William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 1 | // Copyright 2013 The Go Authors. All rights reserved. |
| 2 | // Use of this source code is governed by a BSD-style |
| 3 | // license that can be found in the LICENSE file. |
| 4 | |
| 5 | package language |
| 6 | |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 7 | import ( |
| 8 | "errors" |
| 9 | "strings" |
| 10 | |
| 11 | "golang.org/x/text/internal/language" |
| 12 | ) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 13 | |
| 14 | // A MatchOption configures a Matcher. |
| 15 | type MatchOption func(*matcher) |
| 16 | |
| 17 | // PreferSameScript will, in the absence of a match, result in the first |
| 18 | // preferred tag with the same script as a supported tag to match this supported |
| 19 | // tag. The default is currently true, but this may change in the future. |
| 20 | func PreferSameScript(preferSame bool) MatchOption { |
| 21 | return func(m *matcher) { m.preferSameScript = preferSame } |
| 22 | } |
| 23 | |
| 24 | // TODO(v1.0.0): consider making Matcher a concrete type, instead of interface. |
| 25 | // There doesn't seem to be too much need for multiple types. |
| 26 | // Making it a concrete type allows MatchStrings to be a method, which will |
| 27 | // improve its discoverability. |
| 28 | |
| 29 | // MatchStrings parses and matches the given strings until one of them matches |
| 30 | // the language in the Matcher. A string may be an Accept-Language header as |
| 31 | // handled by ParseAcceptLanguage. The default language is returned if no |
| 32 | // other language matched. |
| 33 | func MatchStrings(m Matcher, lang ...string) (tag Tag, index int) { |
| 34 | for _, accept := range lang { |
| 35 | desired, _, err := ParseAcceptLanguage(accept) |
| 36 | if err != nil { |
| 37 | continue |
| 38 | } |
| 39 | if tag, index, conf := m.Match(desired...); conf != No { |
| 40 | return tag, index |
| 41 | } |
| 42 | } |
| 43 | tag, index, _ = m.Match() |
| 44 | return |
| 45 | } |
| 46 | |
| 47 | // Matcher is the interface that wraps the Match method. |
| 48 | // |
| 49 | // Match returns the best match for any of the given tags, along with |
| 50 | // a unique index associated with the returned tag and a confidence |
| 51 | // score. |
| 52 | type Matcher interface { |
| 53 | Match(t ...Tag) (tag Tag, index int, c Confidence) |
| 54 | } |
| 55 | |
| 56 | // Comprehends reports the confidence score for a speaker of a given language |
| 57 | // to being able to comprehend the written form of an alternative language. |
| 58 | func Comprehends(speaker, alternative Tag) Confidence { |
| 59 | _, _, c := NewMatcher([]Tag{alternative}).Match(speaker) |
| 60 | return c |
| 61 | } |
| 62 | |
| 63 | // NewMatcher returns a Matcher that matches an ordered list of preferred tags |
| 64 | // against a list of supported tags based on written intelligibility, closeness |
| 65 | // of dialect, equivalence of subtags and various other rules. It is initialized |
| 66 | // with the list of supported tags. The first element is used as the default |
| 67 | // value in case no match is found. |
| 68 | // |
| 69 | // Its Match method matches the first of the given Tags to reach a certain |
| 70 | // confidence threshold. The tags passed to Match should therefore be specified |
| 71 | // in order of preference. Extensions are ignored for matching. |
| 72 | // |
| 73 | // The index returned by the Match method corresponds to the index of the |
| 74 | // matched tag in t, but is augmented with the Unicode extension ('u')of the |
| 75 | // corresponding preferred tag. This allows user locale options to be passed |
| 76 | // transparently. |
| 77 | func NewMatcher(t []Tag, options ...MatchOption) Matcher { |
| 78 | return newMatcher(t, options) |
| 79 | } |
| 80 | |
| 81 | func (m *matcher) Match(want ...Tag) (t Tag, index int, c Confidence) { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 82 | var tt language.Tag |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 83 | match, w, c := m.getBest(want...) |
| 84 | if match != nil { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 85 | tt, index = match.tag, match.index |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 86 | } else { |
| 87 | // TODO: this should be an option |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 88 | tt = m.default_.tag |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 89 | if m.preferSameScript { |
| 90 | outer: |
| 91 | for _, w := range want { |
| 92 | script, _ := w.Script() |
| 93 | if script.scriptID == 0 { |
| 94 | // Don't do anything if there is no script, such as with |
| 95 | // private subtags. |
| 96 | continue |
| 97 | } |
| 98 | for i, h := range m.supported { |
| 99 | if script.scriptID == h.maxScript { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 100 | tt, index = h.tag, i |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 101 | break outer |
