# About It's a implementation of [Jaro-Winkler distance](http://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance) algorithm, it uses C extension and will fallback to pure Ruby version in JRuby. Both implementation supports UTF-8 string. **Windows Issue** It will fallabck to pure Ruby implementation on Windows since it can't be compiled currently. (ref [#1](https://github.com/tonytonyjan/jaro_winkler/issues/1)) # Installation ``` gem install jaro_winkler ``` # Usage ```ruby require 'jaro_winkler' JaroWinkler.distance "MARTHA", "MARHTA" # => 0.9611 JaroWinkler.distance "MARTHA", "marhta", case_match: true # => 0.9611 JaroWinkler.distance "MARTHA", "MARHTA", weight: 0.2 # => 0.9778 # Force the strategy JaroWinkler.c_distance "MARTHA", "MARHTA" # C extension JaroWinkler.r_distance "MARTHA", "MARHTA" # Pure Ruby ``` **Both implementations support UTF-8 string.** ## Options Name | Type | Default | Note ----------- | ------ | ------- | ------------------------------------------------------------------------------------------------------------ case_match | boolean | false | All lower case characters are converted to upper case prior to the comparison. weight | number | 0.1 | A constant scaling factor for how much the score is adjusted upwards for having common prefixes. threshold | number | 0.7 | The prefix bonus is only added when the compared strings have a Jaro distance above the threshold. # Why This? There is also another gem named [fuzzy-string-match](https://github.com/kiyoka/fuzzy-string-match), it uses the same algorithm and both provides C and Ruby implementation. I reinvent this wheel because of the naming in `fuzzy-string-match` such as `getDistance` breaks convention, and some weird code like `a1 = s1.split( // )` (`s1.chars` could be better), furthermore, it's bugged: string 1 | string 2 | origin | fuzzy-string-match | jaro_winkler ---------- | ---------- | -------- | ------------------ | ------------------ "henka" | "henkan" | 0.966667 | 0.9722 (wrong) | 0.9666666666666667 "al" | "al" | 1.000000 | 1.0 | 1.0 "martha" | "marhta" | 0.961111 | 0.9611 | 0.9611111111111111 "jones" | "johnson" | 0.832381 | 0.8323 | 0.8323809523809523 "abcvwxyz" | "cabvwxyz" | 0.958333 | 0.9583 | 0.9583333333333333 "dwayne" | "duane" | 0.840000 | 0.8400 | 0.84 "dixon" | "dicksonx" | 0.813333 | 0.8133 | 0.8133333333333332 "fvie" | "ten" | 0.000000 | 0.0 | 0 - The origin result is from the [original C implementation by the author of the algorithm](http://web.archive.org/web/20100227020019/http://www.census.gov/geo/msb/stand/strcmp.c). - Test data are borrowed from [fuzzy-string-match's rspec file](https://github.com/kiyoka/fuzzy-string-match/blob/master/test/basic_pure_spec.rb). ## Benchmark - jaro_winkler (1.0.1) - fuzzy-string-match (0.9.6) ```ruby require 'benchmark' require 'jaro_winkler' require 'fuzzystringmatch' ary = [['al', 'al'], ['martha', 'marhta'], ['jones', 'johnson'], ['abcvwxyz', 'cabvwxyz'], ['dwayne', 'duane'], ['dixon', 'dicksonx'], ['fvie', 'ten']] n = 100000 Benchmark.bmbm do |x| x.report 'jaro_winkler ' do n.times{ ary.each{ |str1, str2| JaroWinkler.distance(str1, str2) } } end x.report 'fuzzystringmatch' do jarow = FuzzyStringMatch::JaroWinkler.create(:pure) n.times{ ary.each{ |str1, str2| jarow.getDistance(str1, str2) } } end end # user system total real # jaro_winkler 12.480000 0.010000 12.490000 ( 12.497828) # fuzzystringmatch 14.990000 0.010000 15.000000 ( 15.014898) ``` # Todo - Adjusting word table (Reference to original C implementation.)