mirror of
https://github.com/Llewellynvdm/fzf.git
synced 2024-11-11 16:15:46 +00:00
426 lines
10 KiB
Go
426 lines
10 KiB
Go
package fzf
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import (
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"fmt"
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"regexp"
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"strings"
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"github.com/junegunn/fzf/src/algo"
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"github.com/junegunn/fzf/src/util"
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)
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// fuzzy
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// 'exact
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// ^prefix-exact
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// suffix-exact$
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// !inverse-exact
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// !'inverse-fuzzy
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// !^inverse-prefix-exact
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// !inverse-suffix-exact$
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type termType int
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const (
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termFuzzy termType = iota
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termExact
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termPrefix
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termSuffix
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termEqual
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)
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type term struct {
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typ termType
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inv bool
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text []rune
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caseSensitive bool
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normalize bool
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}
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// String returns the string representation of a term.
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func (t term) String() string {
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return fmt.Sprintf("term{typ: %d, inv: %v, text: []rune(%q), caseSensitive: %v}", t.typ, t.inv, string(t.text), t.caseSensitive)
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}
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type termSet []term
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// Pattern represents search pattern
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type Pattern struct {
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fuzzy bool
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fuzzyAlgo algo.Algo
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extended bool
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caseSensitive bool
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normalize bool
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forward bool
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text []rune
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termSets []termSet
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sortable bool
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cacheable bool
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cacheKey string
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delimiter Delimiter
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nth []Range
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procFun map[termType]algo.Algo
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}
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var (
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_patternCache map[string]*Pattern
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_splitRegex *regexp.Regexp
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_cache ChunkCache
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)
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func init() {
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_splitRegex = regexp.MustCompile(" +")
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clearPatternCache()
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clearChunkCache()
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}
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func clearPatternCache() {
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// We can uniquely identify the pattern for a given string since
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// search mode and caseMode do not change while the program is running
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_patternCache = make(map[string]*Pattern)
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}
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func clearChunkCache() {
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_cache = NewChunkCache()
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}
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// BuildPattern builds Pattern object from the given arguments
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func BuildPattern(fuzzy bool, fuzzyAlgo algo.Algo, extended bool, caseMode Case, normalize bool, forward bool,
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cacheable bool, nth []Range, delimiter Delimiter, runes []rune) *Pattern {
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var asString string
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if extended {
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asString = strings.TrimLeft(string(runes), " ")
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for strings.HasSuffix(asString, " ") && !strings.HasSuffix(asString, "\\ ") {
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asString = asString[:len(asString)-1]
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}
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} else {
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asString = string(runes)
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}
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cached, found := _patternCache[asString]
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if found {
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return cached
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}
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caseSensitive := true
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sortable := true
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termSets := []termSet{}
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if extended {
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termSets = parseTerms(fuzzy, caseMode, normalize, asString)
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// We should not sort the result if there are only inverse search terms
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sortable = false
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Loop:
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for _, termSet := range termSets {
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for idx, term := range termSet {
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if !term.inv {
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sortable = true
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}
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// If the query contains inverse search terms or OR operators,
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// we cannot cache the search scope
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if !cacheable || idx > 0 || term.inv || fuzzy && term.typ != termFuzzy || !fuzzy && term.typ != termExact {
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cacheable = false
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if sortable {
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// Can't break until we see at least one non-inverse term
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break Loop
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}
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}
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}
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}
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} else {
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lowerString := strings.ToLower(asString)
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normalize = normalize &&
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lowerString == string(algo.NormalizeRunes([]rune(lowerString)))
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caseSensitive = caseMode == CaseRespect ||
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caseMode == CaseSmart && lowerString != asString
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if !caseSensitive {
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asString = lowerString
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}
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}
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ptr := &Pattern{
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fuzzy: fuzzy,
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fuzzyAlgo: fuzzyAlgo,
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extended: extended,
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caseSensitive: caseSensitive,
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normalize: normalize,
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forward: forward,
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text: []rune(asString),
