Polars Fuzzy Matching

Installation

pip install polars
pip install polars-fuzzy-match

Usage

With both the plugin and polars installed, usage is as follows:

import polars as pl
from polars_fuzzy_match import fuzzy_match_score


df = pl.DataFrame(
    {
        'strs': ['foo', 'foo quz BAR', 'baaarfoo', 'quz'],
    }
)
pattern = 'bar'
out = df.with_columns(
    score=fuzzy_match_score(
        pl.col('strs'),
        pattern,
    )
)
print(out)

This outputs:

shape: (4, 2)
┌─────────────┬───────┐
│ strs        ┆ score │
│ ---         ┆ ---   │
│ str         ┆ u32   │
╞═════════════╪═══════╡
│ foo         ┆ null  │
│ foo quz BAR ┆ 88    │
│ baaarfoo    ┆ 74    │
│ quz         ┆ null  │
└─────────────┴───────┘

When there is no match, score is null. When the pattern matches the value in the given column, score is non-null. The higher the score, the closer the value is to the pattern. Therefore, we can filter out values that do not match and order by score:

pattern = 'bar'
out = (
    df.with_columns(
        score=fuzzy_match_score(
            pl.col('strs'),
            pattern,
        )
    )
    .filter(pl.col('score').is_not_null())
    .sort(by='score', descending=True)
)
print(out)

This outputs:

shape: (2, 2)
┌─────────────┬───────┐
│ strs        ┆ score │
│ ---         ┆ ---   │
│ str         ┆ u32   │
╞═════════════╪═══════╡
│ foo quz BAR ┆ 88    │
│ baaarfoo    ┆ 74    │
└─────────────┴───────┘

Fzf-style search syntax

This plugin supports Fzf-style search syntax for the pattern. It's worth noting that this section is taken almost verbatim from the Fzf README:

Credits

1. Marco Gorelli's Tutorial on writing Polars Plugin. See here.
2. The Helix Editor team for the Nucleo fuzzy matching library.