fzf/src/pattern.go
2022-08-03 22:18:26 +09:00

428 lines
10 KiB
Go

package fzf
import (
"fmt"
"regexp"
"strings"
"github.com/junegunn/fzf/src/algo"
"github.com/junegunn/fzf/src/util"
)
// fuzzy
// 'exact
// ^prefix-exact
// suffix-exact$
// !inverse-exact
// !'inverse-fuzzy
// !^inverse-prefix-exact
// !inverse-suffix-exact$
type termType int
const (
termFuzzy termType = iota
termExact
termPrefix
termSuffix
termEqual
)
type term struct {
typ termType
inv bool
text []rune
caseSensitive bool
normalize bool
}
// String returns the string representation of a term.
func (t term) String() string {
return fmt.Sprintf("term{typ: %d, inv: %v, text: []rune(%q), caseSensitive: %v}", t.typ, t.inv, string(t.text), t.caseSensitive)
}
type termSet []term
// Pattern represents search pattern
type Pattern struct {
fuzzy bool
fuzzyAlgo algo.Algo
extended bool
caseSensitive bool
normalize bool
forward bool
withPos bool
text []rune
termSets []termSet
sortable bool
cacheable bool
cacheKey string
delimiter Delimiter
nth []Range
procFun map[termType]algo.Algo
}
var (
_patternCache map[string]*Pattern
_splitRegex *regexp.Regexp
_cache ChunkCache
)
func init() {
_splitRegex = regexp.MustCompile(" +")
clearPatternCache()
clearChunkCache()
}
func clearPatternCache() {
// We can uniquely identify the pattern for a given string since
// search mode and caseMode do not change while the program is running
_patternCache = make(map[string]*Pattern)
}
func clearChunkCache() {
_cache = NewChunkCache()
}
// BuildPattern builds Pattern object from the given arguments
func BuildPattern(fuzzy bool, fuzzyAlgo algo.Algo, extended bool, caseMode Case, normalize bool, forward bool,
withPos bool, cacheable bool, nth []Range, delimiter Delimiter, runes []rune) *Pattern {
var asString string
if extended {
asString = strings.TrimLeft(string(runes), " ")
for strings.HasSuffix(asString, " ") && !strings.HasSuffix(asString, "\\ ") {
asString = asString[:len(asString)-1]
}
} else {
asString = string(runes)
}
cached, found := _patternCache[asString]
if found {
return cached
}
caseSensitive := true
sortable := true
termSets := []termSet{}
if extended {
termSets = parseTerms(fuzzy, caseMode, normalize, asString)
// We should not sort the result if there are only inverse search terms
sortable = false
Loop:
for _, termSet := range termSets {
for idx, term := range termSet {
if !term.inv {
sortable = true
}
// If the query contains inverse search terms or OR operators,
// we cannot cache the search scope
if !cacheable || idx > 0 || term.inv || fuzzy && term.typ != termFuzzy || !fuzzy && term.typ != termExact {
cacheable = false
if sortable {
// Can't break until we see at least one non-inverse term
break Loop
}
}
}
}
} else {
lowerString := strings.ToLower(asString)
normalize = normalize &&
lowerString == string(algo.NormalizeRunes([]rune(lowerString)))
caseSensitive = caseMode == CaseRespect ||
caseMode == CaseSmart && lowerString != asString
if !caseSensitive {
asString = lowerString
}
}
ptr := &Pattern{
fuzzy: fuzzy,
fuzzyAlgo: fuzzyAlgo,
extended: extended,
caseSensitive: caseSensitive,
normalize: normalize,
forward: forward,
withPos: withPos,
text: []rune(asString),
termSets: termSets,
sortable: sortable,
cacheable: cacheable,
nth: nth,
delimiter: delimiter,
procFun: make(map[termType]algo.Algo)}
ptr.cacheKey = ptr.buildCacheKey()
ptr.procFun[termFuzzy] = fuzzyAlgo
ptr.procFun[termEqual] = algo.EqualMatch
ptr.procFun[termExact] = algo.ExactMatchNaive
ptr.procFun[termPrefix] = algo.PrefixMatch
ptr.procFun[termSuffix] = algo.SuffixMatch
_patternCache[asString] = ptr
return ptr
}
func parseTerms(fuzzy bool, caseMode Case, normalize bool, str string) []termSet {
str = strings.Replace(str, "\\ ", "\t", -1)
tokens := _splitRegex.Split(str, -1)
sets := []termSet{}
set := termSet{}
switchSet := false
afterBar := false
for _, token := range tokens {
typ, inv, text := termFuzzy, false, strings.Replace(token, "\t", " ", -1)
lowerText := strings.ToLower(text)
caseSensitive := caseMode == CaseRespect ||
caseMode == CaseSmart && text != lowerText
normalizeTerm := normalize &&
lowerText == string(algo.NormalizeRunes([]rune(lowerText)))
if !caseSensitive {
text = lowerText
}
if !fuzzy {
typ = termExact
}
if len(set) > 0 && !afterBar && text == "|" {
switchSet = false
afterBar = true
continue
}
afterBar = false
if strings.HasPrefix(text, "!") {
inv = true
typ = termExact
text = text[1:]
}
if text != "$" && strings.HasSuffix(text, "$") {
typ = termSuffix
text = text[:len(text)-1]
}
if strings.HasPrefix(text, "'") {
// Flip exactness
if fuzzy && !inv {
typ = termExact
text = text[1:]
} else {
typ = termFuzzy
text = text[1:]
}
} else if strings.HasPrefix(text, "^") {
if typ == termSuffix {
typ = termEqual
} else {
typ = termPrefix
}
text = text[1:]
}
if len(text) > 0 {
if switchSet {
sets = append(sets, set)
set = termSet{}
}
