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remove types from Index.__iter__()` #532

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Merged
merged 2 commits into from
Feb 10, 2023
Merged

remove types from Index.__iter__()` #532

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1dd248b
remove types from Index.__iter__()`
Dr-Irv Feb 10, 2023
50f4f9f
add some tests
Dr-Irv Feb 10, 2023
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3 changes: 1 addition & 2 deletions pandas-stubs/core/indexes/base.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,6 @@ from pandas._typing import (
DtypeObj,
FillnaOptions,
HashableT,
IndexIterScalar,
IndexT,
Label,
Level,
Expand Down Expand Up @@ -223,7 +222,7 @@ class Index(IndexOpsMixin, PandasObject):
def shape(self) -> tuple[int, ...]: ...
# Extra methods from old stubs
def __eq__(self, other: object) -> np_ndarray_bool: ... # type: ignore[override]
def __iter__(self) -> Iterator[IndexIterScalar | tuple[Hashable, ...]]: ...
def __iter__(self) -> Iterator: ...
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If we were to type the return type, shouldn't this simply have been Iterator[Hashable] (tuple and everything in IndexIterScalar) is hashable?

(Having mypy_primer could have been helpful to see the false-positives earlier.)

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#367 (comment)

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If we were to type the return type, shouldn't this simply have been Iterator[Hashable] (tuple and everything in IndexIterScalar) is hashable?

(Having mypy_primer could have been helpful to see the false-positives earlier.)

If I change it to Iterator[Hashable], then I get this with the test (and example above) from pyright:

Operator "in" not supported for types "Literal['at']" and "Hashable"
  Operator "in" not supported for types "Literal['at']" and "Hashable"

def __ne__(self, other: object) -> np_ndarray_bool: ... # type: ignore[override]
def __le__(self, other: Index | Scalar) -> np_ndarray_bool: ... # type: ignore[override]
def __ge__(self, other: Index | Scalar) -> np_ndarray_bool: ... # type: ignore[override]
Expand Down
11 changes: 10 additions & 1 deletion tests/test_frame.py
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Expand Up @@ -1813,7 +1813,6 @@ def test_frame_index_numpy() -> None:


def test_frame_stack() -> None:

multicol2 = pd.MultiIndex.from_tuples([("weight", "kg"), ("height", "m")])
df_multi_level_cols2 = pd.DataFrame(
[[1.0, 2.0], [3.0, 4.0]], index=["cat", "dog"], columns=multicol2
Expand Down Expand Up @@ -2403,3 +2402,13 @@ def get_NDArray(df: pd.DataFrame, key: npt.NDArray[np.uint64]) -> pd.DataFrame:

a: npt.NDArray[np.uint64] = np.array([10, 30], dtype="uint64")
check(assert_type(get_NDArray(df, a), pd.DataFrame), pd.DataFrame)


def test_in_columns() -> None:
# GH 532 (PR)
df = pd.DataFrame(np.random.random((3, 4)), columns=["cat", "dog", "rat", "pig"])
cols = [c for c in df.columns if "at" in c]
check(assert_type(cols, list), list, str)
check(assert_type(df.loc[:, cols], pd.DataFrame), pd.DataFrame)
check(assert_type(df[cols], pd.DataFrame), pd.DataFrame)
check(assert_type(df.groupby(by=cols).sum(), pd.DataFrame), pd.DataFrame)
9 changes: 3 additions & 6 deletions tests/test_indexes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,6 @@
import datetime as dt
from typing import (
TYPE_CHECKING,
Hashable,
List,
Tuple,
Union,
)
Expand All @@ -29,7 +27,6 @@
if TYPE_CHECKING:
from pandas.core.indexes.numeric import NumericIndex

from pandas._typing import IndexIterScalar
else:
if not PD_LTE_15:
from pandas import Index as NumericIndex
Expand Down Expand Up @@ -108,7 +105,7 @@ def test_column_sequence() -> None:
df = pd.DataFrame([1, 2, 3])
col_list = list(df.columns)
check(
assert_type(col_list, List[Union["IndexIterScalar", Tuple[Hashable, ...]]]),
assert_type(col_list, list),
list,
int,
)
Expand Down Expand Up @@ -684,14 +681,14 @@ def test_sorted_and_list() -> None:
check(
assert_type(
sorted(i1),
List[Union["IndexIterScalar", Tuple[Hashable, ...]]],
list,
),
list,
)
check(
assert_type(
list(i1),
List[Union["IndexIterScalar", Tuple[Hashable, ...]]],
list,
),
list,
)
Expand Down