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perf: Use semi-join instead of unique for checking 1:N relationships #362

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Merged
Oliver Borchert (borchero) merged 2 commits into from
Jul 7, 2026
+4 −4
Merged

perf: Use semi-join instead of unique for checking 1:N relationships #362

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7137163
perf: Use semi-join instead of `unique` for checking 1:N relationships
borchero Jul 6, 2026
3574fd7
Fix benchmark
borchero Jul 6, 2026
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4 changes: 2 additions & 2 deletions dataframely/functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -84,9 +84,9 @@ def require_relationship_one_to_at_least_one(
columns, filtered to ensure a 1:{1,N} relationship.
"""
if drop_duplicates:
return lhs.unique(on, keep="none").join(rhs.unique(on), on=on)
return lhs.unique(on, keep="none").join(rhs, on=on, how="semi")

return lhs.join(rhs.unique(on), on=on)
return lhs.join(rhs, on=on, how="semi")
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# ------------------------------------------------------------------------------------ #
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4 changes: 2 additions & 2 deletions tests/benches/test_collection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,13 +15,13 @@ def partitioned_dataset(dataset: pl.DataFrame) -> dict[str, pl.DataFrame]:
"elevation",
"aspect",
"slope",
idx=pl.int_range(pl.len(), dtype=pl.UInt32),
idx=pl.int_range(pl.len(), dtype=pl.UInt32).shuffle(),
),
"second": dataset.select(
"horizontal_distance_to_hydrology",
"vertical_distance_to_hydrology",
"horizontal_distance_to_roadways",
idx=pl.int_range(pl.len(), dtype=pl.UInt32),
idx=pl.int_range(pl.len(), dtype=pl.UInt32).shuffle(),
),
}

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