mirror of https://github.com/onweru/compose.git
assets/js/lunr.js
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Current version of lunr '"+z.version+"' does not match serialized index '"+e.version+"'");for(var u=0;u<i.length;u++){var l=(h=i[u])[0],c=h[1];r[l]=new z.Vector(c)}for(u=0;u<s.length;u++){var h,d=(h=s[u])[0],f=h[1];o.insert(d),n[d]=f}return o.finish(),t.fields=e.fields,t.fieldVectors=r,t.invertedIndex=n,t.tokenSet=o.root,t.pipeline=a,new z.Index(t)},z.Builder=function(){this._ref="id",this._fields=Object.create(null),this._documents=Object.create(null),this.invertedIndex=Object.create(null),this.fieldTermFrequencies={},this.fieldLengths={},this.tokenizer=z.tokenizer,this.pipeline=new z.Pipeline,this.searchPipeline=new z.Pipeline,this.documentCount=0,this._b=.75,this._k1=1.2,this.termIndex=0,this.metadataWhitelist=[]},z.Builder.prototype.ref=function(e){this._ref=e},z.Builder.prototype.field=function(e,t){if(/\//.test(e))throw new RangeError("Field '"+e+"' contains illegal character '/'");this._fields[e]=t||{}},z.Builder.prototype.b=function(e){this._b=e<0?0:1<e?1:e},z.Builder.prototype.k1=function(e){this._k1=e},z.Builder.prototype.add=function(e,t){var r=e[this._ref],i=Object.keys(this._fields);this._documents[r]=t||{},this.documentCount+=1;for(var n=0;n<i.length;n++){var s=i[n],o=this._fields[s].extractor,a=o?o(e):e[s],u=this.tokenizer(a,{fields:[s]}),l=this.pipeline.run(u),c=new z.FieldRef(r,s),h=Object.create(null);this.fieldTermFrequencies[c]=h,this.fieldLengths[c]=0,this.fieldLengths[c]+=l.length;for(var d=0;d<l.length;d++){var f=l[d];if(null==h[f]&&(h[f]=0),h[f]+=1,null==this.invertedIndex[f]){var p=Object.create(null);p._index=this.termIndex,this.termIndex+=1;for(var y=0;y<i.length;y++)p[i[y]]=Object.create(null);this.invertedIndex[f]=p}null==this.invertedIndex[f][s][r]&&(this.invertedIndex[f][s][r]=Object.create(null));for(var m=0;m<this.metadataWhitelist.length;m++){var g=this.metadataWhitelist[m],x=f.metadata[g];null==this.invertedIndex[f][s][r][g]&&(this.invertedIndex[f][s][r][g]=[]),this.invertedIndex[f][s][r][g].push(x)}}}},z.Builder.prototype.calculateAverageFieldLengths=function(){for(var e=Object.keys(this.fieldLengths),t=e.length,r={},i={},n=0;n<t;n++){var s=z.FieldRef.fromString(e[n]),o=s.fieldName;i[o]||(i[o]=0),i[o]+=1,r[o]||(r[o]=0),r[o]+=this.fieldLengths[s]}var a=Object.keys(this._fields);for(n=0;n<a.length;n++){var u=a[n];r[u]=r[u]/i[u]}this.averageFieldLength=r},z.Builder.prototype.createFieldVectors=function(){for(var e={},t=Object.keys(this.fieldTermFrequencies),r=t.length,i=Object.create(null),n=0;n<r;n++){for(var s=z.FieldRef.fromString(t[n]),o=s.fieldName,a=this.fieldLengths[s],u=new z.Vector,l=this.fieldTermFrequencies[s],c=Object.keys(l),h=c.length,d=this._fields[o].boost||1,f=this._documents[s.docRef].boost||1,p=0;p<h;p++){var y,m,g,x=c[p],v=l[x],w=this.invertedIndex[x]._index;void 0===i[x]?(y=z.idf(this.invertedIndex[x],this.documentCount),i[x]=y):y=i[x],m=y*((this._k1+1)*v)/(this._k1*(1-this._b+this._b*(a/this.averageFieldLength[o]))+v),m*=d,m*=f,g=Math.round(1e3*m)/1e3,u.insert(w,g)}e[s]=u}this.fieldVectors=e},z.Builder.prototype.createTokenSet=function(){this.tokenSet=z.TokenSet.fromArray(Object.keys(this.invertedIndex).sort())},z.Builder.prototype.build=function(){return this.calculateAverageFieldLengths(),this.createFieldVectors(),this.createTokenSet(),new z.Index({invertedIndex:this.invertedIndex,fieldVectors:this.fieldVectors,tokenSet:this.tokenSet,fields:Object.keys(this._fields),pipeline:this.searchPipeline})},z.Builder.prototype.use=function(e){var t=Array.prototype.slice.call(arguments,1);t.unshift(this),e.apply(this,t)},z.MatchData=function(e,t,r){for(var i=Object.create(null),n=Object.keys(r||{}),s=0;s<n.length;s++){var o=n[s];i[o]=r[o].slice()}this.metadata=Object.create(null),void 0!==e&&(this.metadata[e]=Object.create(null),this.metadata[e][t]=i)},z.MatchData.prototype.combine=function(e){for(var t=Object.keys(e.metadata),r=0;r<t.length;r++){var i=t[r],n=Object.keys(e.metadata[i]);null==this.metadata[i]&&(this.metadata[i]=Object.create(null));for(var s=0;s<n.length;s++){var o=n[s],a=Object.keys(e.metadata[i][o]);null==this.metadata[i][o]&&(this.metadata[i][o]=Object.create(null));for(var u=0;u<a.length;u++){var l=a[u];null==this.metadata[i][o][l]?this.metadata[i][o][l]=e.metadata[i][o][l]:this.metadata[i][o][l]=this.metadata[i][o][l].concat(e.metadata[i][o][l])}}}},z.MatchData.prototype.add=function(e,t,r){if(!(e in this.metadata))return this.metadata[e]=Object.create(null),void(this.metadata[e][t]=r);if(t in this.metadata[e])for(var i=Object.keys(r),n=0;n<i.length;n++){var s=i[n];s in this.metadata[e][t]?this.metadata[e][t][s]=this.metadata[e][t][s].concat(r[s]):this.metadata[e][t][s]=r[s]}else this.metadata[e][t]=r},z.Query=function(e){this.clauses=[],this.allFields=e},z.Query.wildcard=new String("*"),z.Query.wildcard.NONE=0,z.Query.wildcard.LEADING=1,z.Query.wildcard.TRAILING=2,z.Query.presence={OPTIONAL:1,REQUIRED:2,PROHIBITED:3},z.Query.prototype.clause=function(e){return"fields"in e||(e.fields=this.allFields),"boost"in e||(e.boost=1),"usePipeline"in e||(e.usePipeline=!0),"wildcard"in e||(e.wildcard=z.Query.wildcard.NONE),e.wildcard&z.Query.wildcard.LEADING&&e.term.charAt(0)!=z.Query.wildcard&&(e.term="*"+e.term),e.wildcard&z.Query.wildcard.TRAILING&&e.term.slice(-1)!=z.Query.wildcard&&(e.term=e.term+"*"),"presence"in e||(e.presence=z.Query.presence.OPTIONAL),this.clauses.push(e),this},z.Query.prototype.isNegated=function(){for(var e=0;e<this.clauses.length;e++)if(this.clauses[e].presence!=z.Query.presence.PROHIBITED)return!1;return!0},z.Query.prototype.term=function(e,t){if(Array.isArray(e))return e.forEach(function(e){this.term(e,z.utils.clone(t))},this),this;var r=t||{};return r.term=e.toString(),this.clause(r),this},z.QueryParseError=function(e,t,r){this.name="QueryParseError",this.message=e,this.start=t,this.end=r},z.QueryParseError.prototype=new Error,z.QueryLexer=function(e){this.lexemes=[],this.str=e,this.length=e.length,this.pos=0,this.start=0,this.escapeCharPositions=[]},z.QueryLexer.prototype.run=function(){for(var e=z.QueryLexer.lexText;e;)e=e(this)},z.QueryLexer.prototype.sliceString=function(){for(var e=[],t=this.start,r=this.pos,i=0;i<this.escapeCharPositions.length;i++)r=this.escapeCharPositions[i],e.push(this.str.slice(t,r)),t=r+1;return e.push(this.str.slice(t,this.pos)),this.escapeCharPositions.length=0,e.join("")},z.QueryLexer.prototype.emit=function(e){this.lexemes.push({type:e,str:this.sliceString(),start:this.start,end:this.pos}),this.start=this.pos},z.QueryLexer.prototype.escapeCharacter=function(){this.escapeCharPositions.push(this.pos-1),this.pos+=1},z.QueryLexer.prototype.next=function(){if(this.pos>=this.length)return z.QueryLexer.EOS;var e=this.str.charAt(this.pos);return this.pos+=1,e},z.QueryLexer.prototype.width=function(){return this.pos-this.start},z.QueryLexer.prototype.ignore=function(){this.start==this.pos&&(this.pos+=1),this.start=this.pos},z.QueryLexer.prototype.backup=function(){--this.pos},z.QueryLexer.prototype.acceptDigitRun=function(){for(var e,t;47<(t=(e=this.next()).charCodeAt(0))&&t<58;);e!