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termSets: termSets,
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sortable: sortable,
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cacheable: cacheable,
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nth: nth,
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delimiter: delimiter,
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procFun: make(map[termType]algo.Algo)}
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ptr.cacheKey = ptr.buildCacheKey()
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ptr.procFun[termFuzzy] = fuzzyAlgo
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ptr.procFun[termEqual] = algo.EqualMatch
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ptr.procFun[termExact] = algo.ExactMatchNaive
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ptr.procFun[termPrefix] = algo.PrefixMatch
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ptr.procFun[termSuffix] = algo.SuffixMatch
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_patternCache[asString] = ptr
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return ptr
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}
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func parseTerms(fuzzy bool, caseMode Case, normalize bool, str string) []termSet {
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str = strings.Replace(str, "\\ ", "\t", -1)
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tokens := _splitRegex.Split(str, -1)
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sets := []termSet{}
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set := termSet{}
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switchSet := false
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afterBar := false
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for _, token := range tokens {
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typ, inv, text := termFuzzy, false, strings.Replace(token, "\t", " ", -1)
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lowerText := strings.ToLower(text)
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caseSensitive := caseMode == CaseRespect ||
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caseMode == CaseSmart && text != lowerText
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normalizeTerm := normalize &&
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lowerText == string(algo.NormalizeRunes([]rune(lowerText)))
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if !caseSensitive {
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text = lowerText
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}
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if !fuzzy {
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typ = termExact
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}
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if len(set) > 0 && !afterBar && text == "|" {
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switchSet = false
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afterBar = true
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continue
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}
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afterBar = false
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if strings.HasPrefix(text, "!") {
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inv = true
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typ = termExact
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text = text[1:]
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}
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if text != "$" && strings.HasSuffix(text, "$") {
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typ = termSuffix
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text = text[:len(text)-1]
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}
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if strings.HasPrefix(text, "'") {
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// Flip exactness
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if fuzzy && !inv {
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typ = termExact
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text = text[1:]
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} else {
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typ = termFuzzy
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text = text[1:]
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}
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} else if strings.HasPrefix(text, "^") {
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if typ == termSuffix {
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typ = termEqual
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} else {
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typ = termPrefix
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}
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text = text[1:]
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}
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if len(text) > 0 {
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if switchSet {
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sets = append(sets, set)
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set = termSet{}
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}
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textRunes := []rune(text)
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if normalizeTerm {
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textRunes = algo.NormalizeRunes(textRunes)
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}
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set = append(set, term{
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typ: typ,
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inv: inv,
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text: textRunes,
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caseSensitive: caseSensitive,
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normalize: normalizeTerm})
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switchSet = true
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}
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}
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if len(set) > 0 {
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sets = append(sets, set)
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}
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return sets
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}
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// IsEmpty returns true if the pattern is effectively empty
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func (p *Pattern) IsEmpty() bool {
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if !p.extended {
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return len(p.text) == 0
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}
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return len(p.termSets) == 0
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}
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// AsString returns the search query in string type
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func (p *Pattern) AsString() string {
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return string(p.text)
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}
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func (p *Pattern) buildCacheKey() string {
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if !p.extended {
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return p.AsString()
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}
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cacheableTerms := []string{}
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for _, termSet := range p.termSets {
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if len(termSet) == 1 && !termSet[0].inv && (p.fuzzy || termSet[0].typ == termExact) {
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cacheableTerms = append(cacheableTerms, string(termSet[0].text))
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}
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}
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return strings.Join(cacheableTerms, "\t")
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}
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// CacheKey is used to build string to be used as the key of result cache
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func (p *Pattern) CacheKey() string {
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return p.cacheKey
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}
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// Match returns the list of matches Items in the given Chunk
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func (p *Pattern) Match(chunk *Chunk, slab *util.Slab) []Result {
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// ChunkCache: Exact match
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cacheKey := p.CacheKey()
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if p.cacheable {
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if cached := _cache.Lookup(chunk, cacheKey); cached != nil {
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return cached
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}
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}
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// Prefix/suffix cache
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space := _cache.Search(chunk, cacheKey)
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matches := p.matchChunk(chunk, space, slab)
