/fuzzy-matcher

Fuzzy Matching Library for Rust

Primary LanguageRustMIT LicenseMIT

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 lewang/flx#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.