=z.QueryLexer.EOS&&this.backup()},z.QueryLexer.prototype.more=function(){return this.pos<this.length},z.QueryLexer.EOS="EOS",z.QueryLexer.FIELD="FIELD",z.QueryLexer.TERM="TERM",z.QueryLexer.EDIT_DISTANCE="EDIT_DISTANCE",z.QueryLexer.BOOST="BOOST",z.QueryLexer.PRESENCE="PRESENCE",z.QueryLexer.lexField=function(e){return e.backup(),e.emit(z.QueryLexer.FIELD),e.ignore(),z.QueryLexer.lexText},z.QueryLexer.lexTerm=function(e){if(1<e.width()&&(e.backup(),e.emit(z.QueryLexer.TERM)),e.ignore(),e.more())return z.QueryLexer.lexText},z.QueryLexer.lexEditDistance=function(e){return e.ignore(),e.acceptDigitRun(),e.emit(z.QueryLexer.EDIT_DISTANCE),z.QueryLexer.lexText},z.QueryLexer.lexBoost=function(e){return e.ignore(),e.acceptDigitRun(),e.emit(z.QueryLexer.BOOST),z.QueryLexer.lexText},z.QueryLexer.lexEOS=function(e){0<e.width()&&e.emit(z.QueryLexer.TERM)},z.QueryLexer.termSeparator=z.tokenizer.separator,z.QueryLexer.lexText=function(e){for(;;){var t=e.next();if(t==z.QueryLexer.EOS)return z.QueryLexer.lexEOS;if(92!=t.charCodeAt(0)){if(":"==t)return z.QueryLexer.lexField;if("~"==t)return e.backup(),0<e.width()&&e.emit(z.QueryLexer.TERM),z.QueryLexer.lexEditDistance;if("^"==t)return e.backup(),0<e.width()&&e.emit(z.QueryLexer.TERM),z.QueryLexer.lexBoost;if("+"==t&&1===e.width())return e.emit(z.QueryLexer.PRESENCE),z.QueryLexer.lexText;if("-"==t&&1===e.width())return e.emit(z.QueryLexer.PRESENCE),z.QueryLexer.lexText;if(t.match(z.QueryLexer.termSeparator))return z.QueryLexer.lexTerm}else e.escapeCharacter()}},z.QueryParser=function(e,t){this.lexer=new z.QueryLexer(e),this.query=t,this.currentClause={},this.lexemeIdx=0},z.QueryParser.prototype.parse=function(){this.lexer.run(),this.lexemes=this.lexer.lexemes;for(var e=z.QueryParser.parseClause;e;)e=e(this);return this.query},z.QueryParser.prototype.peekLexeme=function(){return this.lexemes[this.lexemeIdx]},z.QueryParser.prototype.consumeLexeme=function(){var e=this.peekLexeme();return this.lexemeIdx+=1,e},z.QueryParser.prototype.nextClause=function(){var e=this.currentClause;this.query.clause(e),this.currentClause={}},z.QueryParser.parseClause=function(e){var t=e.peekLexeme();if(null!=t)switch(t.type){case z.QueryLexer.PRESENCE:return z.QueryParser.parsePresence;case z.QueryLexer.FIELD:return z.QueryParser.parseField;case z.QueryLexer.TERM:return z.QueryParser.parseTerm;default:var r="expected either a field or a term, found "+t.type;throw 1<=t.str.length&&(r+=" with value '"+t.str+"'"),new z.QueryParseError(r,t.start,t.end)}},z.QueryParser.parsePresence=function(e){var t=e.consumeLexeme();if(null!=t){switch(t.str){case"-":e.currentClause.presence=z.Query.presence.PROHIBITED;break;case"+":e.currentClause.presence=z.Query.presence.REQUIRED;break;default:var r="unrecognised presence operator'"+t.str+"'";throw new z.QueryParseError(r,t.start,t.end)}var i=e.peekLexeme();if(null==i){r="expecting term or field, found nothing";throw new z.QueryParseError(r,t.start,t.end)}switch(i.type){case z.QueryLexer.FIELD:return z.QueryParser.parseField;case z.QueryLexer.TERM:return z.QueryParser.parseTerm;default:r="expecting term or field, found '"+i.type+"'";throw new z.QueryParseError(r,i.start,i.end)}}},z.QueryParser.parseField=function(e){var t=e.consumeLexeme();if(null!=t){if(-1==e.query.allFields.indexOf(t.str)){var r=e.query.allFields.map(function(e){return"'"+e+"'"}).join(", "),i="unrecognised field '"+t.str+"', possible fields: "+r;throw new z.QueryParseError(i,t.start,t.end)}e.currentClause.fields=[t.str];var n=e.peekLexeme();if(null==n){i="expecting term, found nothing";throw new z.QueryParseError(i,t.start,t.end)}switch(n.type){case z.QueryLexer.TERM:return z.QueryParser.parseTerm;default:i="expecting term, found '"+n.type+"'";throw new z.QueryParseError(i,n.start,n.end)}}},z.QueryParser.parseTerm=function(e){var t=e.consumeLexeme();if(null!=t){e.currentClause.term=t.str.toLowerCase(),-1!=t.str.indexOf("*")&&(e.currentClause.usePipeline=!1);var r=e.peekLexeme();if(null!=r)switch(r.type){case z.QueryLexer.TERM:return e.nextClause(),z.QueryParser.parseTerm;case z.QueryLexer.FIELD:return e.nextClause(),z.QueryParser.parseField;case z.QueryLexer.EDIT_DISTANCE:return z.QueryParser.parseEditDistance;case z.QueryLexer.BOOST:return z.QueryParser.parseBoost;case z.QueryLexer.PRESENCE:return e.nextClause(),z.QueryParser.parsePresence;default:var i="Unexpected lexeme type '"+r.type+"'";throw new z.QueryParseError(i,r.start,r.end)}else e.nextClause()}},z.QueryParser.parseEditDistance=function(e){var t=e.consumeLexeme();if(null!=t){var r=parseInt(t.str,10);if(isNaN(r)){var i="edit distance must be numeric";throw new z.QueryParseError(i,t.start,t.end)}e.currentClause.editDistance=r;var n=e.peekLexeme();if(null!=n)switch(n.type){case z.QueryLexer.TERM:return e.nextClause(),z.QueryParser.parseTerm;case z.QueryLexer.FIELD:return e.nextClause(),z.QueryParser.parseField;case z.QueryLexer.EDIT_DISTANCE:return z.QueryParser.parseEditDistance;case z.QueryLexer.BOOST:return z.QueryParser.parseBoost;case z.QueryLexer.PRESENCE:return e.nextClause(),z.QueryParser.parsePresence;default:i="Unexpected lexeme type '"+n.type+"'";throw new z.QueryParseError(i,n.start,n.end)}else e.nextClause()}},z.QueryParser.parseBoost=function(e){var t=e.consumeLexeme();if(null!=t){var r=parseInt(t.str,10);if(isNaN(r)){var i="boost must be numeric";throw new z.QueryParseError(i,t.start,t.end)}e.currentClause.boost=r;var n=e.peekLexeme();if(null!=n)switch(n.type){case z.QueryLexer.TERM:return e.nextClause(),z.QueryParser.parseTerm;case z.QueryLexer.FIELD:return e.nextClause(),z.QueryParser.parseField;case z.QueryLexer.EDIT_DISTANCE:return z.QueryParser.parseEditDistance;case z.QueryLexer.BOOST:return z.QueryParser.parseBoost;case z.QueryLexer.PRESENCE:return e.nextClause(),z.QueryParser.parsePresence;default:i="Unexpected lexeme type '"+n.type+"'";throw new z.QueryParseError(i,n.start,n.end)}else e.nextClause()}},i=this,n=function(){return z},"function"==typeof define&&define.amd?define(n):"object"==typeof exports?module.exports=n():i.lunr=n()}(); /** * lunr - http://lunrjs.com - A bit like Solr, but much smaller and not as bright - 2.3.9 * Copyright (C) 2020 Oliver Nightingale * @license MIT */ ;(function(){ /** * A convenience function for configuring and constructing * a new lunr Index. * * A lunr.Builder instance is created and the pipeline setup * with a trimmer, stop word filter and stemmer. * * This builder object is yielded to the configuration function * that is passed as a parameter, allowing the list of fields * and other builder parameters to be customised. * * All documents _must_ be added within the passed config function. * * @example * var idx = lunr(function () { * this.field('title') * this.field('body') * this.ref('id') * * documents.forEach(function (doc) { * this.add(doc) * }, this) * }) * * @see {@link lunr.Builder} * @see {@link lunr.Pipeline} * @see {@link lunr.trimmer} * @see {@link lunr.stopWordFilter} * @see {@link lunr.stemmer} * @namespace {function} lunr */ var lunr = function (config) { var builder = new lunr.Builder