fuzzy-muff

Crates.iofuzzy-muff
lib.rsfuzzy-muff
version
sourcesrc
created_at2023-05-17 04:16:54.768382
updated_at2024-12-10 09:40:20.270162
descriptionFuzzy Matching Library
homepagehttps://github.com/lotabout/fuzzy-matcher
repositoryhttps://github.com/lotabout/fuzzy-matcher
max_upload_size
id866584
Cargo.toml error:TOML parse error at line 21, column 1 | 21 | autolib = false | ^^^^^^^ unknown field `autolib`, expected one of `name`, `version`, `edition`, `authors`, `description`, `readme`, `license`, `repository`, `homepage`, `documentation`, `build`, `resolver`, `links`, `default-run`, `default_dash_run`, `rust-version`, `rust_dash_version`, `rust_version`, `license-file`, `license_dash_file`, `license_file`, `licenseFile`, `license_capital_file`, `forced-target`, `forced_dash_target`, `autobins`, `autotests`, `autoexamples`, `autobenches`, `publish`, `metadata`, `keywords`, `categories`, `exclude`, `include`
size0
(kimono-koans)

documentation

https://docs.rs/fuzzy-matcher

README

Crates.io

Fuzzy Matcher

Fuzzy matching algorithm(s) in Rust!

Usage

In your Cargo.toml add the following:

[dependencies]
fuzzy-matcher = "*"

Here are some code example:

use fuzzy_matcher::FuzzyMatcher;
use fuzzy_matcher::skim::SkimMatcherV2;

let matcher = SkimMatcherV2::default();
assert_eq!(None, matcher.fuzzy_match("abc", "abx"));
assert!(matcher.fuzzy_match("axbycz", "abc").is_some());
assert!(matcher.fuzzy_match("axbycz", "xyz").is_some());

let (score, indices) = matcher.fuzzy_indices("axbycz", "abc").unwrap();
assert_eq!(indices, [0, 2, 4]);
  • fuzzy_match only return scores while fuzzy_indices returns the matching indices as well.
  • Both function return None if the pattern won't match.
  • The score is the higher the better.

More example

echo "axbycz" | cargo run --example fz "abc" and check what happens.

About the Algorithm

Skim

The skim is currently used by skim, a fuzzy finder.

Skim V2

  • Just like fzf v2, the algorithm is based on Smith-Waterman algorithm which is normally used in DNA sequence alignment
  • Also checkout https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/gaps.pdf for more details
  • The time complexity is O(mn) where m, n are the length of the pattern and input line.
  • Space complexity is O(mn) for fuzzy_indices and O(2n) for fuzzy_match which will compress the table for dynamic programming.
  • V2 matcher has an option to set the max element of the score matrix, if m*n exceeded the limit, it will fallback to a linear search.

Skim V1

Clangd

  • The algorithm is based on clangd's FuzzyMatch.cpp.
  • Also checkout https://github.com/lewang/flx/issues/98 for some variants.
  • The algorithm is O(mn) where m, n are the length of the pattern and input line.
  • Space complexity is O(mn) for fuzzy_indices and O(2n) for fuzzy_match which will compress the table for dynamic programming.
Commit count: 65

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