| 102 | } |
| 103 | } |
| 104 | } |
| 105 | } |
| 106 | // TODO: select first language tag based on script. |
| 107 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 108 | if w.RegionID != tt.RegionID && w.RegionID != 0 { |
| 109 | if w.RegionID != 0 && tt.RegionID != 0 && tt.RegionID.Contains(w.RegionID) { |
| 110 | tt.RegionID = w.RegionID |
| 111 | tt.RemakeString() |
| 112 | } else if r := w.RegionID.String(); len(r) == 2 { |
| 113 | // TODO: also filter macro and deprecated. |
| 114 | tt, _ = tt.SetTypeForKey("rg", strings.ToLower(r)+"zzzz") |
| 115 | } |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 116 | } |
| 117 | // Copy options from the user-provided tag into the result tag. This is hard |
| 118 | // to do after the fact, so we do it here. |
| 119 | // TODO: add in alternative variants to -u-va-. |
| 120 | // TODO: add preferred region to -u-rg-. |
| 121 | if e := w.Extensions(); len(e) > 0 { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 122 | b := language.Builder{} |
| 123 | b.SetTag(tt) |
| 124 | for _, e := range e { |
| 125 | b.AddExt(e) |
| 126 | } |
| 127 | tt = b.Make() |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 128 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 129 | return makeTag(tt), index, c |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 130 | } |
| 131 | |
| 132 | // ErrMissingLikelyTagsData indicates no information was available |
| 133 | // to compute likely values of missing tags. |
| 134 | var ErrMissingLikelyTagsData = errors.New("missing likely tags data") |
| 135 | |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 136 | // func (t *Tag) setTagsFrom(id Tag) { |
| 137 | // t.LangID = id.LangID |
| 138 | // t.ScriptID = id.ScriptID |
| 139 | // t.RegionID = id.RegionID |
| 140 | // } |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 141 | |
| 142 | // Tag Matching |
| 143 | // CLDR defines an algorithm for finding the best match between two sets of language |
| 144 | // tags. The basic algorithm defines how to score a possible match and then find |
| 145 | // the match with the best score |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 146 | // (see https://www.unicode.org/reports/tr35/#LanguageMatching). |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 147 | // Using scoring has several disadvantages. The scoring obfuscates the importance of |
| 148 | // the various factors considered, making the algorithm harder to understand. Using |
| 149 | // scoring also requires the full score to be computed for each pair of tags. |
| 150 | // |
| 151 | // We will use a different algorithm which aims to have the following properties: |
| 152 | // - clarity on the precedence of the various selection factors, and |
| 153 | // - improved performance by allowing early termination of a comparison. |
| 154 | // |
| 155 | // Matching algorithm (overview) |
| 156 | // Input: |
| 157 | // - supported: a set of supported tags |
| 158 | // - default: the default tag to return in case there is no match |
| 159 | // - desired: list of desired tags, ordered by preference, starting with |
| 160 | // the most-preferred. |
| 161 | // |
| 162 | // Algorithm: |
| 163 | // 1) Set the best match to the lowest confidence level |
| 164 | // 2) For each tag in "desired": |
| 165 | // a) For each tag in "supported": |
| 166 | // 1) compute the match between the two tags. |
| 167 | // 2) if the match is better than the previous best match, replace it |
| 168 | // with the new match. (see next section) |
| 169 | // b) if the current best match is Exact and pin is true the result will be |
| 170 | // frozen to the language found thusfar, although better matches may |
| 171 | // still be found for the same language. |
| 172 | // 3) If the best match so far is below a certain threshold, return "default". |
| 173 | // |
| 174 | // Ranking: |
| 175 | // We use two phases to determine whether one pair of tags are a better match |
| 176 | // than another pair of tags. First, we determine a rough confidence level. If the |
| 177 | // levels are different, the one with the highest confidence wins. |
| 178 | // Second, if the rough confidence levels are identical, we use a set of tie-breaker |
| 179 | // rules. |
| 180 | // |
| 181 | // The confidence level of matching a pair of tags is determined by finding the |
| 182 | // lowest confidence level of any matches of the corresponding subtags (the |
| 183 | // result is deemed as good as its weakest link). |
| 184 | // We define the following levels: |
| 185 | // Exact - An exact match of a subtag, before adding likely subtags. |
| 186 | // MaxExact - An exact match of a subtag, after adding likely subtags. |
| 187 | // [See Note 2]. |
