TYP: Gradual shape type defaults by jorenham · Pull Request #28982 · numpy/numpy

jorenham · 2025-05-16T06:50:43Z

The type tuple[Any, ...] is special in that it is consistent with all tuple types, and assignable to a tuple of any length. This is useful for gradual typing.

So by using tuple[Any, ...] instead of tuple[int, ...] as shape-type default, we prevent situations where users are not allowed to assign an array with unknown shape-type to an array-type with a known shape type.

The downside is that there are certain situations where (mostly) mypy will over-eagerly pick the first overload, where it would previously pick a different one. But I only saw this happen once in the tests, and managed to work around it.

Let's see what mypy_primer has to say about this.

jorenham · 2025-05-16T07:41:16Z

mypy primer is looking pretty good in general

github-actions · 2025-05-16T17:10:24Z

Diff from mypy_primer, showing the effect of this PR on type check results on a corpus of open source code:

hydpy (https://github.com/hydpy-dev/hydpy)
- hydpy/core/testtools.py:1516: error: Incompatible return value type (got "dict[ModelSequence, ndarray[tuple[int, int], dtype[float64]]]", expected "dict[ModelSequence, ndarray[tuple[int, ...], dtype[float64]]]")  [return-value]
- hydpy/core/testtools.py:1516: note: "Dict" is invariant -- see https://mypy.readthedocs.io/en/stable/common_issues.html#variance
- hydpy/core/testtools.py:1516: note: Consider using "Mapping" instead, which is covariant in the value type
- hydpy/core/testtools.py:1516: note: Perhaps you need a type annotation for "yvalues"? Suggestion: "dict[ModelSequence, ndarray[tuple[int, ...], dtype[float64]]]"
+ hydpy/core/objecttools.py:955: error: Argument 1 to "repr_values" has incompatible type "Sequence[object] | ndarray[tuple[Any, ...], dtype[generic[Any]]] | generic[Any]"; expected "Sequence[object] | ndarray[tuple[Any, ...], dtype[generic[Any]]]"  [arg-type]
+ hydpy/core/netcdftools.py:489: error: Argument 1 to "join" of "bytes" has incompatible type "bytes_"; expected "Iterable[Buffer]"  [arg-type]
+ hydpy/core/netcdftools.py:489: note: Following member(s) of "bytes_" have conflicts:
+ hydpy/core/netcdftools.py:489: note:     Expected:
+ hydpy/core/netcdftools.py:489: note:         def __iter__(self) -> Iterator[Buffer]
+ hydpy/core/netcdftools.py:489: note:     Got:
+ hydpy/core/netcdftools.py:489: note:         def __iter__(self) -> Iterator[int]
+ hydpy/core/netcdftools.py:489: note:     Expected:
+ hydpy/core/netcdftools.py:489: note:         def __iter__(self) -> Iterator[Buffer]
+ hydpy/core/netcdftools.py:489: note:     Got:
+ hydpy/core/netcdftools.py:489: note:         def __iter__(self) -> Iterator[int]
+ hydpy/core/netcdftools.py:489: note:     Expected:
+ hydpy/core/netcdftools.py:489: note:         def __iter__(self) -> Iterator[Buffer]
+ hydpy/core/netcdftools.py:489: note:     Got:
+ hydpy/core/netcdftools.py:489: note:         def __iter__(self) -> Iterator[int]
- hydpy/core/itemtools.py:951: error: Argument 2 to "update_variable" of "ChangeItem" has incompatible type "float64"; expected "ndarray[tuple[int, ...], dtype[float64]]"  [arg-type]
+ hydpy/core/itemtools.py:951: error: Argument 2 to "update_variable" of "ChangeItem" has incompatible type "float64"; expected "ndarray[tuple[Any, ...], dtype[float64]]"  [arg-type]
- hydpy/core/itemtools.py:954: error: Argument 2 to "update_variable" of "ChangeItem" has incompatible type "float64"; expected "ndarray[tuple[int, ...], dtype[float64]]"  [arg-type]
+ hydpy/core/itemtools.py:954: error: Argument 2 to "update_variable" of "ChangeItem" has incompatible type "float64"; expected "ndarray[tuple[Any, ...], dtype[float64]]"  [arg-type]
- hydpy/auxs/statstools.py:298: error: Argument "sim" to "SimObs" has incompatible type "Series[Any]"; expected "ndarray[tuple[int, ...], dtype[float64]]"  [arg-type]
+ hydpy/auxs/statstools.py:298: error: Argument "sim" to "SimObs" has incompatible type "Series[Any]"; expected "ndarray[tuple[Any, ...], dtype[float64]]"  [arg-type]
- hydpy/auxs/statstools.py:298: error: Argument "obs" to "SimObs" has incompatible type "Series[Any]"; expected "ndarray[tuple[int, ...], dtype[float64]]"  [arg-type]
+ hydpy/auxs/statstools.py:298: error: Argument "obs" to "SimObs" has incompatible type "Series[Any]"; expected "ndarray[tuple[Any, ...], dtype[float64]]"  [arg-type]
- hydpy/auxs/ppolytools.py:256: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, signedinteger[_64Bit]], dtype[float64]]", variable has type "Sequence[Sequence[float] | ndarray[tuple[int, ...], dtype[float64]]] | ndarray[tuple[int, ...], dtype[float64]]")  [assignment]
- hydpy/auxs/ppolytools.py:423: error: No overload variant of "CubicHermiteSpline" matches argument types "ndarray[tuple[int, ...], dtype[float64]]", "ndarray[tuple[int, ...], dtype[float64]]"  [call-overload]
+ hydpy/auxs/ppolytools.py:423: error: No overload variant of "CubicHermiteSpline" matches argument types "ndarray[tuple[Any, ...], dtype[float64]]", "ndarray[tuple[Any, ...], dtype[float64]]"  [call-overload]
- hydpy/auxs/ppolytools.py:427: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[signedinteger[_64Bit]]]", variable has type "ndarray[tuple[int], dtype[signedinteger[_64Bit]]]")  [assignment]
- hydpy/auxs/armatools.py:258: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[float64]]")  [assignment]
- hydpy/models/rconc/rconc_control.py:422: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], Any]", variable has type "ndarray[tuple[int], dtype[floating[Any]]]")  [assignment]

