Use checkmember.py to check method override

[ilevkivskyi]

This is a second "large" PR towards #7724. Here I actually expect a smaller fallout than for variables, since methods are usually less tricky, but let's see.

[ilevkivskyi]

OK, so essentially as I predicted. We have a small bunch of improvements, but also we have some potential fasle positives in scipy-stubs (they look big, but it is only because we format a lot of overloads). I actually expected this problem: "restricted" self-types are really tricky even to reason about in terms of overrides, not to say about implementation. I am not sure what to do with this, maybe we can just live with this, and instruct people to use type ignores.

[ilevkivskyi]

Hm, actually at least some of the errors in scipy-stubs may be "real". It looks like few of those I checked may be because mypy considers tuple[int, ...] not a subtype of tuple[int, *tuple[int, ...]].

[ilevkivskyi]

Anyway, I spent some time thinking about this, and scipy-stubs stuff is way too tricky. Maybe we can special-case it somehow later. @JukkaL if don't have objections, I would propose to go ahead.

[JukkaL]

I agree that we can move forward.

[github-actions]

Diff from mypy_primer, showing the effect of this PR on open source code:

mkdocs (https://github.com/mkdocs/mkdocs)
+ mkdocs/structure/pages.py:228: error: Unused "type: ignore" comment  [unused-ignore]

scipy-stubs (https://github.com/scipy/scipy-stubs)
+ scipy-stubs/stats/_probability_distribution.pyi:248: error: Signature of "moment" incompatible with supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:      Superclass:
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool], kind: Literal['raw'], *, method: Literal['formula', 'transform', 'quadrature', 'cache'] | None) -> float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool], kind: Literal['central'], *, method: Literal['formula', 'transform', 'quadrature', 'cache', 'normalize'] | None) -> float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool], kind: Literal['standardized'], *, method: Literal['formula', 'transform', 'general', 'cache', 'normalize'] | None) -> float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:      Subclass:
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool] = ..., kind: Literal['raw'] = ..., *, method: Literal['formula', 'transform', 'quadrature', 'cache'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool], kind: Literal['central'], *, method: Literal['formula', 'transform', 'quadrature', 'cache', 'normalize'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool] = ..., *, kind: Literal['central'], method: Literal['formula', 'transform', 'quadrature', 'cache', 'normalize'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool], kind: Literal['standardized'], *, method: Literal['formula', 'transform', 'general', 'cache', 'normalize'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          @overload
+ scipy-stubs/stats/_probability_distribution.pyi:248: note:          def moment(self, order: int | integer[Any] | numpy.bool[builtins.bool] = ..., *, kind: Literal['standardized'], method: Literal['formula', 'transform', 'general', 'cache', 'normalize'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:305: error: Return type "ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" of "entropy" incompatible with return type "float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" in supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:311: error: Return type "ndarray[_ShapeT0_co, dtype[complex128 | complexfloating[_64Bit | _96Bit | _128Bit, _64Bit | _96Bit | _128Bit]]]" of "logentropy" incompatible with return type "complex128 | complexfloating[_64Bit | _96Bit | _128Bit, _64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[complex128 | complexfloating[_64Bit | _96Bit | _128Bit, _64Bit | _96Bit | _128Bit]]]" in supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:319: error: Argument 1 of "pdf" is incompatible with supertype "_ProbabilityDistribution"; supertype defines the argument type as "float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:319: note: This violates the Liskov substitution principle
+ scipy-stubs/stats/_probability_distribution.pyi:319: note: See https://mypy.readthedocs.io/en/stable/common_issues.html#incompatible-overrides
+ scipy-stubs/stats/_probability_distribution.pyi:319: error: Return type "ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" of "pdf" incompatible with return type "float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" in supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:355: error: Argument 1 of "logpdf" is incompatible with supertype "_ProbabilityDistribution"; supertype defines the argument type as "float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:355: note: This violates the Liskov substitution principle
+ scipy-stubs/stats/_probability_distribution.pyi:355: note: See https://mypy.readthedocs.io/en/stable/common_issues.html#incompatible-overrides
+ scipy-stubs/stats/_probability_distribution.pyi:355: error: Return type "ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" of "logpdf" incompatible with return type "float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" in supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:392: error: Signature of "cdf" incompatible with supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:392: note:      Superclass:
+ scipy-stubs/stats/_probability_distribution.pyi:392: note:          def cdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None, /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'subtraction'] | None) -> float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:392: note:      Subclass:
+ scipy-stubs/stats/_probability_distribution.pyi:392: note:          def cdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'subtraction'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:540: error: Signature of "logcdf" incompatible with supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:540: note:      Superclass:
+ scipy-stubs/stats/_probability_distribution.pyi:540: note:          def logcdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None, /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'subtraction'] | None) -> float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:540: note:      Subclass:
+ scipy-stubs/stats/_probability_distribution.pyi:540: note:          def logcdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'subtraction'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:688: error: Signature of "ccdf" incompatible with supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:688: note:      Superclass:
+ scipy-stubs/stats/_probability_distribution.pyi:688: note:          def ccdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None, /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'addition'] | None) -> float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:688: note:      Subclass:
+ scipy-stubs/stats/_probability_distribution.pyi:688: note:          def ccdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'addition'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:836: error: Signature of "logccdf" incompatible with supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:836: note:      Superclass:
+ scipy-stubs/stats/_probability_distribution.pyi:836: note:          def logccdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None, /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'addition'] | None) -> float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:836: note:      Subclass:
+ scipy-stubs/stats/_probability_distribution.pyi:836: note:          def logccdf(self, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., /, *, method: Literal['formula', 'logexp', 'complement', 'quadrature', 'addition'] | None = ...) -> ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]
+ scipy-stubs/stats/_probability_distribution.pyi:984: error: Argument 1 of "icdf" is incompatible with supertype "_ProbabilityDistribution"; supertype defines the argument type as "float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:984: note: This violates the Liskov substitution principle
+ scipy-stubs/stats/_probability_distribution.pyi:984: note: See https://mypy.readthedocs.io/en/stable/common_issues.html#incompatible-overrides
+ scipy-stubs/stats/_probability_distribution.pyi:984: error: Return type "ndarray[_ShapeT0_co, dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" of "icdf" incompatible with return type "float64 | floating[_64Bit | _96Bit | _128Bit] | ndarray[tuple[int, *tuple[int, ...]], dtype[float64 | floating[_64Bit | _96Bit | _128Bit]]]" in supertype "_ProbabilityDistribution"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:1019: error: Argument 1 of "ilogcdf" is incompatible with supertype "_ProbabilityDistribution"; supertype defines the argument type as "float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | SequenceND[CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool], tuple[int, ...]] | float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | CanArray0D[floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]"  [override]
+ scipy-stubs/stats/_probability_distribution.pyi:1019: note: This violates the Liskov substitution principle
+ scipy-stubs/stats/_probability_distribution.pyi:1019: note: See https://mypy.readthedocs.io/en/stable/common_issues.html#incompatible-overrides