| 188 | // High - High level of mutual intelligibility between different subtag |
| 189 | // variants. |
| 190 | // Low - Low level of mutual intelligibility between different subtag |
| 191 | // variants. |
| 192 | // No - No mutual intelligibility. |
| 193 | // |
| 194 | // The following levels can occur for each type of subtag: |
| 195 | // Base: Exact, MaxExact, High, Low, No |
| 196 | // Script: Exact, MaxExact [see Note 3], Low, No |
| 197 | // Region: Exact, MaxExact, High |
| 198 | // Variant: Exact, High |
| 199 | // Private: Exact, No |
| 200 | // |
| 201 | // Any result with a confidence level of Low or higher is deemed a possible match. |
| 202 | // Once a desired tag matches any of the supported tags with a level of MaxExact |
| 203 | // or higher, the next desired tag is not considered (see Step 2.b). |
| 204 | // Note that CLDR provides languageMatching data that defines close equivalence |
| 205 | // classes for base languages, scripts and regions. |
| 206 | // |
| 207 | // Tie-breaking |
| 208 | // If we get the same confidence level for two matches, we apply a sequence of |
| 209 | // tie-breaking rules. The first that succeeds defines the result. The rules are |
| 210 | // applied in the following order. |
| 211 | // 1) Original language was defined and was identical. |
| 212 | // 2) Original region was defined and was identical. |
| 213 | // 3) Distance between two maximized regions was the smallest. |
| 214 | // 4) Original script was defined and was identical. |
| 215 | // 5) Distance from want tag to have tag using the parent relation [see Note 5.] |
| 216 | // If there is still no winner after these rules are applied, the first match |
| 217 | // found wins. |
| 218 | // |
| 219 | // Notes: |
| 220 | // [2] In practice, as matching of Exact is done in a separate phase from |
| 221 | // matching the other levels, we reuse the Exact level to mean MaxExact in |
| 222 | // the second phase. As a consequence, we only need the levels defined by |
| 223 | // the Confidence type. The MaxExact confidence level is mapped to High in |
| 224 | // the public API. |
| 225 | // [3] We do not differentiate between maximized script values that were derived |
| 226 | // from suppressScript versus most likely tag data. We determined that in |
| 227 | // ranking the two, one ranks just after the other. Moreover, the two cannot |
| 228 | // occur concurrently. As a consequence, they are identical for practical |
| 229 | // purposes. |
| 230 | // [4] In case of deprecated, macro-equivalents and legacy mappings, we assign |
| 231 | // the MaxExact level to allow iw vs he to still be a closer match than |
| 232 | // en-AU vs en-US, for example. |
| 233 | // [5] In CLDR a locale inherits fields that are unspecified for this locale |
| 234 | // from its parent. Therefore, if a locale is a parent of another locale, |
| 235 | // it is a strong measure for closeness, especially when no other tie |
| 236 | // breaker rule applies. One could also argue it is inconsistent, for |
| 237 | // example, when pt-AO matches pt (which CLDR equates with pt-BR), even |
| 238 | // though its parent is pt-PT according to the inheritance rules. |
| 239 | // |
| 240 | // Implementation Details: |
| 241 | // There are several performance considerations worth pointing out. Most notably, |
| 242 | // we preprocess as much as possible (within reason) at the time of creation of a |
| 243 | // matcher. This includes: |
| 244 | // - creating a per-language map, which includes data for the raw base language |
| 245 | // and its canonicalized variant (if applicable), |
| 246 | // - expanding entries for the equivalence classes defined in CLDR's |
| 247 | // languageMatch data. |
| 248 | // The per-language map ensures that typically only a very small number of tags |
| 249 | // need to be considered. The pre-expansion of canonicalized subtags and |
| 250 | // equivalence classes reduces the amount of map lookups that need to be done at |
| 251 | // runtime. |
| 252 | |
| 253 | // matcher keeps a set of supported language tags, indexed by language. |
| 254 | type matcher struct { |
| 255 | default_ *haveTag |
| 256 | supported []*haveTag |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 257 | index map[language.Language]*matchHeader |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 258 | passSettings bool |
| 259 | preferSameScript bool |
| 260 | } |
| 261 | |
| 262 | // matchHeader has the lists of tags for exact matches and matches based on |
| 263 | // maximized and canonicalized tags for a given language. |
| 264 | type matchHeader struct { |
| 265 | haveTags []*haveTag |
| 266 | original bool |
| 267 | } |
| 268 | |
| 269 | // haveTag holds a supported Tag and its maximized script and region. The maximized |
| 270 | // or canonicalized language is not stored as it is not needed during matching. |
