TYP: Gradual shape type defaults #28982
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mypy primer is looking pretty good in general |
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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) ...``` |
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@mroeschke here's another one that's causing some new mypy errors in pandas. Are you seeing anything you don't like? |
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Looks OK to me |
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@MarcoGorelli this also touches a bit of |
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From the typing spec:
So by using
tuple[Any, ...]instead oftuple[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.