builder.pipeline.add( lunr.trimmer, lunr.stopWordFilter, lunr.stemmer ) builder.searchPipeline.add( lunr.stemmer ) config.call(builder, builder) return builder.build() } lunr.version = "2.3.9" /*! * lunr.utils * Copyright (C) 2020 Oliver Nightingale */ /** * A namespace containing utils for the rest of the lunr library * @namespace lunr.utils */ lunr.utils = {} /** * Print a warning message to the console. * * @param {String} message The message to be printed. * @memberOf lunr.utils * @function */ lunr.utils.warn = (function (global) { /* eslint-disable no-console */ return function (message) { if (global.console && console.warn) { console.warn(message) } } /* eslint-enable no-console */ })(this) /** * Convert an object to a string. * * In the case of `null` and `undefined` the function returns * the empty string, in all other cases the result of calling * `toString` on the passed object is returned. * * @param {Any} obj The object to convert to a string. * @return {String} string representation of the passed object. * @memberOf lunr.utils */ lunr.utils.asString = function (obj) { if (obj === void 0 || obj === null) { return "" } else { return obj.toString() } } /** * Clones an object. * * Will create a copy of an existing object such that any mutations * on the copy cannot affect the original. * * Only shallow objects are supported, passing a nested object to this * function will cause a TypeError. * * Objects with primitives, and arrays of primitives are supported. * * @param {Object} obj The object to clone. * @return {Object} a clone of the passed object. * @throws {TypeError} when a nested object is passed. * @memberOf Utils */ lunr.utils.clone = function (obj) { if (obj === null || obj === undefined) { return obj } var clone = Object.create(null), keys = Object.keys(obj) for (var i = 0; i < keys.length; i++) { var key = keys[i], val = obj[key] if (Array.isArray(val)) { clone[key] = val.slice() continue } if (typeof val === 'string' || typeof val === 'number' || typeof val === 'boolean') { clone[key] = val continue } throw new TypeError("clone is not deep and does not support nested objects") } return clone } lunr.FieldRef = function (docRef, fieldName, stringValue) { this.docRef = docRef this.fieldName = fieldName this._stringValue = stringValue } lunr.FieldRef.joiner = "/" lunr.FieldRef.fromString = function (s) { var n = s.indexOf(lunr.FieldRef.joiner) if (n === -1) { throw "malformed field ref string" } var fieldRef = s.slice(0, n), docRef = s.slice(n + 1) return new lunr.FieldRef (docRef, fieldRef, s) } lunr.FieldRef.prototype.toString = function () { if (this._stringValue == undefined) { this._stringValue = this.fieldName + lunr.FieldRef.joiner + this.docRef } return this._stringValue } /*! * lunr.Set * Copyright (C) 2020 Oliver Nightingale */ /** * A lunr set. * * @constructor */ lunr.Set = function (elements) { this.elements = Object.create(null) if (elements) { this.length = elements.length for (var i = 0; i < this.length; i++) { this.elements[elements[i]] = true } } else { this.length = 0 } } /** * A complete set that contains all elements. * * @static * @readonly * @type {lunr.Set} */ lunr.Set.complete = { intersect: function (other) { return other }, union: function () { return this }, contains: function () { return true } } /** * An empty set that contains no elements. * * @static * @readonly * @type {lunr.Set} */ lunr.Set.empty = { intersect: function () { return this }, union: function (other) { return other }, contains: function () { return false } } /** * Returns true if this set contains the specified object. * * @param {object} object - Object whose presence in this set is to be tested. * @returns {boolean} - True if this set contains the specified object. */ lunr.Set.prototype.contains = function (object) { return !!this.elements[object] } /** * Returns a new set containing only the elements that are present in both * this set and the specified set. * * @param {lunr.Set} other - set to intersect with this set. * @returns {lunr.Set} a new set that is the intersection of this and the specified set. */ lunr.Set.prototype.intersect = function (other) { var a, b, elements, intersection = [] if (other === lunr.Set.complete) { return this } if (other === lunr.Set.empty) { return other } if (this.length < other.length) { a = this b = other } else { a = other b = this } elements = Object.keys(a.elements) for (var i = 0; i < elements.length; i++) { var element = elements[i] if (element in b.elements) { intersection.push(element) } } return new lunr.Set (intersection) } /** * Returns a new set combining the elements of this and the specified set. * * @param {lunr.Set} other - set to union with this set. * @return {lunr.Set} a new set that is the union of this and the specified set. */ lunr.Set.prototype.union = function (other) { if (other === lunr.Set.complete) { return lunr.Set.complete } if (other === lunr.Set.empty) { return this } return new lunr.Set(Object.keys(this.elements).concat(Object.keys(other.elements))) } /** * A function to calculate the inverse document frequency for * a posting. This is shared between the builder and the index * * @private * @param {object} posting - The posting for a given term * @param {number} documentCount - The total number of documents. */ lunr.idf = function (posting, documentCount) { var documentsWithTerm = 0 for (var fieldName in posting) { if (fieldName == '_index') continue // Ignore the term index, its not a field documentsWithTerm += Object.keys(posting[fieldName]).length } var x = (documentCount - documentsWithTerm + 0.5) / (documentsWithTerm + 0.5) return Math.log(1 + Math.abs(x)) } /** * A token wraps a string representation of a token * as it is passed through the text processing pipeline. * * @constructor * @param {string} [str=''] - The string token being wrapped. * @param {object} [metadata={}] - Metadata associated with this token. */ lunr.Token = function (str, metadata) { this.str = str || "" this.metadata = metadata || {} } /** * Returns the token string that is being wrapped by this object. * * @returns {string} */ lunr.Token.prototype.toString = function () { return this.str } /** * A token update function is used when updating or optionally * when cloning a token. * * @callback lunr.Token~updateFunction * @param {string} str - The string representation of the token. * @param {Object} metadata - All metadata associated with this token. */ /** * Applies the given function to the wrapped string token. * * @example * token.update(function (str, metadata) { * return str.toUpperCase() * }) * * @param {lunr.Token~updateFunction} fn - A function to apply to the token string. * @returns {lunr.Token} */ lunr.Token.prototype.update = function (fn) { this.str = fn(this.str, this.metadata) return this } /** * Creates a clone of this token. Optionally a function can be * applied to the cloned token. * * @param {lunr.Token~updateFunction} [fn] - An optional function to apply to the cloned token. * @returns {lunr.Token} */ lunr.Token.prototype.clone = function (fn) { fn = fn || function (s) { return s } return new lunr.Token (fn(this.str, this.metadata), this.metadata) } /*! * lunr.tokenizer * Copyright (C) 2020 Oliver Nightingale */ /** * A function for splitting a string into tokens ready to be inserted into * the search index. Uses `lunr.tokenizer.separator` to split strings, change * the value of this property to change how strings are split into tokens. * * This tokenizer will convert its parameter to a string by calling `toString` and * then will split this string on the character in `lunr.tokenizer.separator`. * Arrays will have their elements converted to strings and wrapped in a lunr.Token. * * Optional metadata can be passed to the tokenizer, this metadata will be cloned and * added as metadata to every token that is created from the object to be tokenized. * * @static * @param {?