| 271 | type haveTag struct { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 272 | tag language.Tag |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 273 | |
| 274 | // index of this tag in the original list of supported tags. |
| 275 | index int |
| 276 | |
| 277 | // conf is the maximum confidence that can result from matching this haveTag. |
| 278 | // When conf < Exact this means it was inserted after applying a CLDR equivalence rule. |
| 279 | conf Confidence |
| 280 | |
| 281 | // Maximized region and script. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 282 | maxRegion language.Region |
| 283 | maxScript language.Script |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 284 | |
| 285 | // altScript may be checked as an alternative match to maxScript. If altScript |
| 286 | // matches, the confidence level for this match is Low. Theoretically there |
| 287 | // could be multiple alternative scripts. This does not occur in practice. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 288 | altScript language.Script |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 289 | |
| 290 | // nextMax is the index of the next haveTag with the same maximized tags. |
| 291 | nextMax uint16 |
| 292 | } |
| 293 | |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 294 | func makeHaveTag(tag language.Tag, index int) (haveTag, language.Language) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 295 | max := tag |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 296 | if tag.LangID != 0 || tag.RegionID != 0 || tag.ScriptID != 0 { |
| 297 | max, _ = canonicalize(All, max) |
| 298 | max, _ = max.Maximize() |
| 299 | max.RemakeString() |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 300 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 301 | return haveTag{tag, index, Exact, max.RegionID, max.ScriptID, altScript(max.LangID, max.ScriptID), 0}, max.LangID |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 302 | } |
| 303 | |
| 304 | // altScript returns an alternative script that may match the given script with |
| 305 | // a low confidence. At the moment, the langMatch data allows for at most one |
| 306 | // script to map to another and we rely on this to keep the code simple. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 307 | func altScript(l language.Language, s language.Script) language.Script { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 308 | for _, alt := range matchScript { |
| 309 | // TODO: also match cases where language is not the same. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 310 | if (language.Language(alt.wantLang) == l || language.Language(alt.haveLang) == l) && |
| 311 | language.Script(alt.haveScript) == s { |
| 312 | return language.Script(alt.wantScript) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 313 | } |
| 314 | } |
| 315 | return 0 |
| 316 | } |
| 317 | |
| 318 | // addIfNew adds a haveTag to the list of tags only if it is a unique tag. |
| 319 | // Tags that have the same maximized values are linked by index. |
| 320 | func (h *matchHeader) addIfNew(n haveTag, exact bool) { |
| 321 | h.original = h.original || exact |
| 322 | // Don't add new exact matches. |
| 323 | for _, v := range h.haveTags { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 324 | if equalsRest(v.tag, n.tag) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 325 | return |
| 326 | } |
| 327 | } |
| 328 | // Allow duplicate maximized tags, but create a linked list to allow quickly |
| 329 | // comparing the equivalents and bail out. |
| 330 | for i, v := range h.haveTags { |
| 331 | if v.maxScript == n.maxScript && |
| 332 | v.maxRegion == n.maxRegion && |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 333 | v.tag.VariantOrPrivateUseTags() == n.tag.VariantOrPrivateUseTags() { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 334 | for h.haveTags[i].nextMax != 0 { |
| 335 | i = int(h.haveTags[i].nextMax) |
| 336 | } |
| 337 | h.haveTags[i].nextMax = uint16(len(h.haveTags)) |
| 338 | break |
| 339 | } |
| 340 | } |
| 341 | h.haveTags = append(h.haveTags, &n) |
| 342 | } |
| 343 | |
| 344 | // header returns the matchHeader for the given language. It creates one if |
| 345 | // it doesn't already exist. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 346 | func (m *matcher) header(l language.Language) *matchHeader { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 347 | if h := m.index[l]; h != nil { |
| 348 | return h |
| 349 | } |
| 350 | h := &matchHeader{} |
| 351 | m.index[l] = h |
| 352 | return h |
| 353 | } |
| 354 | |
| 355 | func toConf(d uint8) Confidence { |
| 356 | if d <= 10 { |
| 357 | return High |
| 358 | } |
| 359 | if d < 30 { |
| 360 | return Low |
| 361 | } |
| 362 | return No |
| 363 | } |
| 364 | |
| 365 | // newMatcher builds an index for the given supported tags and returns it as |
