Fix annotations for DataFrame.apply() including additional overloads #448
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gandhis1
commented
Nov 26, 2022
| @@ -155,6 +156,9 @@ AxisType: TypeAlias = Literal["columns", "index", 0, 1] | |||
| DtypeNp = TypeVar("DtypeNp", bound=np.dtype[np.generic]) | |||
| KeysArgType: TypeAlias = Any | |||
| ListLike = TypeVar("ListLike", Sequence, np.ndarray, "Series", "Index") | |||
| ListLikeExceptSeriesAndStr = TypeVar( | |||
| "ListLikeExceptSeriesAndStr", MutableSequence, np.ndarray, tuple, "Index" | |||
| ) | |||
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I agree, the name is awful, but do we have a better way to exclude str from list-likes?
Dr-Irv
requested changes
Nov 26, 2022
Dr-Irv
requested changes
Nov 26, 2022
|
I've updated the overloads to also handle the scalar value type when a |
Dr-Irv
approved these changes
Dec 5, 2022
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assert_type()to assert the type of any return valueIn #401 the annotations for
applywas changed. This introduced false negatives in my code base, because the particular mix of return types and arguments I was using was not supported. Here I am still not sure it is exhaustive but I think it's an improvement. In particular theresult_typeneeds to be accounted for, as well as differentiating between a true list-like,str, andSeriesin the return value of the function.@Dr-Irv @bashtage @danielroseman