(string|object|object[])} obj - The object to convert into tokens * @param {?object} metadata - Optional metadata to associate with every token * @returns {lunr.Token[]} * @see {@link lunr.Pipeline} */ lunr.tokenizer = function (obj, metadata) { if (obj == null || obj == undefined) { return [] } if (Array.isArray(obj)) { return obj.map(function (t) { return new lunr.Token( lunr.utils.asString(t).toLowerCase(), lunr.utils.clone(metadata) ) }) } var str = obj.toString().toLowerCase(), len = str.length, tokens = [] for (var sliceEnd = 0, sliceStart = 0; sliceEnd <= len; sliceEnd++) { var char = str.charAt(sliceEnd), sliceLength = sliceEnd - sliceStart if ((char.match(lunr.tokenizer.separator) || sliceEnd == len)) { if (sliceLength > 0) { var tokenMetadata = lunr.utils.clone(metadata) || {} tokenMetadata["position"] = [sliceStart, sliceLength] tokenMetadata["index"] = tokens.length tokens.push( new lunr.Token ( str.slice(sliceStart, sliceEnd), tokenMetadata ) ) } sliceStart = sliceEnd + 1 } } return tokens } /** * The separator used to split a string into tokens. Override this property to change the behaviour of * `lunr.tokenizer` behaviour when tokenizing strings. By default this splits on whitespace and hyphens. * * @static * @see lunr.tokenizer */ lunr.tokenizer.separator = /[\s\-]+/ /*! * lunr.Pipeline * Copyright (C) 2020 Oliver Nightingale */ /** * lunr.Pipelines maintain an ordered list of functions to be applied to all * tokens in documents entering the search index and queries being ran against * the index. * * An instance of lunr.Index created with the lunr shortcut will contain a * pipeline with a stop word filter and an English language stemmer. Extra * functions can be added before or after either of these functions or these * default functions can be removed. * * When run the pipeline will call each function in turn, passing a token, the * index of that token in the original list of all tokens and finally a list of * all the original tokens. * * The output of functions in the pipeline will be passed to the next function * in the pipeline. To exclude a token from entering the index the function * should return undefined, the rest of the pipeline will not be called with * this token. * * For serialisation of pipelines to work, all functions used in an instance of * a pipeline should be registered with lunr.Pipeline. Registered functions can * then be loaded. If trying to load a serialised pipeline that uses functions * that are not registered an error will be thrown. * * If not planning on serialising the pipeline then registering pipeline functions * is not necessary. * * @constructor */ lunr.Pipeline = function () { this._stack = [] } lunr.Pipeline.registeredFunctions = Object.create(null) /** * A pipeline function maps lunr.Token to lunr.Token. A lunr.Token contains the token * string as well as all known metadata. A pipeline function can mutate the token string * or mutate (or add) metadata for a given token. * * A pipeline function can indicate that the passed token should be discarded by returning * null, undefined or an empty string. This token will not be passed to any downstream pipeline * functions and will not be added to the index. * * Multiple tokens can be returned by returning an array of tokens. Each token will be passed * to any downstream pipeline functions and all will returned tokens will be added to the index. * * Any number of pipeline functions may be chained together using a lunr.Pipeline. * * @interface lunr.PipelineFunction * @param {lunr.Token} token - A token from the document being processed. * @param {number} i - The index of this token in the complete list of tokens for this document/field. * @param {lunr.Token[]} tokens - All tokens for this document/field. * @returns {(?lunr.Token|lunr.Token[])} */ /** * Register a function with the pipeline. * * Functions that are used in the pipeline should be registered if the pipeline * needs to be serialised, or a serialised pipeline needs to be loaded. * * Registering a function does not add it to a pipeline, functions must still be * added to instances of the pipeline for them to be used when running a pipeline. * * @param {lunr.PipelineFunction} fn - The function to check for. * @param {String} label - The label to register this function with */ lunr.Pipeline.registerFunction = function (fn, label) { if (label in this.registeredFunctions) { lunr.utils.warn('Overwriting existing registered function: ' + label) } fn.label = label lunr.Pipeline.registeredFunctions[fn.label] = fn } /** * Warns if the function is not registered as a Pipeline function. * * @param {lunr.PipelineFunction} fn - The function to check for. * @private */ lunr.Pipeline.warnIfFunctionNotRegistered = function (fn) { var isRegistered = fn.label && (fn.label in this.registeredFunctions) if (!isRegistered) { lunr.utils.warn('Function is not registered with pipeline. This may cause problems when serialising the index.\n', fn) } } /** * Loads a previously serialised pipeline. * * All functions to be loaded must already be registered with lunr.Pipeline. * If any function from the serialised data has not been registered then an * error will be thrown. * * @param {Object} serialised - The serialised pipeline to load. * @returns {lunr.Pipeline} */ lunr.Pipeline.load = function (serialised) { var pipeline = new lunr.Pipeline serialised.forEach(function (fnName) { var fn = lunr.Pipeline.registeredFunctions[fnName] if (fn) { pipeline.add(fn) } else { throw new Error('Cannot load unregistered function: ' + fnName) } }) return pipeline } /** * Adds new functions to the end of the pipeline. * * Logs a warning if the function has not been registered. * * @param {lunr.PipelineFunction[]} functions - Any number of functions to add to the pipeline. */ lunr.Pipeline.prototype.add = function () { var fns = Array.prototype.slice.call(arguments) fns.forEach(function (fn) { lunr.Pipeline.warnIfFunctionNotRegistered(fn) this._stack.push(fn) }, this) } /** * Adds a single function after a function that already exists in the * pipeline. * * Logs a warning if the function has not been registered. * * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline. * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline. */ lunr.Pipeline.prototype.after = function (existingFn, newFn) { lunr.Pipeline.warnIfFunctionNotRegistered(newFn) var