| 366 | // a matcher. It also expands the index by considering various equivalence classes |
| 367 | // for a given tag. |
| 368 | func newMatcher(supported []Tag, options []MatchOption) *matcher { |
| 369 | m := &matcher{ |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 370 | index: make(map[language.Language]*matchHeader), |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 371 | preferSameScript: true, |
| 372 | } |
| 373 | for _, o := range options { |
| 374 | o(m) |
| 375 | } |
| 376 | if len(supported) == 0 { |
| 377 | m.default_ = &haveTag{} |
| 378 | return m |
| 379 | } |
| 380 | // Add supported languages to the index. Add exact matches first to give |
| 381 | // them precedence. |
| 382 | for i, tag := range supported { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 383 | tt := tag.tag() |
| 384 | pair, _ := makeHaveTag(tt, i) |
| 385 | m.header(tt.LangID).addIfNew(pair, true) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 386 | m.supported = append(m.supported, &pair) |
| 387 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 388 | m.default_ = m.header(supported[0].lang()).haveTags[0] |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 389 | // Keep these in two different loops to support the case that two equivalent |
| 390 | // languages are distinguished, such as iw and he. |
| 391 | for i, tag := range supported { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 392 | tt := tag.tag() |
| 393 | pair, max := makeHaveTag(tt, i) |
| 394 | if max != tt.LangID { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 395 | m.header(max).addIfNew(pair, true) |
| 396 | } |
| 397 | } |
| 398 | |
| 399 | // update is used to add indexes in the map for equivalent languages. |
| 400 | // update will only add entries to original indexes, thus not computing any |
| 401 | // transitive relations. |
| 402 | update := func(want, have uint16, conf Confidence) { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 403 | if hh := m.index[language.Language(have)]; hh != nil { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 404 | if !hh.original { |
| 405 | return |
| 406 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 407 | hw := m.header(language.Language(want)) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 408 | for _, ht := range hh.haveTags { |
| 409 | v := *ht |
| 410 | if conf < v.conf { |
| 411 | v.conf = conf |
| 412 | } |
| 413 | v.nextMax = 0 // this value needs to be recomputed |
| 414 | if v.altScript != 0 { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 415 | v.altScript = altScript(language.Language(want), v.maxScript) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 416 | } |
| 417 | hw.addIfNew(v, conf == Exact && hh.original) |
| 418 | } |
| 419 | } |
| 420 | } |
| 421 | |
| 422 | // Add entries for languages with mutual intelligibility as defined by CLDR's |
| 423 | // languageMatch data. |
| 424 | for _, ml := range matchLang { |
| 425 | update(ml.want, ml.have, toConf(ml.distance)) |
| 426 | if !ml.oneway { |
| 427 | update(ml.have, ml.want, toConf(ml.distance)) |
| 428 | } |
| 429 | } |
| 430 | |
| 431 | // Add entries for possible canonicalizations. This is an optimization to |
| 432 | // ensure that only one map lookup needs to be done at runtime per desired tag. |
| 433 | // First we match deprecated equivalents. If they are perfect equivalents |
| 434 | // (their canonicalization simply substitutes a different language code, but |
| 435 | // nothing else), the match confidence is Exact, otherwise it is High. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 436 | for i, lm := range language.AliasMap { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 437 | // If deprecated codes match and there is no fiddling with the script or |
| 438 | // or region, we consider it an exact match. |
| 439 | conf := Exact |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 440 | if language.AliasTypes[i] != language.Macro { |
| 441 | if !isExactEquivalent(language.Language(lm.From)) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 442 | conf = High |
| 443 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 444 | update(lm.To, lm.From, conf) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 445 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 446 | update(lm.From, lm.To, conf) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 447 | } |
| 448 | return m |
| 449 | } |
| 450 | |
| 451 | // getBest gets the best matching tag in m for any of the given tags, taking into |
| 452 | // account the order of preference of the given tags. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 453 | func (m *matcher) getBest(want ...Tag) (got *haveTag, orig language.Tag, c Confidence) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 454 | best := bestMatch{} |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 455 | for i, ww := range want { |