freqtrade (https://github.com/freqtrade/freqtrade)
- freqtrade/data/metrics.py:122: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "Series[builtins.bool] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | str | str_ | <9 more items>"  [index]
+ freqtrade/data/metrics.py:122: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "Series[builtins.bool] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | str | str_ | <9 more items>"  [index]
- freqtrade/data/entryexitanalysis.py:59: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "Series[builtins.bool] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | str | str_ | <9 more items>"  [index]
+ freqtrade/data/entryexitanalysis.py:59: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "Series[builtins.bool] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | str | str_ | <9 more items>"  [index]
- freqtrade/data/entryexitanalysis.py:60: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "Series[builtins.bool] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | str | str_ | <9 more items>"  [index]
+ freqtrade/data/entryexitanalysis.py:60: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "Series[builtins.bool] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | str | str_ | <9 more items>"  [index]
- freqtrade/data/entryexitanalysis.py:60: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | <6 more items>"  [index]
+ freqtrade/data/entryexitanalysis.py:60: error: Invalid index type "tuple[Hashable, str]" for "_LocIndexerFrame[DataFrame]"; expected type "slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | <6 more items>"  [index]
- freqtrade/plot/plotting.py:187: error: Invalid index type "tuple[datetime, str]" for "_LocIndexerFrame[DataFrame]"; expected type "slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | <6 more items>"  [index]
+ freqtrade/plot/plotting.py:187: error: Invalid index type "tuple[datetime, str]" for "_LocIndexerFrame[DataFrame]"; expected type "slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | <6 more items>"  [index]
- freqtrade/plot/plotting.py:188: error: Invalid index type "tuple[datetime, str]" for "_LocIndexerFrame[DataFrame]"; expected type "slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | <6 more items>"  [index]
+ freqtrade/plot/plotting.py:188: error: Invalid index type "tuple[datetime, str]" for "_LocIndexerFrame[DataFrame]"; expected type "slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | <6 more items>"  [index]
- freqtrade/freqai/data_drawer.py:363: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
+ freqtrade/freqai/data_drawer.py:363: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
- freqtrade/freqai/data_drawer.py:363: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "tuple[int, int]"  [index]
+ freqtrade/freqai/data_drawer.py:363: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "tuple[int, int]"  [index]
- freqtrade/freqai/data_drawer.py:368: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
+ freqtrade/freqai/data_drawer.py:368: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
- freqtrade/freqai/data_drawer.py:369: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
+ freqtrade/freqai/data_drawer.py:369: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
- freqtrade/freqai/data_drawer.py:373: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
+ freqtrade/freqai/data_drawer.py:373: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
- freqtrade/freqai/data_drawer.py:376: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
+ freqtrade/freqai/data_drawer.py:376: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
- freqtrade/freqai/data_drawer.py:383: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
+ freqtrade/freqai/data_drawer.py:383: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
- freqtrade/freqai/data_drawer.py:387: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
+ freqtrade/freqai/data_drawer.py:387: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int] | tuple[int, int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], int] | tuple[slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int], slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]] | tuple[int, slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[integer[Any]]] | Index[Any] | list[int] | Series[int]]"  [index]
- freqtrade/freqai/data_drawer.py:387: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "tuple[int, int]"  [index]
+ freqtrade/freqai/data_drawer.py:387: error: Invalid index type "tuple[int, int | slice[Any, Any, Any] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]]" for "_iLocIndexerFrame[DataFrame]"; expected type "tuple[int, int]"  [index]

