gomuks/vendor/github.com/renstrom/fuzzysearch/fuzzy/fuzzy.go
2018-05-23 10:21:08 -05:00

177 lines
4.1 KiB
Go

// Fuzzy searching allows for flexibly matching a string with partial input,
// useful for filtering data very quickly based on lightweight user input.
package fuzzy
import (
"unicode"
"unicode/utf8"
)
var noop = func(r rune) rune { return r }
// Match returns true if source matches target using a fuzzy-searching
// algorithm. Note that it doesn't implement Levenshtein distance (see
// RankMatch instead), but rather a simplified version where there's no
// approximation. The method will return true only if each character in the
// source can be found in the target and occurs after the preceding matches.
func Match(source, target string) bool {
return match(source, target, noop)
}
// MatchFold is a case-insensitive version of Match.
func MatchFold(source, target string) bool {
return match(source, target, unicode.ToLower)
}
func match(source, target string, fn func(rune) rune) bool {
lenDiff := len(target) - len(source)
if lenDiff < 0 {
return false
}
if lenDiff == 0 && source == target {
return true
}
Outer:
for _, r1 := range source {
for i, r2 := range target {
if fn(r1) == fn(r2) {
target = target[i+utf8.RuneLen(r2):]
continue Outer
}
}
return false
}
return true
}
// Find will return a list of strings in targets that fuzzy matches source.
func Find(source string, targets []string) []string {
return find(source, targets, noop)
}
// FindFold is a case-insensitive version of Find.
func FindFold(source string, targets []string) []string {
return find(source, targets, unicode.ToLower)
}
func find(source string, targets []string, fn func(rune) rune) []string {
var matches []string
for _, target := range targets {
if match(source, target, fn) {
matches = append(matches, target)
}
}
return matches
}
// RankMatch is similar to Match except it will measure the Levenshtein
// distance between the source and the target and return its result. If there
// was no match, it will return -1.
// Given the requirements of match, RankMatch only needs to perform a subset of
// the Levenshtein calculation, only deletions need be considered, required
// additions and substitutions would fail the match test.
func RankMatch(source, target string) int {
return rank(source, target, noop)
}
// RankMatchFold is a case-insensitive version of RankMatch.
func RankMatchFold(source, target string) int {
return rank(source, target, unicode.ToLower)
}
func rank(source, target string, fn func(rune) rune) int {
lenDiff := len(target) - len(source)
if lenDiff < 0 {
return -1
}
if lenDiff == 0 && source == target {
return 0
}
runeDiff := 0
Outer:
for _, r1 := range source {
for i, r2 := range target {
if fn(r1) == fn(r2) {
target = target[i+utf8.RuneLen(r2):]
continue Outer
} else {
runeDiff++
}
}
return -1
}
// Count up remaining char
for len(target) > 0 {
target = target[utf8.RuneLen(rune(target[0])):]
runeDiff++
}
return runeDiff
}
// RankFind is similar to Find, except it will also rank all matches using
// Levenshtein distance.
func RankFind(source string, targets []string) Ranks {
var r Ranks
for index, target := range targets {
if match(source, target, noop) {
distance := LevenshteinDistance(source, target)
r = append(r, Rank{source, target, distance, index})
}
}
return r
}
// RankFindFold is a case-insensitive version of RankFind.
func RankFindFold(source string, targets []string) Ranks {
var r Ranks
for index, target := range targets {
if match(source, target, unicode.ToLower) {
distance := LevenshteinDistance(source, target)
r = append(r, Rank{source, target, distance, index})
}
}
return r
}
type Rank struct {
// Source is used as the source for matching.
Source string
// Target is the word matched against.
Target string
// Distance is the Levenshtein distance between Source and Target.
Distance int
// Location of Target in original list
OriginalIndex int
}
type Ranks []Rank
func (r Ranks) Len() int {
return len(r)
}
func (r Ranks) Swap(i, j int) {
r[i], r[j] = r[j], r[i]
}
func (r Ranks) Less(i, j int) bool {
return r[i].Distance < r[j].Distance
}