pip install polars
pip install polars-fuzzy-matchWith 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 │
└─────────────┴───────┘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:
| Pattern | Match type | Description |
|---|---|---|
bar |
fuzzy | items that fuzzy match bar e.g. 'bXXaXXr' |
'foo |
substring exact match | items that include foo e.g. 'is foo ok' |
^music |
prefix exact match | items that start with music |
.mp3$ |
suffix exact match | items that end with .mp3 |
!fire |
inverse exact match | items that do not include fire |
!^music |
inverse prefix exact match | items that do not start with music |
!.mp3$ |
inverse suffix exact match | items that do not end with .mp3 |