... (truncated 28 lines) ...

AutoSplit (https://github.com/Toufool/AutoSplit)
- src/capture_method/XcbCaptureMethod.py:58:17: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "Image")  [assignment]
+ src/capture_method/XcbCaptureMethod.py:58:17: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[Any]]", variable has type "Image")  [assignment]
- src/capture_method/ScrotCaptureMethod.py:48:17: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "Image")  [assignment]
+ src/capture_method/ScrotCaptureMethod.py:48:17: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[Any]]", variable has type "Image")  [assignment]

xarray (https://github.com/pydata/xarray)
- xarray/core/indexing.py:1152: error: Argument 1 to "append" of "list" has incompatible type "ndarray[tuple[int, ...], dtype[Any]]"; expected "slice[Any, Any, Any]"  [arg-type]
+ xarray/core/indexing.py:1152: error: Argument 1 to "append" of "list" has incompatible type "ndarray[tuple[Any, ...], dtype[Any]]"; expected "slice[Any, Any, Any]"  [arg-type]
- 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:93: error: Return type "tuple[ndarray[tuple[Any, ...], dtype[Any]], ...]" of "compute" incompatible with return type "tuple[ndarray[Any, _DType_co], ...]" in supertype "ChunkManagerEntrypoint"  [override]
- xarray/tests/test_dataarray.py:3810: error: Argument 1 to "len" has incompatible type "ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]] | numpy.bool[builtins.bool]"; expected "Sized"  [arg-type]
+ xarray/tests/test_dataarray.py:3810: error: Argument 1 to "len" has incompatible type "ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]] | numpy.bool[builtins.bool]"; expected "Sized"  [arg-type]

dedupe (https://github.com/dedupeio/dedupe)
+ dedupe/clustering.py:59: error: Incompatible types in assignment (expression has type "signedinteger[_64Bit]", variable has type "int")  [assignment]
+ dedupe/labeler.py:199: error: Generator has incompatible item type "tuple[int | str, int | str]"; expected "tuple[int, int] | tuple[str, str]"  [misc]
- dedupe/datamodel.py:122: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[float64]]", variable has type "ndarray[tuple[int, int], dtype[Any]]")  [assignment]
- dedupe/convenience.py:43: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[signedinteger[Any]]]")  [assignment]
- dedupe/convenience.py:73: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[signedinteger[Any]]]", variable has type "ndarray[tuple[int], dtype[signedinteger[Any]]]")  [assignment]
+ dedupe/convenience.py:99: error: "signedinteger[_64Bit]" object is not iterable  [misc]
+ dedupe/convenience.py:99: error: Cannot determine type of "p"  [has-type]
+ dedupe/convenience.py:99: error: Cannot determine type of "q"  [has-type]

