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Comment on lines 601 to 605
check(
assert_type(df.iterrows(), "Iterable[tuple[Hashable, pd.Series]]"),
assert_type(df.iterrows(), "Iterator[tuple[Hashable, pd.Series]]"),
Iterable,
tuple,
)
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Can we add a test of this form for iterrows() and itertuples():

for t1, t2 in df.iterrows():
    check(assert_type(t1, Hashable), Hashable)
    check(assert_type(t2, pd.Series), pd.Series)

Comment on lines 631 to 633
for t1 in df.itertuples():
check(assert_type(t1, _PandasNamedTuple), _PandasNamedTuple)

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We shouldn't be using _PandasNamedTuple here in the call to check because what is happening internally is that pandas is creating a new class of type pandas.core.foo.Pandas, and if you use the name="Foobar" argument, the class is of the type pandas.core.foo.Foobar

But it's a dynamic class, so I think something like this would be appropriate:

for t1 in df.itertuples():
    assert_type(t1, _PandasNamedTuple)
    assert(t1.__class__.__name__ == "Pandas")
    assert(isinstance(t1.Index, int))
    assert(isinstance(t1.col1, int))  
    assert(isinstance(t1.col2, int))
    for k in [0, 1, 2]:
        assert(isinstance(t1[k], int))

And you could add a similar test for having name="Foobar" as the argument, and only the line that checks the name of the class would need to be changed.

assert isinstance(t1.Index, int)
assert isinstance(t1.col1, int)
assert isinstance(t1.col2, int)
for k in [0, 1]:
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This loop and the one below should be for k in [0,1,2] since the tuple has 3 components.

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Ahh yes correct I thought it was iterating over the number of elements.

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@Dr-Irv Dr-Irv merged commit 925584b into pandas-dev:main May 21, 2025
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@tilsche
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tilsche commented May 28, 2025

Thank you for the quick fix, merge and release.

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Successfully merging this pull request may close these issues.

Return type for DataFrame/Series iteration methods should be Iterator, not Iterable
3 participants