, float, _NestedSequence[Union[bool, int, float]]], axis: Optional[Union[SupportsIndex, Sequence[SupportsIndex]]] = ..., out: _ArrayType = ..., overwrite_input: bool = ..., method: Literal['inverted_cdf', 'averaged_inverted_cdf', 'closest_observation', 'interpolated_inverted_cdf', 'hazen', 'weibull', 'linear', 'median_unbiased', 'normal_unbiased', 'lower', 'higher', 'midpoint', 'nearest'] = ..., keepdims: bool = ...) -> _ArrayType
superset/utils/pandas_postprocessing/boxplot.py:102: error: Incompatible types in assignment (expression has type overloaded function, variable has type "Callable[[Any], float]")
superset/utils/pandas_postprocessing/boxplot.py:103: error: Incompatible types in assignment (expression has type overloaded function, variable has type "Callable[[Any], float]")
superset/utils/pandas_postprocessing/boxplot.py:129: error: Module has no attribute "object"; maybe "object_"?
superset/result_set.py:65: error: Missing type parameters for generic type "ndarray"
superset/result_set.py:68: error: List item 0 has incompatible type "str"; expected "Sequence[Literal['aligned', 'allocate', 'arraymask', 'copy', 'config', 'nbo', 'no_subtype', 'no_broadcast', 'overlap_assume_elementwise', 'readonly', 'readwrite', 'updateifcopy', 'virtual', 'writeonly', 'writemasked']]"
superset/result_set.py:72: error: Unsupported target for indexed assignment ("Tuple[ndarray[Any, dtype[Any]], ...]")
superset/result_set.py:74: error: Unsupported target for indexed assignment ("Tuple[ndarray[Any, dtype[Any]], ...]")
superset/result_set.py:109: error: Missing type parameters for generic type "ndarray"
superset/result_set.py:159: error: Argument 1 to "first_nonempty" of "SupersetResultSet" has incompatible type "ndarray[Any, dtype[Any]]"; expected "List[Any]"
superset/reports/commands/alert.py:87: error: Missing type parameters for generic type "recarray"
superset/reports/commands/alert.py:92: error: Missing type parameters for generic type "recarray"
superset/reports/commands/alert.py:111: error: Missing type parameters for generic type "recarray"
superset/db_engine_specs/hive.py:209: error: Missing type parameters for generic type "dtype"
Found 17 errors in 6 files (checked 1223 source files)

pip-compile-multi verify.................................................Passed
Check docstring is first.................................................Passed
Check for added large files..............................................Passed
Check Yaml...............................................................Passed
Debug Statements (Python)................................................Passed
Fix End of Files.........................................................Passed
Trim Trailing Whitespace.................................................Passed
black....................................................................Passed
Blacklist................................................................Passed

TESTING INSTRUCTIONS

ADDITIONAL INFORMATION

• Has associated issue:
• Required feature flags:
• Changes UI
• Includes DB Migration (follow approval process in SIP-59)
  • Migration is atomic, supports rollback & is backwards-compatible
  • Confirm DB migration upgrade and downgrade tested
  • Runtime estimates and downtime expectations provided
• Introduces new feature or API
• Removes existing feature or API

additional commits