pos = this._stack.indexOf(existingFn) if (pos == -1) { throw new Error('Cannot find existingFn') } pos = pos + 1 this._stack.splice(pos, 0, newFn) } /** * Adds a single function before a function that already exists in the * pipeline. * * Logs a warning if the function has not been registered. * * @param {lunr.PipelineFunction} existingFn - A function that already exists in the pipeline. * @param {lunr.PipelineFunction} newFn - The new function to add to the pipeline. */ lunr.Pipeline.prototype.before = function (existingFn, newFn) { lunr.Pipeline.warnIfFunctionNotRegistered(newFn) var pos = this._stack.indexOf(existingFn) if (pos == -1) { throw new Error('Cannot find existingFn') } this._stack.splice(pos, 0, newFn) } /** * Removes a function from the pipeline. * * @param {lunr.PipelineFunction} fn The function to remove from the pipeline. */ lunr.Pipeline.prototype.remove = function (fn) { var pos = this._stack.indexOf(fn) if (pos == -1) { return } this._stack.splice(pos, 1) } /** * Runs the current list of functions that make up the pipeline against the * passed tokens. * * @param {Array} tokens The tokens to run through the pipeline. * @returns {Array} */ lunr.Pipeline.prototype.run = function (tokens) { var stackLength = this._stack.length for (var i = 0; i < stackLength; i++) { var fn = this._stack[i] var memo = [] for (var j = 0; j < tokens.length; j++) { var result = fn(tokens[j], j, tokens) if (result === null || result === void 0 || result === '') continue if (Array.isArray(result)) { for (var k = 0; k < result.length; k++) { memo.push(result[k]) } } else { memo.push(result) } } tokens = memo } return tokens } /** * Convenience method for passing a string through a pipeline and getting * strings out. This method takes care of wrapping the passed string in a * token and mapping the resulting tokens back to strings. * * @param {string} str - The string to pass through the pipeline. * @param {?object} metadata - Optional metadata to associate with the token * passed to the pipeline. * @returns {string[]} */ lunr.Pipeline.prototype.runString = function (str, metadata) { var token = new lunr.Token (str, metadata) return this.run([token]).map(function (t) { return t.toString() }) } /** * Resets the pipeline by removing any existing processors. * */ lunr.Pipeline.prototype.reset = function () { this._stack = [] } /** * Returns a representation of the pipeline ready for serialisation. * * Logs a warning if the function has not been registered. * * @returns {Array} */ lunr.Pipeline.prototype.toJSON = function () { return this._stack.map(function (fn) { lunr.Pipeline.warnIfFunctionNotRegistered(fn) return fn.label }) } /*! * lunr.Vector * Copyright (C) 2020 Oliver Nightingale */ /** * A vector is used to construct the vector space of documents and queries. These * vectors support operations to determine the similarity between two documents or * a document and a query. * * Normally no parameters are required for initializing a vector, but in the case of * loading a previously dumped vector the raw elements can be provided to the constructor. * * For performance reasons vectors are implemented with a flat array, where an elements * index is immediately followed by its value. E.g. [index, value, index, value]. This * allows the underlying array to be as sparse as possible and still offer decent * performance when being used for vector calculations. * * @constructor * @param {Number[]} [elements] - The flat list of element index and element value pairs. */ lunr.Vector = function (elements) { this._magnitude = 0 this.elements = elements || [] } /** * Calculates the position within the vector to insert a given index. * * This is used internally by insert and upsert. If there are duplicate indexes then * the position is returned as if the value for that index were to be updated, but it * is the callers responsibility to check whether there is a duplicate at that index * * @param {Number} insertIdx - The index at which the element should be inserted. * @returns {Number} */ lunr.Vector.prototype.positionForIndex = function (index) { // For an empty vector the tuple can be inserted at the beginning if (this.elements.length == 0) { return 0 } var start = 0, end = this.elements.length / 2, sliceLength = end - start, pivotPoint = Math.floor(sliceLength / 2), pivotIndex = this.elements[pivotPoint * 2] while (sliceLength > 1) { if (pivotIndex < index) { start = pivotPoint } if (pivotIndex > index) { end = pivotPoint } if (pivotIndex == index) { break } sliceLength = end - start pivotPoint = start + Math.floor(sliceLength / 2) pivotIndex = this.elements[pivotPoint * 2] } if (pivotIndex == index) { return pivotPoint * 2 } if (pivotIndex > index) { return pivotPoint * 2 } if (pivotIndex < index) { return (pivotPoint + 1) * 2 } } /** * Inserts an element at an index within the vector. * * Does not allow duplicates, will throw an error if there is already an entry * for this index. * * @param {Number} insertIdx - The index at which the element should be inserted. * @param {Number} val - The value to be inserted into the vector. */ lunr.Vector.prototype.insert = function (insertIdx, val) { this.upsert(insertIdx, val, function () { throw "duplicate index" }) } /** * Inserts or updates an existing index within the vector. * * @param {Number} insertIdx - The index at which the element should be inserted. * @param {Number} val - The value to be inserted into the vector. * @param {function} fn - A function that is called for updates, the existing value and the * requested value are passed as arguments */ lunr.Vector.prototype.upsert = function (insertIdx, val, fn) { this._magnitude = 0 var position = this.positionForIndex(insertIdx) if (this.elements[position] == insertIdx) { this.elements[position + 1] = fn(this.elements[position + 1], val) } else { this.elements.splice(position, 0, insertIdx, val) } } /** * Calculates the magnitude of this vector. * * @returns {Number} */ lunr.Vector.prototype.magnitude = function () { if (this._magnitude) return this._magnitude var sumOfSquares = 0, elementsLength = this.elements.length for (var i = 1; i < elementsLength; i += 2) { var val = this.elements[i] sumOfSquares += val * val } return this._magnitude = Math.sqrt(sumOfSquares) } /** * Calculates the dot product of this vector and another vector. * * @param {lunr.Vector} otherVector - The vector to compute the dot product with. * @returns {Number} */ lunr.Vector.prototype.dot = function (otherVector) { var dotProduct = 0, a = this.elements, b = otherVector.elements, aLen = a.length, bLen = b.length, aVal = 0, bVal = 0, i = 0, j = 0 while (i < aLen && j < bLen) { aVal = a[i], bVal = b[j] if (aVal < bVal) { i += 2 } else if (aVal > bVal) { j += 2 } else if (aVal == bVal) { dotProduct += a[i + 1] * b[j + 1] i += 2 j += 2 } } return dotProduct } /** * Calculates the similarity between this vector and another vector. * * @param {lunr.Vector} otherVector - The other vector to calculate the * similarity with. * @returns {Number} */ lunr.Vector.prototype.similarity = function (otherVector) { return