Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Linting fails with No overload variant of "__setitem__" of "ndarray" matches argument types on `numpy #8966

Open
hendrikmakait opened this issue Dec 12, 2024 · 1 comment

Comments

@hendrikmakait
Copy link
Member

CI: https://github.com/dask/distributed/actions/runs/12297748764/job/34319586733#step:4:144

Traceback

distributed/shuffle/_rechunk.py:756: error: No overload variant of "__setitem__" of "ndarray" matches argument types "tuple[int, ...]", "TaskRef"  [call-overload]
distributed/shuffle/_rechunk.py:756: note: Possible overload variants:
distributed/shuffle/_rechunk.py:756: note:     def __setitem__(self, str | list[str], _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes], /) -> None
distributed/shuffle/_rechunk.py:756: note:     def __setitem__(self, SupportsIndex | slice | EllipsisType | _SupportsArray[dtype[numpy.bool[builtins.bool]] | dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]] | dtype[integer[Any]]]] | builtins.bool | int | _NestedSequence[builtins.bool | int] | tuple[SupportsIndex | slice | EllipsisType | _SupportsArray[dtype[numpy.bool[builtins.bool]] | dtype[integer[Any]]] | _NestedSequence[_SupportsArray[dtype[numpy.bool[builtins.bool]] | dtype[integer[Any]]]] | builtins.bool | int | _NestedSequence[builtins.bool | int] | None, ...] | None, _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes], /) -> None
Found 1 error in 1 file (checked 339 source files)

Error: Process completed with exit code 1.

This is likely caused by numpy/numpy#27964

@phofl
Copy link
Collaborator

phofl commented Dec 18, 2024

the legacy df removal PR has a fix for that

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

2 participants