Add configurable distance metric for fuzzy join nearest‑neighbor matching #1861
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hello @sabasiddique1! The CI doesn't pass, could you fix it please? It looks like it's because of the styling, it's explained how to deal with it here in the contribution guide. |
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| # Test that invalid metric raises error | ||
| with pytest.raises(ValueError): | ||
| fuzzy_join(left, right, on="A", metric='invalid_metric') |
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This should be in a stand-alone test, to keep tests unitary and dedicated to a specific purpose.
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| c = fuzzy_join(b, a, left_on="col3", right_on="col1", add_match_info=True) | ||
| assert ns.shape(c)[0] == len(b) | ||
| def test_fuzzy_join_distance_metrics(df_module): |
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| left, right, on="A", suffix="r", metric='euclidean', add_match_info=False | ||
| ) | ||
| assert ns.shape(result_euclidean)[0] == 2 | ||
| assert ns.shape(result_euclidean)[1] == 3 # A, Ar, Br |
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The comment # A, Ar, Br is unclear to me, what do you mean here?
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REF: #1847
Goal
Allow users to choose the distance metric used for nearest‑neighbor matching in
fuzzy_join/Joiner, enabling alternatives like cosine or manhattan for different data types.Context / Issue
Addresses enhancement request to support non‑Euclidean distance metrics for fuzzy join nearest neighbors.
What changed (step‑by‑step)
metricparameter tofuzzy_joinandJoinerwith default'euclidean'.metricthrough the matching classes tosklearn.neighbors.NearestNeighbors.Tests
pytest skrub/tests/test_fuzzy_join.py -v