this.dot(otherVector) / this.magnitude() || 0 } /** * Converts the vector to an array of the elements within the vector. * * @returns {Number[]} */ lunr.Vector.prototype.toArray = function () { var output = new Array (this.elements.length / 2) for (var i = 1, j = 0; i < this.elements.length; i += 2, j++) { output[j] = this.elements[i] } return output } /** * A JSON serializable representation of the vector. * * @returns {Number[]} */ lunr.Vector.prototype.toJSON = function () { return this.elements } /* eslint-disable */ /*! * lunr.stemmer * Copyright (C) 2020 Oliver Nightingale * Includes code from - http://tartarus.org/~martin/PorterStemmer/js.txt */ /** * lunr.stemmer is an english language stemmer, this is a JavaScript * implementation of the PorterStemmer taken from http://tartarus.org/~martin * * @static * @implements {lunr.PipelineFunction} * @param {lunr.Token} token - The string to stem * @returns {lunr.Token} * @see {@link lunr.Pipeline} * @function */ lunr.stemmer = (function(){ var step2list = { "ational" : "ate", "tional" : "tion", "enci" : "ence", "anci" : "ance", "izer" : "ize", "bli" : "ble", "alli" : "al", "entli" : "ent", "eli" : "e", "ousli" : "ous", "ization" : "ize", "ation" : "ate", "ator" : "ate", "alism" : "al", "iveness" : "ive", "fulness" : "ful", "ousness" : "ous", "aliti" : "al", "iviti" : "ive", "biliti" : "ble", "logi" : "log" }, step3list = { "icate" : "ic", "ative" : "", "alize" : "al", "iciti" : "ic", "ical" : "ic", "ful" : "", "ness" : "" }, c = "[^aeiou]", // consonant v = "[aeiouy]", // vowel C = c + "[^aeiouy]*", // consonant sequence V = v + "[aeiou]*", // vowel sequence mgr0 = "^(" + C + ")?" + V + C, // [C]VC... is m>0 meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$", // [C]VC[V] is m=1 mgr1 = "^(" + C + ")?" + V + C + V + C, // [C]VCVC... is m>1 s_v = "^(" + C + ")?" + v; // vowel in stem var re_mgr0 = new RegExp(mgr0); var re_mgr1 = new RegExp(mgr1); var re_meq1 = new RegExp(meq1); var re_s_v = new RegExp(s_v); var re_1a = /^(.+?)(ss|i)es$/; var re2_1a = /^(.+?)([^s])s$/; var re_1b = /^(.+?)eed$/; var re2_1b = /^(.+?)(ed|ing)$/; var re_1b_2 = /.$/; var re2_1b_2 = /(at|bl|iz)$/; var re3_1b_2 = new RegExp("([^aeiouylsz])\\1$"); var re4_1b_2 = new RegExp("^" + C + v + "[^aeiouwxy]$"); var re_1c = /^(.+?[^aeiou])y$/; var re_2 = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; var re_3 = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; var re_4 = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; var re2_4 = /^(.+?)(s|t)(ion)$/; var re_5 = /^(.+?)e$/; var re_5_1 = /ll$/; var re3_5 = new RegExp("^" + C + v + "[^aeiouwxy]$"); var porterStemmer = function porterStemmer(w) { var stem, suffix, firstch, re, re2, re3, re4; if (w.length < 3) { return w; } firstch = w.substr(0,1); if (firstch == "y") { w = firstch.toUpperCase() + w.substr(1); } // Step 1a re = re_1a re2 = re2_1a; if (re.test(w)) { w = w.replace(re,"$1$2"); } else if (re2.test(w)) { w = w.replace(re2,"$1$2"); } // Step 1b re = re_1b; re2 = re2_1b; if (re.test(w)) { var fp = re.exec(w); re = re_mgr0; if (re.test(fp[1])) { re = re_1b_2; w = w.replace(re,""); } } else if (re2.test(w)) { var fp = re2.exec(w); stem = fp[1]; re2 = re_s_v; if (re2.test(stem)) { w = stem; re2 = re2_1b_2; re3 = re3_1b_2; re4 = re4_1b_2; if (re2.test(w)) { w = w + "e"; } else if (re3.test(w)) { re = re_1b_2; w = w.replace(re,""); } else if (re4.test(w)) { w = w + "e"; } } } // Step 1c - replace suffix y or Y by i if preceded by a non-vowel which is not the first letter of the word (so cry -> cri, by -> by, say -> say) re = re_1c; if (re.test(w)) { var fp = re.exec(w); stem = fp[1]; w = stem + "i"; } // Step 2 re = re_2; if (re.test(w)) { var fp = re.exec(w); stem = fp[1]; suffix = fp[2]; re = re_mgr0; if (re.test(stem)) { w = stem + step2list[suffix]; } } // Step 3 re = re_3; if (re.test(w)) { var fp = re.exec(w); stem = fp[1]; suffix = fp[2]; re = re_mgr0; if (re.test(stem)) { w = stem + step3list[suffix]; } } // Step 4 re = re_4; re2 = re2_4; if (re.test(w)) { var fp = re.exec(w); stem = fp[1]; re = re_mgr1; if (re.test(stem)) { w = stem; } } else if (re2.test(w)) { var fp = re2.exec(w); stem = fp[1] + fp[2]; re2 = re_mgr1; if (re2.test(stem)) { w = stem; } } // Step 5 re = re_5; if (re.test(w)) { var fp = re.exec(w); stem = fp[1]; re = re_mgr1; re2 = re_meq1; re3 = re3_5; if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) { w = stem; } } re = re_5_1; re2 = re_mgr1; if (re.test(w) && re2.test(w)) { re = re_1b_2; w = w.replace(re,""); } // and turn initial Y back to y if (firstch == "y") { w = firstch.toLowerCase() + w.substr(1); } return w; }; return function (token) { return token.update(porterStemmer); } })(); lunr.Pipeline.registerFunction(lunr.stemmer, 'stemmer') /*! * lunr.stopWordFilter * Copyright (C) 2020 Oliver Nightingale */ /** * lunr.generateStopWordFilter builds a stopWordFilter function from the provided * list of stop words. * * The built in lunr.stopWordFilter is built using this generator and can be used * to generate custom stopWordFilters for applications or non English languages. * * @function * @param {Array} token The token to pass through the filter * @returns {lunr.PipelineFunction} * @see lunr.Pipeline * @see lunr.stopWordFilter */ lunr.generateStopWordFilter = function (stopWords) { var words = stopWords.reduce(function (memo, stopWord) { memo[stopWord] = stopWord return memo }, {}) return function (token) { if (token && words[token.toString()] !== token.toString()) return token } } /** * lunr.stopWordFilter is an English language stop word list filter, any words * contained in the list will not be passed through the filter. * * This is intended to be used in the Pipeline. If the token does not pass the * filter then undefined will be returned. * * @function * @implements {lunr.PipelineFunction} * @params {lunr.Token} token - A token to check for being a stop word. * @returns {lunr.Token} * @see {@link lunr.Pipeline} */ lunr.stopWordFilter = lunr.generateStopWordFilter([ 'a', 'able', 'about', 'across', 'after', 'all', 'almost', 'also', 'am', 'among', 'an', 'and', 'any', 'are', 'as', 'at', 'be', 'because', 'been', 'but', 'by', 'can', 'cannot', 'could', 'dear', 'did', 'do', 'does', 'either', 'else', 'ever', 'every', 'for', 'from', 'get', 'got', 'had', 'has', 'have', 'he', 'her', 'hers', 'him', 'his', 'how', 'however', 'i', 'if', 'in', 'into', 'is', 'it', 'its', 'just', 'least', 'let', 'like', 'likely', 'may', 'me', 'might', 'most', 'must', 'my', 'neither', 'no', 'nor', 'not', 'of', 'off', 'often', 'on', 'only', 'or', 'other', 'our', 'own', 'rather', 'said', 'say', 'says', 'she', 'should', 'since', 'so', 'some', 'than', 'that', 'the', 'their', 'them', 'then', 'there', 'these', 'they', 'this', 'tis', 'to', 'too', 'twas', 'us', 'wants', 'was', 'we', 'were', 'what', 'when', 'where', 'which', 'while', 'who', 'whom', 'why', 'will', 'with', 'would', 'yet', 'you', 'your' ]) lunr.Pipeline.registerFunction(lunr.stopWordFilter, 'stopWordFilter') /*! * lunr.trimmer * Copyright (C) 2020 Oliver Nightingale */ /** * lunr.trimmer is a pipeline function for trimming non word * characters