Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/lotabout/fuzzy-matcher
Fuzzy Matching Library for Rust
https://github.com/lotabout/fuzzy-matcher
fuzzy-matching rust text-search
Last synced: 3 months ago
JSON representation
Fuzzy Matching Library for Rust
- Host: GitHub
- URL: https://github.com/lotabout/fuzzy-matcher
- Owner: lotabout
- License: mit
- Created: 2019-03-01T02:36:19.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-02-27T19:43:21.000Z (4 months ago)
- Last Synced: 2024-03-09T21:53:29.883Z (4 months ago)
- Topics: fuzzy-matching, rust, text-search
- Language: Rust
- Homepage:
- Size: 66.4 KB
- Stars: 232
- Watchers: 5
- Forks: 16
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome-stars - fuzzy-matcher
- my-awesome-stars - lotabout/fuzzy-matcher - Fuzzy Matching Library for Rust (Rust)
- awesome-stars - lotabout/fuzzy-matcher - Fuzzy Matching Library for Rust (Rust)
README
[](https://crates.io/crates/fuzzy-matcher)
# Fuzzy Matcher
Fuzzy matching algorithm(s) in Rust!
## Usage
In your Cargo.toml add the following:
```toml
[dependencies]
fuzzy-matcher = "*"
```
Here are some code example:
```rust
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](https://github.com/lotabout/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
- It's based on Smith's post [Reverse Engineering Sublime Text’s Fuzzy Match](https://www.forrestthewoods.com/blog/reverse_engineering_sublime_texts_fuzzy_match/)
- The implementation here actually has some flaws that don't perform well
in certain cases.
- It's recommended to checkout original implementation in [C++](https://github.com/forrestthewoods/lib_fts/blob/master/code/fts_fuzzy_match.h) and [JavaScript](https://github.com/forrestthewoods/lib_fts/blob/master/code/fts_fuzzy_match.js)
### Clangd
- The algorithm is based on [clangd's FuzzyMatch.cpp](https://github.com/MaskRay/ccls/blob/master/src/fuzzy_match.cc).
- 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.