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fix(python): Panic on empty df / null List(Categorical) #16730

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merged 3 commits into from
Jun 5, 2024
Merged

fix(python): Panic on empty df / null List(Categorical) #16730

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f34a7b3
fix panic on empty/null List(Categorical)
Object905 Jun 4, 2024
3493ed1
don't clone twice
Object905 Jun 4, 2024
34f1136
assert cats is empty when rev_map is None
Object905 Jun 5, 2024
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5 changes: 4 additions & 1 deletion crates/polars-core/src/series/from.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -84,9 +84,12 @@ impl Series {
#[cfg(feature = "dtype-categorical")]
dt @ (Categorical(rev_map, ordering) | Enum(rev_map, ordering)) => {
let cats = UInt32Chunked::from_chunks(name, chunks);
let rev_map = rev_map
.clone()
.unwrap_or_else(|| Arc::new(RevMapping::default()));
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We should assert cats is emtpy if we set an empty rev map.

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Maybe should add it directly in from_cats_and_rev_map_unchecked under cfg(debug_assertions)?
But this seems to be the only place when they're unwrapped, so I added it just here for now.

let mut ca = CategoricalChunked::from_cats_and_rev_map_unchecked(
cats,
rev_map.clone().unwrap(),
rev_map,
matches!(dt, Enum(_, _)),
*ordering,
);
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19 changes: 19 additions & 0 deletions py-polars/tests/unit/datatypes/test_list.py
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Expand Up @@ -832,3 +832,22 @@ def test_list_str_sum_exception_12935() -> None:
def test_list_list_sum_exception_12935() -> None:
with pytest.raises(pl.exceptions.InvalidOperationError):
pl.Series([[1], [2]]).sum()


def test_null_list_categorical_16405() -> None:
df = pl.DataFrame(
[(None, "foo")],
schema={
"match": pl.List(pl.Categorical),
"what": pl.Categorical,
},
)

df = df.select(
pl.col("match")
.list.set_intersection(pl.concat_list(pl.col("what")))
.alias("result")
)

expected = pl.DataFrame([None], schema={"result": pl.List(pl.Categorical)})
assert_frame_equal(df, expected)
5 changes: 5 additions & 0 deletions py-polars/tests/unit/test_empty.py
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Expand Up @@ -137,3 +137,8 @@ def test_empty_to_empty(method: str) -> None:
def test_empty_shift_over_16676() -> None:
df = pl.DataFrame({"a": [], "b": []})
assert df.with_columns(pl.col("a").shift(fill_value=0).over("b")).shape == (0, 2)


def test_empty_list_cat_16405() -> None:
df = pl.DataFrame(schema={"cat": pl.List(pl.Categorical)})
df.select(pl.col("cat") == pl.col("cat"))
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