from the beginning and end of tokens before they * enter the index. * * This implementation may not work correctly for non latin * characters and should either be removed or adapted for use * with languages with non-latin characters. * * @static * @implements {lunr.PipelineFunction} * @param {lunr.Token} token The token to pass through the filter * @returns {lunr.Token} * @see lunr.Pipeline */ lunr.trimmer = function (token) { return token.update(function (s) { return s.replace(/^\W+/, '').replace(/\W+$/, '') }) } lunr.Pipeline.registerFunction(lunr.trimmer, 'trimmer') /*! * lunr.TokenSet * Copyright (C) 2020 Oliver Nightingale */ /** * A token set is used to store the unique list of all tokens * within an index. Token sets are also used to represent an * incoming query to the index, this query token set and index * token set are then intersected to find which tokens to look * up in the inverted index. * * A token set can hold multiple tokens, as in the case of the * index token set, or it can hold a single token as in the * case of a simple query token set. * * Additionally token sets are used to perform wildcard matching. * Leading, contained and trailing wildcards are supported, and * from this edit distance matching can also be provided. * * Token sets are implemented as a minimal finite state automata, * where both common prefixes and suffixes are shared between tokens. * This helps to reduce the space used for storing the token set. * * @constructor */ lunr.TokenSet = function () { this.final = false this.edges = {} this.id = lunr.TokenSet._nextId lunr.TokenSet._nextId += 1 } /** * Keeps track of the next, auto increment, identifier to assign * to a new tokenSet. * * TokenSets require a unique identifier to be correctly minimised. * * @private */ lunr.TokenSet._nextId = 1 /** * Creates a TokenSet instance from the given sorted array of words. * * @param {String[]} arr - A sorted array of strings to create the set from. * @returns {lunr.TokenSet} * @throws Will throw an error if the input array is not sorted. */ lunr.TokenSet.fromArray = function (arr) { var builder = new lunr.TokenSet.Builder for (var i = 0, len = arr.length; i < len; i++) { builder.insert(arr[i]) } builder.finish() return builder.root } /** * Creates a token set from a query clause. * * @private * @param {Object} clause - A single clause from lunr.Query. * @param {string} clause.term - The query clause term. * @param {number} [clause.editDistance] - The optional edit distance for the term. * @returns {lunr.TokenSet} */ lunr.TokenSet.fromClause = function (clause) { if ('editDistance' in clause) { return lunr.TokenSet.fromFuzzyString(clause.term, clause.editDistance) } else { return lunr.TokenSet.fromString(clause.term) } } /** * Creates a token set representing a single string with a specified * edit distance. * * Insertions, deletions, substitutions and transpositions are each * treated as an edit distance of 1. * * Increasing the allowed edit distance will have a dramatic impact * on the performance of both creating and intersecting these TokenSets. * It is advised to keep the edit distance less than 3. * * @param {string} str - The string to create the token set from. * @param {number} editDistance - The allowed edit distance to match. * @returns {lunr.Vector} */ lunr.TokenSet.fromFuzzyString = function (str, editDistance) { var root = new lunr.TokenSet var stack = [{ node: root, editsRemaining: editDistance, str: str }] while (stack.length) { var frame = stack.pop() // no edit if (frame.str.length > 0) { var char = frame.str.charAt(0), noEditNode if (char in frame.node.edges) { noEditNode = frame.node.edges[char] } else { noEditNode = new lunr.TokenSet frame.node.edges[char] = noEditNode } if (frame.str.length == 1) { noEditNode.final = true } stack.push({ node: noEditNode, editsRemaining: frame.editsRemaining, str: frame.str.slice(1) }) } if (frame.editsRemaining == 0) { continue } // insertion if ("*" in frame.node.edges) { var insertionNode = frame.node.edges["*"] } else { var insertionNode = new lunr.TokenSet frame.node.edges["*"] = insertionNode } if (frame.str.length == 0) { insertionNode.final = true } stack.push({ node: insertionNode, editsRemaining: frame.editsRemaining - 1, str: frame.str }) // deletion // can only do a deletion if we have enough edits remaining // and if there are characters left to delete in the string if (frame.str.length > 1) { stack.push({ node: frame.node, editsRemaining: frame.editsRemaining - 1, str: frame.str.slice(1) }) } // deletion // just removing the last character from the str if (frame.str.length == 1) { frame.node.final = true } // substitution // can only do a substitution if we have enough edits remaining // and if there are characters left to substitute if (frame.str.length >= 1) { if ("*" in frame.node.edges) { var substitutionNode = frame.node.edges["*"] } else { var substitutionNode = new lunr.TokenSet frame.node.edges["*"] = substitutionNode } if (frame.str.length == 1) { substitutionNode.final = true } stack.push({ node: substitutionNode, editsRemaining: frame.editsRemaining - 1, str: frame.str.slice(1) }) } // transposition // can only do a transposition if there are edits remaining // and there are enough characters to transpose if (frame.str.length > 1) { var charA = frame.str.charAt(0), charB = frame.str.charAt(1), transposeNode if (charB in frame.node.edges) { transposeNode = frame.node.edges[charB] } else { transposeNode = new lunr.TokenSet frame.node.edges[charB] = transposeNode } if (frame.str.length == 1) { transposeNode.final = true } stack.push({ node: transposeNode, editsRemaining: frame.editsRemaining - 1, str: charA + frame.str.slice(2) }) } } return root } /** * Creates a TokenSet from a string. * * The string may contain one or more wildcard characters (*) * that will allow wildcard matching when intersecting with * another TokenSet. * * @param {string} str - The string to create a TokenSet from. * @returns {lunr.TokenSet} */ lunr.TokenSet.fromString = function (str) { var node = new lunr.TokenSet, root = node /* * Iterates through all characters within the passed string * appending a node for each character. * * When a wildcard character is found then a self * referencing edge is introduced to continually match * any number of any characters. */ for (var i = 0, len = str.length; i < len; i++) { var char = str[i], final = (i == len - 1) if (char == "*") { node.edges[char] = node node.final = final } else { var next = new lunr.TokenSet next.final = final node.edges[char] = next node = next } } return root } /** * Converts this TokenSet into an array of strings * contained within the TokenSet. * * This is not intended to be used on a TokenSet that * contains wildcards, in these cases the results are * undefined and are likely to cause an infinite loop. * * @returns {string[]} */ lunr.TokenSet.prototype.toArray = function () { var words = [] var stack = [{ prefix: "", node: this }] while (stack.length) { var frame = stack.pop(), edges = Object.keys(frame.node.edges), len = edges.length if (frame.node.final) { /* In Safari, at this point