| 456 | w := ww.tag() |
| 457 | var max language.Tag |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 458 | // Check for exact match first. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 459 | h := m.index[w.LangID] |
| 460 | if w.LangID != 0 { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 461 | if h == nil { |
| 462 | continue |
| 463 | } |
| 464 | // Base language is defined. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 465 | max, _ = canonicalize(Legacy|Deprecated|Macro, w) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 466 | // A region that is added through canonicalization is stronger than |
| 467 | // a maximized region: set it in the original (e.g. mo -> ro-MD). |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 468 | if w.RegionID != max.RegionID { |
| 469 | w.RegionID = max.RegionID |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 470 | } |
| 471 | // TODO: should we do the same for scripts? |
| 472 | // See test case: en, sr, nl ; sh ; sr |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 473 | max, _ = max.Maximize() |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 474 | } else { |
| 475 | // Base language is not defined. |
| 476 | if h != nil { |
| 477 | for i := range h.haveTags { |
| 478 | have := h.haveTags[i] |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 479 | if equalsRest(have.tag, w) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 480 | return have, w, Exact |
| 481 | } |
| 482 | } |
| 483 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 484 | if w.ScriptID == 0 && w.RegionID == 0 { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 485 | // We skip all tags matching und for approximate matching, including |
| 486 | // private tags. |
| 487 | continue |
| 488 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 489 | max, _ = w.Maximize() |
| 490 | if h = m.index[max.LangID]; h == nil { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 491 | continue |
| 492 | } |
| 493 | } |
| 494 | pin := true |
| 495 | for _, t := range want[i+1:] { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 496 | if w.LangID == t.lang() { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 497 | pin = false |
| 498 | break |
| 499 | } |
| 500 | } |
| 501 | // Check for match based on maximized tag. |
| 502 | for i := range h.haveTags { |
| 503 | have := h.haveTags[i] |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 504 | best.update(have, w, max.ScriptID, max.RegionID, pin) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 505 | if best.conf == Exact { |
| 506 | for have.nextMax != 0 { |
| 507 | have = h.haveTags[have.nextMax] |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 508 | best.update(have, w, max.ScriptID, max.RegionID, pin) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 509 | } |
| 510 | return best.have, best.want, best.conf |
| 511 | } |
| 512 | } |
| 513 | } |
| 514 | if best.conf <= No { |
| 515 | if len(want) != 0 { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 516 | return nil, want[0].tag(), No |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 517 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 518 | return nil, language.Tag{}, No |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 519 | } |
| 520 | return best.have, best.want, best.conf |
| 521 | } |
| 522 | |
| 523 | // bestMatch accumulates the best match so far. |
| 524 | type bestMatch struct { |
| 525 | have *haveTag |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 526 | want language.Tag |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 527 | conf Confidence |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 528 | pinnedRegion language.Region |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 529 | pinLanguage bool |
| 530 | sameRegionGroup bool |
| 531 | // Cached results from applying tie-breaking rules. |
| 532 | origLang bool |
| 533 | origReg bool |
| 534 | paradigmReg bool |
| 535 | regGroupDist uint8 |
| 536 | origScript bool |
| 537 | } |
| 538 | |
| 539 | // update updates the existing best match if the new pair is considered to be a |
| 540 | // better match. To determine if the given pair is a better match, it first |
| 541 | // computes the rough confidence level. If this surpasses the current match, it |
| 542 | // will replace it and update the tie-breaker rule cache. If there is a tie, it |
| 543 | // proceeds with applying a series of tie-breaker rules. If there is no |
| 544 | // conclusive winner after applying the tie-breaker rules, it leaves the current |
| 545 | // match as the preferred match. |
| 546 | // |
| 547 | // If pin is true and have and tag are a strong match, it will henceforth only |
