Inspired by bevacqua/fuzzysearch, a fuzzy matching library written in JavaScript. But contains some extras like ranking using Levenshtein distance and finding matches in a list of words.
Fuzzy searching allows for flexibly matching a string with partial input, useful for filtering data very quickly based on lightweight user input.
The current implementation uses the algorithm suggested by Mr. Aleph, a russian compiler engineer working at V8.
go get github.com/lithammer/fuzzysearch/fuzzy
package main
import "github.com/lithammer/fuzzysearch/fuzzy"
func main() {
fuzzy.Match("twl", "cartwheel") // true
fuzzy.Match("cart", "cartwheel") // true
fuzzy.Match("cw", "cartwheel") // true
fuzzy.Match("ee", "cartwheel") // true
fuzzy.Match("art", "cartwheel") // true
fuzzy.Match("eeel", "cartwheel") // false
fuzzy.Match("dog", "cartwheel") // false
fuzzy.Match("kitten", "sitting") // false
fuzzy.RankMatch("kitten", "sitting") // -1
fuzzy.RankMatch("cart", "cartwheel") // 5
words := []string{"cartwheel", "foobar", "wheel", "baz"}
fuzzy.Find("whl", words) // [cartwheel wheel]
fuzzy.RankFind("whl", words) // [{whl cartwheel 6 0} {whl wheel 2 2}]
// Unicode normalized matching.
fuzzy.MatchNormalized("cartwheel", "cartwhéél") // true
// Case insensitive matching.
fuzzy.MatchFold("ArTeeL", "cartwheel") // true
}You can sort the result of a fuzzy.RankFind() call using the sort
package in the standard library:
matches := fuzzy.RankFind("whl", words) // [{whl cartwheel 6 0} {whl wheel 2 2}]
sort.Sort(matches) // [{whl wheel 2 2} {whl cartwheel 6 0}]See the fuzzy package documentation for more examples.
MIT