... (truncated 9 lines) ...

prefect (https://github.com/PrefectHQ/prefect)
- src/prefect/task_runners.py:244: note:          def [P`-1, R] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectConcurrentFuture[R]
+ src/prefect/task_runners.py:244: note:          def [P`6954, R] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectConcurrentFuture[R]
- src/prefect/task_runners.py:244: note:          def [P`-1] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectConcurrentFuture[R]
+ src/prefect/task_runners.py:244: note:          def [P`6953] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectConcurrentFuture[R]
- src/prefect/task_runners.py:329: note:          def [P`-1, R] map(self, task: Task[P, R], parameters: dict[str, Union[Any, unmapped, allow_failure]], wait_for: Optional[Iterable[PrefectFuture[R]]] = ...) -> PrefectFutureList[PrefectConcurrentFuture[R]]
+ src/prefect/task_runners.py:329: note:          def [P`6962, R] map(self, task: Task[P, R], parameters: dict[str, Union[Any, unmapped, allow_failure]], wait_for: Optional[Iterable[PrefectFuture[R]]] = ...) -> PrefectFutureList[PrefectConcurrentFuture[R]]
- src/prefect/task_runners.py:329: note:          def [P`-1] map(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ...) -> PrefectFutureList[PrefectConcurrentFuture[R]]
+ src/prefect/task_runners.py:329: note:          def [P`6961] map(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ...) -> PrefectFutureList[PrefectConcurrentFuture[R]]
- src/prefect/task_runners.py:391: note:          def [P`-1, R] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectDistributedFuture[R]
+ src/prefect/task_runners.py:391: note:          def [P`6974, R] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectDistributedFuture[R]
- src/prefect/task_runners.py:391: note:          def [P`-1] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectDistributedFuture[R]
+ src/prefect/task_runners.py:391: note:          def [P`6973] submit(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ..., dependencies: Optional[dict[str, set[TaskRunInput]]] = ...) -> PrefectDistributedFuture[R]
- src/prefect/task_runners.py:446: note:          def [P`-1, R] map(self, task: Task[P, R], parameters: dict[str, Union[Any, unmapped, allow_failure]], wait_for: Optional[Iterable[PrefectFuture[R]]] = ...) -> PrefectFutureList[PrefectDistributedFuture[R]]
+ src/prefect/task_runners.py:446: note:          def [P`6982, R] map(self, task: Task[P, R], parameters: dict[str, Union[Any, unmapped, allow_failure]], wait_for: Optional[Iterable[PrefectFuture[R]]] = ...) -> PrefectFutureList[PrefectDistributedFuture[R]]
- src/prefect/task_runners.py:446: note:          def [P`-1] map(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ...) -> PrefectFutureList[PrefectDistributedFuture[R]]
+ src/prefect/task_runners.py:446: note:          def [P`6981] map(self, task: Task[P, Coroutine[Any, Any, R]], parameters: dict[str, Any], wait_for: Optional[Iterable[PrefectFuture[Any]]] = ...) -> PrefectFutureList[PrefectDistributedFuture[R]]