| 548 | // consider matches for this language. This corresponds to the nothing that most |
| 549 | // users have a strong preference for the first defined language. A user can |
| 550 | // still prefer a second language over a dialect of the preferred language by |
| 551 | // explicitly specifying dialects, e.g. "en, nl, en-GB". In this case pin should |
| 552 | // be false. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 553 | func (m *bestMatch) update(have *haveTag, tag language.Tag, maxScript language.Script, maxRegion language.Region, pin bool) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 554 | // Bail if the maximum attainable confidence is below that of the current best match. |
| 555 | c := have.conf |
| 556 | if c < m.conf { |
| 557 | return |
| 558 | } |
| 559 | // Don't change the language once we already have found an exact match. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 560 | if m.pinLanguage && tag.LangID != m.want.LangID { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 561 | return |
| 562 | } |
| 563 | // Pin the region group if we are comparing tags for the same language. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 564 | if tag.LangID == m.want.LangID && m.sameRegionGroup { |
| 565 | _, sameGroup := regionGroupDist(m.pinnedRegion, have.maxRegion, have.maxScript, m.want.LangID) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 566 | if !sameGroup { |
| 567 | return |
| 568 | } |
| 569 | } |
| 570 | if c == Exact && have.maxScript == maxScript { |
| 571 | // If there is another language and then another entry of this language, |
| 572 | // don't pin anything, otherwise pin the language. |
| 573 | m.pinLanguage = pin |
| 574 | } |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 575 | if equalsRest(have.tag, tag) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 576 | } else if have.maxScript != maxScript { |
| 577 | // There is usually very little comprehension between different scripts. |
| 578 | // In a few cases there may still be Low comprehension. This possibility |
| 579 | // is pre-computed and stored in have.altScript. |
| 580 | if Low < m.conf || have.altScript != maxScript { |
| 581 | return |
| 582 | } |
| 583 | c = Low |
| 584 | } else if have.maxRegion != maxRegion { |
| 585 | if High < c { |
| 586 | // There is usually a small difference between languages across regions. |
| 587 | c = High |
| 588 | } |
| 589 | } |
| 590 | |
| 591 | // We store the results of the computations of the tie-breaker rules along |
| 592 | // with the best match. There is no need to do the checks once we determine |
| 593 | // we have a winner, but we do still need to do the tie-breaker computations. |
| 594 | // We use "beaten" to keep track if we still need to do the checks. |
| 595 | beaten := false // true if the new pair defeats the current one. |
| 596 | if c != m.conf { |
| 597 | if c < m.conf { |
| 598 | return |
| 599 | } |
| 600 | beaten = true |
| 601 | } |
| 602 | |
| 603 | // Tie-breaker rules: |
| 604 | // We prefer if the pre-maximized language was specified and identical. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 605 | origLang := have.tag.LangID == tag.LangID && tag.LangID != 0 |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 606 | if !beaten && m.origLang != origLang { |
| 607 | if m.origLang { |
| 608 | return |
| 609 | } |
| 610 | beaten = true |
| 611 | } |
| 612 | |
| 613 | // We prefer if the pre-maximized region was specified and identical. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 614 | origReg := have.tag.RegionID == tag.RegionID && tag.RegionID != 0 |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 615 | if !beaten && m.origReg != origReg { |
| 616 | if m.origReg { |
| 617 | return |
| 618 | } |
| 619 | beaten = true |
| 620 | } |
| 621 | |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 622 | regGroupDist, sameGroup := regionGroupDist(have.maxRegion, maxRegion, maxScript, tag.LangID) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 623 | if !beaten && m.regGroupDist != regGroupDist { |
| 624 | if regGroupDist > m.regGroupDist { |
| 625 | return |
| 626 | } |
| 627 | beaten = true |
| 628 | } |
| 629 | |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 630 | paradigmReg := isParadigmLocale(tag.LangID, have.maxRegion) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 631 | if !beaten && m.paradigmReg != paradigmReg { |
| 632 | if !paradigmReg { |
| 633 | return |
| 634 | } |
| 635 | beaten = true |
| 636 | } |
| 637 | |
| 638 | // Next we prefer if the pre-maximized script was specified and identical. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 639 | origScript := have.tag.ScriptID == tag.ScriptID && tag.ScriptID != 0 |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 640 | if !beaten && m.origScript != origScript { |
| 641 | if m.origScript { |
