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# fuzzy-native
[](https://travis-ci.org/hansonw/fuzzy-native)
Fuzzy string matching library package for Node. Implemented natively in C++ for speed with support for multithreading.
The scoring algorithm is heavily tuned for file paths, but should work for general strings.
## API
(from [main.js.flow](lib/main.js.flow))
```
export type MatcherOptions = {
// Default: false
caseSensitive?: boolean,
// Default: infinite
maxResults?: number,
// Maximum gap to allow between consecutive letters in a match.
// Provide a smaller maxGap to speed up query results.
// Default: unlimited
maxGap?: number;
// Default: 1
numThreads?: number,
// Default: false
recordMatchIndexes?: boolean,
}
export type MatchResult = {
value: string,
// A number in the range (0-1]. Higher scores are more relevant.
// 0 denotes "no match" and will never be returned.
score: number,
// Matching character index in `value` for each character in `query`.
// This can be costly, so this is only returned if `recordMatchIndexes` was set in `options`.
matchIndexes?: Array<number>,
}
export class Matcher {
constructor(candidates: Array<string>) {}
// Returns all matching candidates (subject to `options`).
// Will be ordered by score, descending.
match: (query: string, options?: MatcherOptions) => Array<MatchResult>;
addCandidates: (candidates: Array<string>) => void;
removeCandidates: (candidates: Array<string>) => void;
setCandidates: (candidates: Array<string>) => void;
}
```
See also the [spec](spec/fuzzy-native-spec.js) for basic usage.
## Scoring algorithm
The scoring algorithm is mostly borrowed from 's excellent [command-t](https://github.com/wincent/command-t) vim plugin; most of the code is from [his implementation in match.c](https://github.com/wincent/command-t/blob/master/ruby/command-t/match.c).
Read [the source code](src/score_match.cpp) for a quick overview of how it works (the function `recursive_match`).
NB: [score_match.cpp](src/score_match.cpp) and [score_match.h](src/score_match.h) have no dependencies besides the C/C++ stdlib and can easily be reused for other purposes.
There are a few notable additional optimizations:
- Before running the recursive matcher, we first do a backwards scan through the haystack to see if the needle exists at all. At the same time, we compute the right-most match for each character in the needle to prune the search space.
- For each candidate string, we pre-compute and store a bitmask of its letters in `MatcherBase`. We then compare this the "letter bitmask" of the query to quickly prune out non-matches.