Fuzzball.js

Easy to use and powerful fuzzy string matching.

This is a JavaScript port of https://github.com/seatgeek/fuzzywuzzy. Uses fast-levenshtein https://github.com/hiddentao/fast-levenshtein for distance calculations, with a slight modification to match the behavior of python-Levenshtein. (substitutions are weighted 2 instead of 1 in ratio calculations. can specify an options.subcost to override)

Try it out: https://runkit.com/npm/fuzzball

Requirements

• difflib.js (for the scorers that use partial_ratio)

Installation

Using NPM

npm install fuzzball

Usage

var fuzz = require('fuzzball');
fuzz.ratio("this is a test", "this is a test!")
        100

// eh, don't need to clean it up..
var options = {full_process: false}; //non-alphanumeric will not be converted to whitespace if false, default true
fuzz.ratio("this is a test", "this is a test!", options) 
        97

Simple Ratio

fuzz.ratio("this is a test", "this is a test!")
        100

Partial Ratio

fuzz.partial_ratio("this is a test", "this is a test!")
        100
fuzz.partial_ratio("this is a test", "this is a test again!") //still 100
        100

Token Sort Ratio

fuzz.ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
        91
fuzz.token_sort_ratio("fuzzy wuzzy was a bear", "wuzzy fuzzy was a bear")
        100

Token Set Ratio

fuzz.token_sort_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
        84
fuzz.token_set_ratio("fuzzy was a bear", "fuzzy fuzzy was a bear")
        100

International

// full_process must be set to false if useCollator is true
// or non-roman alphanumeric will be removed (got a good locale-specific alphanumeric check in js?)
var options = {full_process: false, useCollator: true};
fuzz.ratio("this is ä test", "this is a test", options)
        100

Extract (search a list of choices for top results)

Simple: array of strings

var query = "polar bear";
var choices = ["brown bear", "polar bear", "koala bear"];

results = fuzz.extract(query, choices);

[ [ 'polar bear', 100 ],
  [ 'koala bear', 80 ],
  [ 'brown bear', 60 ] ]

Less simple: array of objects with a processor function + options (all except query and choices are optional)

Processor function takes each choice and outputs the string which will be used for scoring

var query = "126abzx";
var choices = [{id: 345, modelnumber: "123abc"},{id: 346, modelnumber: "123efg"},{id: 347, modelnumber: "456abdzx"}];
var scorer = fuzz.partial_ratio;
var processor = function(choice) {return choice['modelnumber']}
var limit = 2; // max number of results
var cutoff = 50; // lowest score to return
var options = {}; // (can specify non-default values for full_process, useCollator, force_ascii, subcost)

results = fuzz.extract(query, choices, scorer, processor, limit, cutoff, options);

[ [ { id: 345, modelnumber: '123abc' }, 67 ],
 [ { id: 347, modelnumber: '456abdzx' }, 57 ] ]

Distance (Levenshtein distance without any ratio calculations)

fuzz.distance("fuzzy was a bear", "fozzy was a bear")
        1

Other scoreing options:

partial_token_set_ratio, partial_token_sort_ratio, WRatio (WRatio is weighted based on relative string length, runs tests based on relative length and returns top score)

Pre-Processing

Is run by default unless options.full_process is set to false, but can run separately as well. (so if searching same list repeatedly can only run once)

fuzz.full_process("myt^eXt!")
        myt ext