8000 ENH: Add dtype-support to the ufunc-based `ndarray` magic methods 4/4 by BvB93 · Pull Request #18417 · numpy/numpy · GitHub
[go: up one dir, main page]
Skip to content

ENH: Add dtype-support to the ufunc-based ndarray magic methods 4/4 #18417

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.

Sign up for GitHub

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

Merged
merged 6 commits into from
Mar 6, 2021
Merged

ENH: Add dtype-support to the ufunc-based ndarray magic methods 4/4 #18417

Changes from 1 commit
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
0148bf8
TST: Validate the mypy exit-code
Feb 12, 2021
7b43240
TST: Improve a number of mypy-related exception messages
Feb 12, 2021
2cc9e29
ENH: Add dtype-support to the (ufunc-based) `ndarray` inplace magic m…
Jan 26, 2021
982468e
TST: Add typing tests for the inplace `ndarray` magic methods
Feb 12, 2021
376ba3a
MAINT: Disallow `timedelta64 % integer`-based operations
Feb 15, 2021
c6bdbad
MAINT: Removed a redundant overload
Mar 4, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
8000 Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
MAINT: Disallow timedelta64 % integer-based operations 
`timedelta64` does not support the `__mod__` and `__divmod__` operations with integers and booleans
  • Loading branch information
Bas van Beek committed Mar 4, 2021
commit 376ba3a9f50397dc94b98253980de0bf0ebc0b68
8 changes: 4 additions & 4 deletions numpy/__init__.pyi
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1641,7 +1641,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]):
@overload
def __mod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc]
@overload
def __mod__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ...
def __mod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[timedelta64]: ...
@overload
def __mod__(self: _ArrayND[object_], other: Any) -> Any: ...
@overload
Expand All @@ -1663,7 +1663,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]):
@overload
def __rmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _ArrayOrScalar[floating[Any]]: ... # type: ignore[misc]
@overload
def __rmod__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> _ArrayOrScalar[timedelta64]: ...
def __rmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> _ArrayOrScalar[timedelta64]: ...
@overload
def __rmod__(self: _ArrayND[object_], other: Any) -> Any: ...
@overload
Expand All @@ -1685,7 +1685,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]):
@overload
def __divmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[_ArrayOrScalar[floating[Any]]]: ... # type: ignore[misc]
@overload
def __divmod__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> Union[Tuple[int64, timedelta64], Tuple[_ArrayND[int64], _ArrayND[timedelta64]]]: ...
def __divmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> Union[Tuple[int64, timedelta64], Tuple[_ArrayND[int64], _ArrayND[timedelta64]]]: ...
@overload
def __divmod__(
self: _ArrayND[Union[bool_, integer[Any], floating[Any], timedelta64]],
Expand All @@ -1703,7 +1703,7 @@ class ndarray(_ArrayOrScalarCommon, Generic[_ShapeType, _DType_co]):
@overload
def __rdivmod__(self: _ArrayFloat_co, other: _ArrayLikeFloat_co) -> _2Tuple[_ArrayOrScalar[floating[Any]]]: ... # type: ignore[misc]
@overload
def __rdivmod__(self: _ArrayTD64_co, other: _ArrayLikeTD64_co) -> Union[Tuple[int64, timedelta64], Tuple[_ArrayND[int64], _ArrayND[timedelta64]]]: ...
def __rdivmod__(self: _ArrayTD64_co, other: _NestedSequence[_SupportsArray[dtype[timedelta64]]]) -> Union[Tuple[int64, timedelta64], Tuple[_ArrayND[int64], _ArrayND[timedelta64]]]: ...
@overload
def __rdivmod__(
self: _ArrayND[Union[bool_, integer[Any], floating[Any], timedelta64]],
Expand Down
0