Update list.{count, index, remove} to accept `object` type by randolf-scholz · Pull Request #15472 · python/typeshed
Diff from mypy_primer, showing the effect of this PR on open source code:
optuna (https://github.com/optuna/optuna) + tests/visualization_tests/test_rank.py:699: error: Need type annotation for "x2" [var-annotated] pwndbg (https://github.com/pwndbg/pwndbg) + pwndbg/aglib/elf.py:448: error: Unused "type: ignore" comment [unused-ignore] colour (https://github.com/colour-science/colour) - colour/utilities/network.py:1772: error: Argument 1 to "remove" of "list" has incompatible type "PortNode"; expected "Self" [arg-type] - colour/notation/munsell.py:2573: error: Argument 1 to "index" of "list" has incompatible type "tuple[Any, Any, Any]"; expected "tuple[float, float]" [arg-type] - colour/notation/munsell.py:2578: error: Argument 1 to "index" of "list" has incompatible type "tuple[Any, Any, Any]"; expected "tuple[float, float]" [arg-type] - colour/notation/munsell.py:2585: error: Argument 1 to "index" of "list" has incompatible type "tuple[Any, Any, Any]"; expected "tuple[float, float]" [arg-type] - colour/notation/munsell.py:2590: error: Argument 1 to "index" of "list" has incompatible type "tuple[Any, Any, Any]"; expected "tuple[float, float]" [arg-type] - colour/plotting/models.py:1457: error: Incompatible types in assignment (expression has type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | str | _NestedSequence[complex | bytes | str]", variable has type "ndarray[tuple[Any, ...], dtype[Any]]") [assignment] + colour/plotting/models.py:1457: error: Incompatible types in assignment (expression has type "Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | str | _NestedSequence[complex | bytes | str]", variable has type "ndarray[Any, Any]") [assignment] xarray (https://github.com/pydata/xarray) + xarray/tests/test_concat.py: note: In function "create_typed_datasets": + xarray/tests/test_concat.py:112: error: Argument 1 to "reshape" has incompatible type "list[Timedelta]"; expected "_SupportsArray[dtype[Never]] | _NestedSequence[_SupportsArray[dtype[Never]]]" [arg-type] + xarray/tests/test_concat.py: note: At top level: + xarray/tests/test_backends.py:2062: error: Need type annotation for "expected" [var-annotated] dedupe (https://github.com/dedupeio/dedupe) + dedupe/labeler.py:410: error: List item 1 has incompatible type "Iterable[Literal[0, 1]]"; expected "_SupportsArray[dtype[signedinteger[_64Bit]]] | _NestedSequence[_SupportsArray[dtype[signedinteger[_64Bit]]]]" [list-item] pandas (https://github.com/pandas-dev/pandas) + pandas/core/dtypes/dtypes.py:974: error: Need type annotation for "np_dtype" [var-annotated] + pandas/core/dtypes/dtypes.py:975: error: Argument 1 has incompatible type "list[dtype[Any] | ExtensionDtype]"; expected "_SupportsArray[dtype[Never]] | _NestedSequence[_SupportsArray[dtype[Never]]]" [arg-type] + pandas/core/arrays/sparse/array.py:1452: error: Need type annotation for "sparse_values" [var-annotated] + pandas/plotting/_matplotlib/misc.py:170: error: Need type annotation for "s" [var-annotated] + pandas/plotting/_matplotlib/core.py:1205: error: List item 0 has incompatible type "Number | number[Any, int | float | complex]"; expected "_SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]]" [list-item] jax (https://github.com/google/jax) + jax/experimental/key_reuse/_core.py:395: error: Unused "type: ignore" comment [unused-ignore] scipy-stubs (https://github.com/scipy/scipy-stubs) + tests/special/test_ufuncs.pyi:69: error: Argument 1 to "__call__" of "_UFunc11f" has incompatible type "list[complex]"; expected "CanArrayND[floating[_16Bit] | integer[Any] | numpy.bool[builtins.bool], tuple[Any, ...]] | SequenceND[CanArrayND[floating[_16Bit] | integer[Any] | numpy.bool[builtins.bool], tuple[Any, ...]]] | SequenceND[JustFloat | int]" [arg-type] + tests/special/test_ufuncs.pyi:69: note: "list" is missing following "CanArrayND" protocol member: + tests/special/test_ufuncs.pyi:69: note: __array__