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/arrays/arrow/_arrow_utils.py:47: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/_numba/executor.py:90: error: Incompatible redefinition (redefinition with type "Callable[[ndarray[tuple[Any, ...], dtype[Any]], ndarray[tuple[Any, ...], dtype[Any]], ndarray[tuple[Any, ...], dtype[Any]], int, VarArg(Any)], Any]", original type "Callable[[ndarray[tuple[Any, ...], dtype[Any]], ndarray[tuple[Any, ...], dtype[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/array_algos/quantile.py:105: 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/tseries/frequencies.py:274: error: List comprehension has incompatible type List[floating[_64Bit]]; expected List[int]  [misc]
+ pandas/tseries/frequencies.py:279: error: List comprehension has incompatible type List[floating[_64Bit]]; expected List[int]  [misc]
+ pandas/core/arrays/arrow/array.py:2543: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/arrays/datetimelike.py:1293: error: No overload variant of "__mul__" of "BaseOffset" matches argument type "signedinteger[_64Bit]"  [operator]
+ pandas/core/arrays/datetimelike.py:1293: note: Possible overload variants:
+ pandas/core/arrays/datetimelike.py:1293: note:     def __mul__(self, ndarray[tuple[Any, ...], dtype[Any]], /) -> ndarray[tuple[Any, ...], dtype[Any]]
+ pandas/core/arrays/datetimelike.py:1293: note:     def __mul__(self, int, /) -> BaseOffset
- 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/core/arrays/categorical.py:1856: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/io/stata.py:1448: error: Invalid index type "unsignedinteger[_8Bit]" for "dict[int, int]"; expected type "int"  [index]
+ pandas/io/stata.py:1450: error: Argument 1 to "append" of "list" has incompatible type "unsignedinteger[_8Bit]"; expected "int"  [arg-type]
- 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/concat.py:936: error: Generator has incompatible item type "ndarray[tuple[int, ...], dtype[Any]]"; expected "ndarray[tuple[int], dtype[Any]]"  [misc]
- pandas/core/reshape/concat.py:940: error: Argument 1 to "append" of "list" has incompatible type "ndarray[tuple[int, ...], dtype[Any]]"; expected "ndarray[tuple[int], dtype[Any]]"  [arg-type]
+ pandas/core/reshape/encoding.py:362: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/internals/managers.py:1527: error: "BlockPlacement" has no attribute "increment_above"  [attr-defined]
+ pandas/core/indexers/objects.py:134: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/indexers/objects.py:135: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/indexers/objects.py:405: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/indexers/objects.py:491: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/core/groupby/groupby.py:1888: error: Unused "type: ignore" comment  [unused-ignore]
+ pandas/io/formats/style_render.py:1243: error: Invalid index type "tuple[signedinteger[_32Bit | _64Bit], signedinteger[_32Bit | _64Bit]]" for "defaultdict[tuple[int, int], Callable[[Any], str]]"; expected type "tuple[int, int]"  [index]

scipy (https://github.com/scipy/scipy)
+ scipy/optimize/_isotonic.py:147: error: Unused "type: ignore" comment  [unused-ignore]
- scipy/spatial/tests/test_spherical_voronoi.py:255: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "list[ndarray[tuple[int, ...], dtype[Any]]]")  [assignment]
+ scipy/spatial/tests/test_spherical_voronoi.py:255: error: Incompatible types in assignment (expression has type "ndarray[tuple[Any, ...], dtype[Any]]", variable has type "list[ndarray[tuple[Any, ...], dtype[Any]]]")  [assignment]