textRunes := []rune(text)
if normalizeTerm {
textRunes = algo.NormalizeRunes(textRunes)
}
set = append(set, term{
typ: typ,
inv: inv,
text: textRunes,
caseSensitive: caseSensitive,
normalize: normalizeTerm})
switchSet = true
}
}
if len(set) > 0 {
sets = append(sets, set)
}
return sets
}
// IsEmpty returns true if the pattern is effectively empty
func (p *Pattern) IsEmpty() bool {
if !p.extended {
return len(p.text) == 0
}
return len(p.termSets) == 0
}
// AsString returns the search query in string type
func (p *Pattern) AsString() string {
return string(p.text)
}
func (p *Pattern) buildCacheKey() string {
if !p.extended {
return p.AsString()
}
cacheableTerms := []string{}
for _, termSet := range p.termSets {
if len(termSet) == 1 && !termSet[0].inv && (p.fuzzy || termSet[0].typ == termExact) {
cacheableTerms = append(cacheableTerms, string(termSet[0].text))
}
}
return strings.Join(cacheableTerms, "\t")
}
// CacheKey is used to build string to be used as the key of result cache
func (p *Pattern) CacheKey() string {
return p.cacheKey
}
// Match returns the list of matches Items in the given Chunk
func (p *Pattern) Match(chunk *Chunk, slab *util.Slab) []Result {
// ChunkCache: Exact match
cacheKey := p.CacheKey()
if p.cacheable {
if cached := _cache.Lookup(chunk, cacheKey); cached != nil {
return cached
}
}
// Prefix/suffix cache
space := _cache.Search(chunk, cacheKey)
matches := p.matchChunk(chunk, space, slab)
if p.cacheable {
_cache.Add(chunk, cacheKey, matches)
}
return matches
}
func (p *Pattern) matchChunk(chunk *Chunk, space []Result, slab *util.Slab) []Result {
matches := []Result{}
if space == nil {
for idx := 0; idx < chunk.count; idx++ {
if match, _, _ := p.MatchItem(&chunk.items[idx], p.withPos, slab); match != nil {
matches = append(matches, *match)
}
}
} else {
for _, result := range space {
if match, _, _ := p.MatchItem(result.item, p.withPos, slab); match != nil {
matches = append(matches, *match)
}
}
}
return matches
}
// MatchItem returns true if the Item is a match
func (p *Pattern) MatchItem(item *Item, withPos bool, slab *util.Slab) (*Result, []Offset, *[]int) {
if p.extended {
if offsets, bonus, pos := p.extendedMatch(item, withPos, slab); len(offsets) == len(p.termSets) {
result := buildResult(item, offsets, bonus)
return &result, offsets, pos
}
return nil, nil, nil
}
offset, bonus, pos := p.basicMatch(item, withPos, slab)
if sidx := offset[0]; sidx >= 0 {
offsets := []Offset{offset}
result := buildResult(item, offsets, bonus)
return &result, offsets, pos
}
return nil, nil, nil
}
func (p *Pattern) basicMatch(item *Item, withPos bool, slab *util.Slab) (Offset, int, *[]int) {
var input []Token
if len(p.nth) == 0 {
input = []Token{{text: &item.text, prefixLength: 0}}
} else {
input = p.transformInput(item)
}
if p.fuzzy {
return p.iter(p.fuzzyAlgo, input, p.caseSensitive, p.normalize, p.forward, p.text, withPos, slab)
}
return p.iter(algo.ExactMatchNaive, input, p.caseSensitive, p.normalize, p.forward, p.text, withPos, slab)
}
func (p *Pattern) extendedMatch(item *Item, withPos bool, slab *util.Slab) ([]Offset, int, *[]int) {
var input []Token
if len(p.nth) == 0 {
input = []Token{{text: &item.text, prefixLength: 0}}
} else {
input = p.transformInput(item)
}
offsets := []Offset{}
var totalScore int
var allPos *[]int
if withPos {
allPos = &[]int{}
}
for _, termSet := range p.termSets {
var offset Offset
var currentScore int
matched := false
for _, term := range termSet {
pfun := p.procFun[term.typ]
off, score, pos := p.iter(pfun, input, term.caseSensitive, term.normalize, p.forward, term.text, withPos, slab)
if sidx := off[0]; sidx >= 0 {
if term.inv {
continue
}
offset, currentScore = off, score
matched = true
if withPos {
if pos != nil {
*allPos = append(*allPos, *pos...)
} else {
for idx := off[0]; idx < off[1]; idx++ {
*allPos = append(*allPos, int(idx))
}
}
}
break
} else if term.inv {
offset, currentScore = Offset{0, 0}, 0
matched = true
continue
}
}
if matched {
offsets = append(offsets, offset)
totalScore += currentScore
}
}
return offsets, totalScore, allPos
}
func (p *Pattern) transformInput(item *Item) []Token {
if item.transformed != nil {
return *item.transformed
}
tokens := Tokenize(item.text.ToString(), p.delimiter)
ret := Transform(tokens, p.nth)
item.transformed = &ret
return ret
}
func (p *Pattern) iter(pfun algo.Algo, tokens []Token, caseSensitive bool, normalize bool, forward bool, pattern []rune, withPos bool, slab *util.Slab) (Offset, int, *[]int) {
for _, part := range tokens {
if res, pos := pfun(caseSensitive, normalize, forward, part.text, pattern, withPos, slab); res.Start >= 0 {
sidx := int32(res.Start) + part.prefixLength
eidx := int32(res.End) + part.prefixLength
if pos != nil {
for idx := range *pos {
(*pos)[idx] += int(part.prefixLength)
}
}
return Offset{sidx, eidx}, res.Score, pos
}
}
return Offset{-1, -1}, 0, nil
}