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if p.cacheable {
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_cache.Add(chunk, cacheKey, matches)
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}
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return matches
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}
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func (p *Pattern) matchChunk(chunk *Chunk, space []Result, slab *util.Slab) []Result {
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matches := []Result{}
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if space == nil {
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for idx := 0; idx < chunk.count; idx++ {
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if match, _, _ := p.MatchItem(&chunk.items[idx], false, slab); match != nil {
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matches = append(matches, *match)
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}
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}
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} else {
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for _, result := range space {
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if match, _, _ := p.MatchItem(result.item, false, slab); match != nil {
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matches = append(matches, *match)
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}
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}
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}
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return matches
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}
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// MatchItem returns true if the Item is a match
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func (p *Pattern) MatchItem(item *Item, withPos bool, slab *util.Slab) (*Result, []Offset, *[]int) {
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if p.extended {
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if offsets, bonus, pos := p.extendedMatch(item, withPos, slab); len(offsets) == len(p.termSets) {
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result := buildResult(item, offsets, bonus)
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return &result, offsets, pos
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}
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return nil, nil, nil
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}
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offset, bonus, pos := p.basicMatch(item, withPos, slab)
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if sidx := offset[0]; sidx >= 0 {
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offsets := []Offset{offset}
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result := buildResult(item, offsets, bonus)
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return &result, offsets, pos
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}
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return nil, nil, nil
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}
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func (p *Pattern) basicMatch(item *Item, withPos bool, slab *util.Slab) (Offset, int, *[]int) {
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var input []Token
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if len(p.nth) == 0 {
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input = []Token{{text: &item.text, prefixLength: 0}}
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} else {
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input = p.transformInput(item)
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}
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if p.fuzzy {
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return p.iter(p.fuzzyAlgo, input, p.caseSensitive, p.normalize, p.forward, p.text, withPos, slab)
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}
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return p.iter(algo.ExactMatchNaive, input, p.caseSensitive, p.normalize, p.forward, p.text, withPos, slab)
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}
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func (p *Pattern) extendedMatch(item *Item, withPos bool, slab *util.Slab) ([]Offset, int, *[]int) {
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var input []Token
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if len(p.nth) == 0 {
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input = []Token{{text: &item.text, prefixLength: 0}}
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} else {
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input = p.transformInput(item)
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}
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offsets := []Offset{}
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var totalScore int
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var allPos *[]int
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if withPos {
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allPos = &[]int{}
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}
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for _, termSet := range p.termSets {
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var offset Offset
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var currentScore int
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matched := false
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for _, term := range termSet {
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pfun := p.procFun[term.typ]
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off, score, pos := p.iter(pfun, input, term.caseSensitive, term.normalize, p.forward, term.text, withPos, slab)
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if sidx := off[0]; sidx >= 0 {
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if term.inv {
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continue
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}
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offset, currentScore = off, score
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matched = true
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if withPos {
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if pos != nil {
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*allPos = append(*allPos, *pos...)
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} else {
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for idx := off[0]; idx < off[1]; idx++ {
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*allPos = append(*allPos, int(idx))
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}
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}
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}
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break
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} else if term.inv {
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offset, currentScore = Offset{0, 0}, 0
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matched = true
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continue
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}
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}
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if matched {
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offsets = append(offsets, offset)
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totalScore += currentScore
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}
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}
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return offsets, totalScore, allPos
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}
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func (p *Pattern) transformInput(item *Item) []Token {
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if item.transformed != nil {
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return *item.transformed
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}
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tokens := Tokenize(item.text.ToString(), p.delimiter)
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ret := Transform(tokens, p.nth)
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item.transformed = &ret
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return ret
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}
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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) {
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for _, part := range tokens {
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if res, pos := pfun(caseSensitive, normalize, forward, part.text, pattern, withPos, slab); res.Start >= 0 {
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sidx := int32(res.Start) + part.prefixLength
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eidx := int32(res.End) + part.prefixLength
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if pos != nil {
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for idx := range *pos {
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(*pos)[idx] += int(part.prefixLength)
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}
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}
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return Offset{sidx, eidx}, res.Score, pos
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}
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}
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return Offset{-1, -1}, 0, nil
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}
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