spark (https://github.com/apache/spark)
- python/pyspark/sql/pandas/types.py:633: error: Argument "ambiguous" to "tz_localize" of "_DatetimeLikeNoTZMethods" has incompatible type "Literal[False]"; expected "Literal['raise', 'infer', 'NaT'] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]]"  [arg-type]
+ python/pyspark/sql/pandas/types.py:633: error: Argument "ambiguous" to "tz_localize" of "_DatetimeLikeNoTZMethods" has incompatible type "Literal[False]"; expected "Literal['raise', 'infer', 'NaT'] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]]"  [arg-type]
+ python/pyspark/sql/pandas/conversion.py:621: error: Argument 1 to "len" has incompatible type "dtype[Any]"; expected "Sized"  [arg-type]
+ python/pyspark/sql/pandas/conversion.py:627: error: Incompatible types in assignment (expression has type "str", variable has type "dtype[Any]")  [assignment]
+ python/pyspark/sql/pandas/conversion.py:629: error: Value of type "tuple[str, ...] | None" is not indexable  [index]
- 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 [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[Any, ...], 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[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: None, *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[tuple[Any, ...], 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[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: list[int | str], *, header: int | Sequence[int] | None = ..., names: MutableSequence[Any] | ndarray[tuple[Any, ...], 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[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/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[Any, ...], 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/ml/linalg/__init__.py:1149: error: Incompatible types in assignment (expression has type "ndarray[tuple[int, ...], dtype[Any]]", variable has type "ndarray[tuple[int], dtype[Any]]")  [assignment]
- python/pyspark/ml/functions.py:244: note:     def [_ScalarT: generic[Any]] vstack(tup: Sequence[_SupportsArray[dtype[_ScalarT]] | _NestedSequence[_SupportsArray[dtype[_ScalarT]]]], *, dtype: None = ..., casting: Literal['no', 'equiv', 'safe', 'same_kind', 'unsafe'] = ...) -> ndarray[tuple[int, ...], dtype[_ScalarT]]
+ python/pyspark/ml/functions.py:244: note:     def [_ScalarT: generic[Any]] vstack(tup: Sequence[_SupportsArray[dtype[_ScalarT]] | _NestedSequence[_SupportsArray[dtype[_ScalarT]]]], *, dtype: None = ..., casting: Literal['no', 'equiv', 'safe', 'same_kind', 'unsafe'] = ...) -> ndarray[tuple[Any, ...], dtype[_ScalarT]]
- python/pyspark/ml/functions.py:244: note:     def [_ScalarT: generic[Any]] vstack(tup: Sequence[Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]], *, dtype: type[_ScalarT] | dtype[_ScalarT] | _SupportsDType[dtype[_ScalarT]], casting: Literal['no', 'equiv', 'safe', 'same_kind', 'unsafe'] = ...) -> ndarray[tuple[int, ...], dtype[_ScalarT]]
+ python/pyspark/ml/functions.py:244: note:     def [_ScalarT: generic[Any]] vstack(tup: Sequence[Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str]], *, dtype: type[_ScalarT] | dtype[_ScalarT] | _SupportsDType[dtype[_ScalarT]], casting: Literal['no', 'equiv', 'safe', 'same_kind', 'unsafe'] = ...) -> ndarray[tuple[Any, ...], dtype[_ScalarT]]

... (truncated 4 lines) ...

static-frame (https://github.com/static-frame/static-frame)
+ static_frame/core/util.py:1977: error: Unused "type: ignore" comment  [unused-ignore]
+ static_frame/core/rank.py:79: error: Unused "type: ignore" comment  [unused-ignore]
+ static_frame/core/rank.py:93: error: Unused "type: ignore" comment  [unused-ignore]
+ static_frame/core/rank.py:96: error: Unused "type: ignore" comment  [unused-ignore]
+ static_frame/core/loc_map.py:413: error: Incompatible types in assignment (expression has type "unsignedinteger[_64Bit]", variable has type "ndarray[tuple[Any, ...], dtype[unsignedinteger[_64Bit]]]")  [assignment]
- 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]

scipy-stubs (https://github.com/scipy/scipy-stubs)
- tests/optimize/minimize.pyi:13: error: No overload variant of "minimize" matches argument types "Callable[[ndarray[tuple[int, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]], ndarray[tuple[int, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]], float64]", "int", "tuple[ndarray[tuple[int, ...], dtype[Any]]]", "str", "dict[str, float]"  [call-overload]
+ tests/optimize/minimize.pyi:13: error: No overload variant of "minimize" matches argument types "Callable[[ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]], ndarray[tuple[Any, ...], dtype[floating[_16Bit] | floating[_32Bit] | float64]]], float64]", "int", "tuple[ndarray[tuple[Any, ...], dtype[Any]]]", "str", "dict[str, float]"  [call-overload]

pandera (https://github.com/pandera-dev/pandera)
- pandera/engines/pandas_engine.py:1384: error: Invalid index type "Series[builtins.bool] | DataFrame" for "Series[Any]"; expected type "list[str] | Index[Any] | Series[Any] | slice[Any, Any, Any] | Series[builtins.bool] | ndarray[tuple[int, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | tuple[Hashable | slice[Any, Any, Any], ...]"  [index]
+ pandera/engines/pandas_engine.py:1384: error: Invalid index type "Series[builtins.bool] | DataFrame" for "Series[Any]"; expected type "list[str] | Index[Any] | Series[Any] | slice[Any, Any, Any] | Series[builtins.bool] | ndarray[tuple[Any, ...], dtype[numpy.bool[builtins.bool]]] | list[builtins.bool] | tuple[Hashable | slice[Any, Any, Any], ...]"  [index]
- 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[tuple[Any, ...], 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

