itertuples #842
itertuples #842
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pandas-stubs/core/frame.pyi
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| @@ -250,7 +250,7 @@ class DataFrame(NDFrame, OpsMixin): | |||
| def iterrows(self) -> Iterable[tuple[Hashable, Series]]: ... | |||
| def itertuples( | |||
| self, index: _bool = ..., name: _str | None = ... | |||
| ) -> Iterable[tuple[Any, ...]]: ... | |||
| ) -> Iterable[Any]: ... | |||
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I'm wondering if we could do something like this:
class _PandasNamedTuple(tuple[Any,...]):
def __getattr__(self, field: str) -> Any: ...Then have itertuples() return Iterable[_PandasNamedTuple]
Then at least you know you're getting a tuple.
tests/test_frame.py
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| @@ -20,6 +20,7 @@ | |||
| Any, | |||
| Callable, | |||
| Generic, | |||
| TypeAlias, | |||
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Needs to come from typing_extensions. Failed under python 3.9
pandas-stubs/core/frame.pyi
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| @@ -2279,3 +2279,6 @@ class DataFrame(NDFrame, OpsMixin): | |||
| ) -> Self: ... | |||
| def __truediv__(self, other: float | DataFrame | Series | Sequence) -> Self: ... | |||
| def __rtruediv__(self, other: float | DataFrame | Series | Sequence) -> Self: ... | |||
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| class _PandasNamedTuple(tuple[Any, ...]): | |||
| def __getattr__(self, field: str) -> Any: ... | |||
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I'm thinking we should return Scalar here, because we also return Scalar when someone does df.loc[3, "a"]
While it's true that some non-scalar value could be an individual element of a DataFrame, I've taken the philosophy of limiting the types to what is "normal" usage, and if you put a funky type in a DataFrame or Series, then you can do a cast to fix it. I've done that in some of our application code when we have lists or other objects inside a Series or DataFrame.
assert_type()to assert the type of any return value