| 642 | return |
| 643 | } |
| 644 | beaten = true |
| 645 | } |
| 646 | |
| 647 | // Update m to the newly found best match. |
| 648 | if beaten { |
| 649 | m.have = have |
| 650 | m.want = tag |
| 651 | m.conf = c |
| 652 | m.pinnedRegion = maxRegion |
| 653 | m.sameRegionGroup = sameGroup |
| 654 | m.origLang = origLang |
| 655 | m.origReg = origReg |
| 656 | m.paradigmReg = paradigmReg |
| 657 | m.origScript = origScript |
| 658 | m.regGroupDist = regGroupDist |
| 659 | } |
| 660 | } |
| 661 | |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 662 | func isParadigmLocale(lang language.Language, r language.Region) bool { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 663 | for _, e := range paradigmLocales { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 664 | if language.Language(e[0]) == lang && (r == language.Region(e[1]) || r == language.Region(e[2])) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 665 | return true |
| 666 | } |
| 667 | } |
| 668 | return false |
| 669 | } |
| 670 | |
| 671 | // regionGroupDist computes the distance between two regions based on their |
| 672 | // CLDR grouping. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 673 | func regionGroupDist(a, b language.Region, script language.Script, lang language.Language) (dist uint8, same bool) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 674 | const defaultDistance = 4 |
| 675 | |
| 676 | aGroup := uint(regionToGroups[a]) << 1 |
| 677 | bGroup := uint(regionToGroups[b]) << 1 |
| 678 | for _, ri := range matchRegion { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 679 | if language.Language(ri.lang) == lang && (ri.script == 0 || language.Script(ri.script) == script) { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 680 | group := uint(1 << (ri.group &^ 0x80)) |
| 681 | if 0x80&ri.group == 0 { |
| 682 | if aGroup&bGroup&group != 0 { // Both regions are in the group. |
| 683 | return ri.distance, ri.distance == defaultDistance |
| 684 | } |
| 685 | } else { |
| 686 | if (aGroup|bGroup)&group == 0 { // Both regions are not in the group. |
| 687 | return ri.distance, ri.distance == defaultDistance |
| 688 | } |
| 689 | } |
| 690 | } |
| 691 | } |
| 692 | return defaultDistance, true |
| 693 | } |
| 694 | |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 695 | // equalsRest compares everything except the language. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 696 | func equalsRest(a, b language.Tag) bool { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 697 | // TODO: don't include extensions in this comparison. To do this efficiently, |
| 698 | // though, we should handle private tags separately. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 699 | return a.ScriptID == b.ScriptID && a.RegionID == b.RegionID && a.VariantOrPrivateUseTags() == b.VariantOrPrivateUseTags() |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 700 | } |
| 701 | |
| 702 | // isExactEquivalent returns true if canonicalizing the language will not alter |
| 703 | // the script or region of a tag. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 704 | func isExactEquivalent(l language.Language) bool { |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 705 | for _, o := range notEquivalent { |
| 706 | if o == l { |
| 707 | return false |
| 708 | } |
| 709 | } |
| 710 | return true |
| 711 | } |
| 712 | |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 713 | var notEquivalent []language.Language |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 714 | |
| 715 | func init() { |
| 716 | // Create a list of all languages for which canonicalization may alter the |
| 717 | // script or region. |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 718 | for _, lm := range language.AliasMap { |
| 719 | tag := language.Tag{LangID: language.Language(lm.From)} |
| 720 | if tag, _ = canonicalize(All, tag); tag.ScriptID != 0 || tag.RegionID != 0 { |
| 721 | notEquivalent = append(notEquivalent, language.Language(lm.From)) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 722 | } |
| 723 | } |
| 724 | // Maximize undefined regions of paradigm locales. |
| 725 | for i, v := range paradigmLocales { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 726 | t := language.Tag{LangID: language.Language(v[0])} |
| 727 | max, _ := t.Maximize() |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 728 | if v[1] == 0 { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 729 | paradigmLocales[i][1] = uint16(max.RegionID) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 730 | } |
| 731 | if v[2] == 0 { |
Abhilash S.L | 3b49463 | 2019-07-16 15:51:09 +0530 | [diff] [blame] | 732 | paradigmLocales[i][2] = uint16(max.RegionID) |
William Kurkian | ea86948 | 2019-04-09 15:16:11 -0400 | [diff] [blame] | 733 | } |
| 734 | } |
| 735 | } |