pandas (https://github.com/pandas-dev/pandas)
+ pandas/core/arrays/boolean.py:372: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/series.py:4818: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/indexes/range.py:1382: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/indexes/multi.py:1802: error: Unused "type: ignore" comment  [unused-ignore]

steam.py (https://github.com/Gobot1234/steam.py)
- steam/ext/csgo/client.py:52: note:          cached_property[Client, steam._gc.client.ClientUser]
+ steam/ext/csgo/client.py:52: note:          steam._gc.client.ClientUser
- steam/ext/csgo/client.py:52: note:          cached_property[Client, steam.ext.csgo.models.ClientUser]
- steam/ext/csgo/client.py:52: note:      Superclass:
- steam/ext/csgo/client.py:52: note:          steam.user.ClientUser
+ steam/ext/csgo/client.py:52: note:          steam.ext.csgo.models.ClientUser
- steam/ext/csgo/client.py:52: note:      Subclass:
- steam/ext/csgo/client.py:52: note:          cached_property[Client, steam.ext.csgo.models.ClientUser]
- steam/ext/tf2/client.py:52: note:          cached_property[Client, steam._gc.client.ClientUser]
+ steam/ext/tf2/client.py:52: note:          steam._gc.client.ClientUser
- steam/ext/tf2/client.py:52: note:          cached_property[Client, steam.ext.tf2.client.ClientUser]
- steam/ext/tf2/client.py:52: note:      Superclass:
- steam/ext/tf2/client.py:52: note:          steam.user.ClientUser
+ steam/ext/tf2/client.py:52: note:          steam.ext.tf2.client.ClientUser
- steam/ext/tf2/client.py:52: note:      Subclass:
- steam/ext/tf2/client.py:52: note:          cached_property[Client, steam.ext.tf2.client.ClientUser]

xarray (https://github.com/pydata/xarray)
- xarray/core/variable.py:420: note:  override has type "T_DuckArray | Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]")
+ xarray/core/variable.py:420: note:  override has type "T_DuckArray | Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | int | float | complex | str | _NestedSequence[bool | int | float | complex | str | bytes]")

sympy (https://github.com/sympy/sympy)
+ sympy/functions/elementary/piecewise.py:813: error: "Expr" has no attribute "_eval_template_is_attr"  [attr-defined]
+ sympy/functions/elementary/piecewise.py:815: error: "Expr" has no attribute "_eval_template_is_attr"  [attr-defined]
+ sympy/printing/codeprinter.py:488: error: Incompatible types in assignment (expression has type "None", base class "StrPrinter" defined the type as "Callable[[Any], Any]")  [assignment]

setuptools (https://github.com/pypa/setuptools)
+ pkg_resources/__init__.py:1988: error: Unused "type: ignore" comment  [unused-ignore]

CPython (cases_generator) (https://github.com/python/cpython)
+ Tools/cases_generator/tier2_generator.py:94: error: Unused "type: ignore" comment  [unused-ignore]

tornado (https://github.com/tornadoweb/tornado)
- tornado/test/ioloop_test.py:558: note:          def [_P`-1, _T] submit(self, Callable[_P, _T], /, *args: _P.args, **kwargs: _P.kwargs) -> Future[_T]
+ tornado/test/ioloop_test.py:558: note:          def [_P`5166, _T] submit(self, Callable[_P, _T], /, *args: _P.args, **kwargs: _P.kwargs) -> Future[_T]

cki-lib (https://gitlab.com/cki-project/cki-lib)
- cki_lib/krb_ticket_refresher.py:26: error: Call to untyped function "_close_to_expire_ticket" of "RefreshKerberosTicket" in typed context  [no-untyped-call]

ibis (https://github.com/ibis-project/ibis)
- ibis/common/grounds.py:117: error: Signature of "__create__" incompatible with supertype "Abstract"  [override]
- ibis/common/grounds.py:117: note:      Superclass:
- ibis/common/grounds.py:117: note:          classmethod[Any, [VarArg(Any), KwArg(Any)], Any]
- ibis/common/grounds.py:117: note:      Subclass:
- ibis/common/grounds.py:117: note:          @classmethod
- ibis/common/grounds.py:117: note:          def __create__(cls, *args: Any, **kwargs: Any) -> Annotable

spack (https://github.com/spack/spack)
+ lib/spack/spack/build_systems/python.py:355: error: Unused "type: ignore" comment  [unused-ignore]
+ lib/spack/spack/build_systems/python.py:368: error: Unused "type: ignore" comment  [unused-ignore]