... (truncated 16 lines) ...```

jorenham · 2025-05-16T17:17:26Z

@mroeschke here's another one that's causing some new mypy errors in pandas. Are you seeing anything you don't like?

mroeschke · 2025-05-16T18:55:28Z

Looks OK to me

jorenham · 2025-05-17T18:36:21Z

@MarcoGorelli this also touches a bit of np.ma; mind taking a look?

MarcoGorelli

nice, thanks for the ping

charris · 2025-05-19T18:30:41Z

Let's give it a shot. Thanks Joren.

jorenham added the 41 - Static typing label May 16, 2025

This comment has been minimized.

Sign in to view

jorenham marked this pull request as ready for review May 16, 2025 07:31

This comment has been minimized.

Sign in to view

jorenham added 6 commits May 16, 2025 18:53

TYP: add _AnyShape to numpy._typing

aaca767

TYP: use _AnyShape as NDArray shape-type default

3ca7ffb

TYP: use a gradual shape-type if unknown

12b741e

TYP: update the type-tests for gradual shape-type defaults

f5ae1f7

STY: appease ruff

260bfca

TST: fix NDArray doctest

a16ef8c

jorenham force-pushed the typing/gradual-shape-type branch from e190d6c to a16ef8c Compare May 16, 2025 16:53

jorenham added this to the 2.3.0 release milestone May 17, 2025

MarcoGorelli reviewed May 19, 2025

View reviewed changes

Comment thread numpy/__init__.pyi

jorenham mentioned this pull request May 19, 2025

prefer gradual type parameter defaults jorenham/optype#316

Merged

charris merged commit 3c76265 into numpy:main May 19, 2025
76 checks passed

jorenham deleted the typing/gradual-shape-type branch May 19, 2025 18:30

This was referenced May 19, 2025

optionally gradual unbounded shape-types jorenham/optype#318

Merged

✨ Gradual shape-types numpy/numtype#573

Merged

DOC: Add information (maybe just release note) for typing regressions #28077

Closed

This was referenced Jun 4, 2025

optionally tag a team or contact person if a PR is merged with negative effects? hauntsaninja/mypy_primer#128

Open

Shape Typing data-apis/array-api-typing#15

Open

jorenham mentioned this pull request Sep 30, 2025

TYP: shape field is typed Any instead of `tuple[int, ...] #29830

Closed

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Uh oh!

Uh oh!

TYP: Gradual shape type defaults#28982

TYP: Gradual shape type defaults#28982
charris merged 6 commits into
numpy:mainfrom
jorenham:typing/gradual-shape-type

jorenham commented May 16, 2025 •

edited

Loading

Uh oh!

This comment has been minimized.

This comment has been minimized.

jorenham commented May 16, 2025

Uh oh!

github-actions Bot commented May 16, 2025

Uh oh!

jorenham commented May 16, 2025

Uh oh!

mroeschke commented May 16, 2025

Uh oh!

jorenham commented May 17, 2025

Uh oh!

MarcoGorelli left a comment

Uh oh!

Uh oh!

Uh oh!

charris commented May 19, 2025

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

4 participants

Uh oh!

Uh oh!

Conversation

jorenham commented May 16, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Uh oh!

This comment has been minimized.

This comment has been minimized.

jorenham commented May 16, 2025

Uh oh!

github-actions Bot commented May 16, 2025

Uh oh!

jorenham commented May 16, 2025

Uh oh!

mroeschke commented May 16, 2025

Uh oh!

jorenham commented May 17, 2025

Uh oh!

MarcoGorelli left a comment

Choose a reason for hiding this comment

Uh oh!

Uh oh!

Uh oh!

charris commented May 19, 2025

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

4 participants

jorenham commented May 16, 2025 •

edited

Loading