the prefix is sometimes corrupted, see: * https://github.com/olivernn/lunr.js/issues/279 Calling any * String.prototype method forces Safari to "cast" this string to what * it's supposed to be, fixing the bug. */ frame.prefix.charAt(0) words.push(frame.prefix) } for (var i = 0; i < len; i++) { var edge = edges[i] stack.push({ prefix: frame.prefix.concat(edge), node: frame.node.edges[edge] }) } } return words } /** * Generates a string representation of a TokenSet. * * This is intended to allow TokenSets to be used as keys * in objects, largely to aid the construction and minimisation * of a TokenSet. As such it is not designed to be a human * friendly representation of the TokenSet. * * @returns {string} */ lunr.TokenSet.prototype.toString = function () { // NOTE: Using Object.keys here as this.edges is very likely // to enter 'hash-mode' with many keys being added // // avoiding a for-in loop here as it leads to the function // being de-optimised (at least in V8). From some simple // benchmarks the performance is comparable, but allowing // V8 to optimize may mean easy performance wins in the future. if (this._str) { return this._str } var str = this.final ? '1' : '0', labels = Object.keys(this.edges).sort(), len = labels.length for (var i = 0; i < len; i++) { var label = labels[i], node = this.edges[label] str = str + label + node.id } return str } /** * Returns a new TokenSet that is the intersection of * this TokenSet and the passed TokenSet. * * This intersection will take into account any wildcards * contained within the TokenSet. * * @param {lunr.TokenSet} b - An other TokenSet to intersect with. * @returns {lunr.TokenSet} */ lunr.TokenSet.prototype.intersect = function (b) { var output = new lunr.TokenSet, frame = undefined var stack = [{ qNode: b, output: output, node: this }] while (stack.length) { frame = stack.pop() // NOTE: As with the #toString method, we are using // Object.keys and a for loop instead of a for-in loop // as both of these objects enter 'hash' mode, causing // the function to be de-optimised in V8 var qEdges = Object.keys(frame.qNode.edges), qLen = qEdges.length, nEdges = Object.keys(frame.node.edges), nLen = nEdges.length for (var q = 0; q < qLen; q++) { var qEdge = qEdges[q] for (var n = 0; n < nLen; n++) { var nEdge = nEdges[n] if (nEdge == qEdge || qEdge == '*') { var node = frame.node.edges[nEdge], qNode = frame.qNode.edges[qEdge], final = node.final && qNode.final, next = undefined if (nEdge in frame.output.edges) { // an edge already exists for this character // no need to create a new node, just set the finality // bit unless this node is already final next = frame.output.edges[nEdge] next.final = next.final || final } else { // no edge exists yet, must create one // set the finality bit and insert it // into the output next = new lunr.TokenSet next.final = final frame.output.edges[nEdge] = next } stack.push({ qNode: qNode, output: next, node: node }) } } } } return output } lunr.TokenSet.Builder = function () { this.previousWord = "" this.root = new lunr.TokenSet this.uncheckedNodes = [] this.minimizedNodes = {} } lunr.TokenSet.Builder.prototype.insert = function (word) { var node, commonPrefix = 0 if (word < this.previousWord) { throw new Error ("Out of order word insertion") } for (var i = 0; i < word.length && i < this.previousWord.length; i++) { if (word[i] != this.previousWord[i]) break commonPrefix++ } this.minimize(commonPrefix) if (this.uncheckedNodes.length == 0) { node = this.root } else { node = this.uncheckedNodes[this.uncheckedNodes.length - 1].child } for (var i = commonPrefix; i < word.length; i++) { var nextNode = new lunr.TokenSet, char = word[i] node.edges[char] = nextNode this.uncheckedNodes.push({ parent: node, char: char, child: nextNode }) node = nextNode } node.final = true this.previousWord = word } lunr.TokenSet.Builder.prototype.finish = function () { this.minimize(0) } lunr.TokenSet.Builder.prototype.minimize = function (downTo) { for (var i = this.uncheckedNodes.length - 1; i >= downTo; i--) { var node = this.uncheckedNodes[i], childKey = node.child.toString() if (childKey in this.minimizedNodes) { node.parent.edges[node.char] = this.minimizedNodes[childKey] } else { // Cache the key for this node since // we know it can't change anymore node.child._str = childKey this.minimizedNodes[childKey] = node.child } this.uncheckedNodes.pop() } } /*! * lunr.Index * Copyright (C) 2020 Oliver Nightingale */ /** * An index contains the built index of all documents and provides a query interface * to the index. * * Usually instances of lunr.Index will not be created using this constructor, instead * lunr.Builder should be used to construct new indexes, or lunr.Index.load should be * used to load previously built and serialized indexes. * * @constructor * @param {Object} attrs - The attributes of the built search index. * @param {Object} attrs.invertedIndex - An index of term/field to document reference. * @param {Object<string, lunr.Vector>} attrs.fieldVectors - Field vectors * @param {lunr.TokenSet} attrs.tokenSet - An set of all corpus tokens. * @param {string[]} attrs.fields - The names of indexed document fields. * @param {lunr.Pipeline} attrs.pipeline - The pipeline to use for search terms. */ lunr.Index = function (attrs) { this.invertedIndex = attrs.invertedIndex this.fieldVectors = attrs.fieldVectors this.tokenSet = attrs.tokenSet this.fields = attrs.fields this.pipeline = attrs.pipeline } /** * A result contains details of a document matching a search query. * @typedef {Object} lunr.Index~Result * @property {string} ref - The reference of the document this result represents. * @property {number} score - A number between 0 and 1 representing how similar this document is to the query. * @property {lunr.MatchData} matchData - Contains metadata about this match including which term(s) caused the match. */ /** * Although lunr provides the ability to create queries using lunr.Query, it also provides a simple * query language which itself is parsed into an instance of lunr.Query. * * For programmatically building queries it is advised to directly use lunr.Query, the query language * is best used for human entered text rather than program generated text. * * At its simplest queries can just be a single term, e.g. `hello`, multiple terms are also supported * and will be combined with OR, e.g `hello world` will match documents that contain either 'hello' * or 'world', though those that contain both will rank higher in the results. * * Wildcards can be included in terms to match one or more unspecified characters, these wildcards can * be inserted anywhere within the term, and more than one wildcard can exist in a single term. Adding * wildcards will increase the number of documents that will be found but can also have a negative * impact on query performance, especially with wildcards at the beginning of a term. * * Terms can be restricted to specific fields, e.g. `title:hello`, only documents with the term * hello in the title field will match this query. Using a field not present in the index will lead * to an error being thrown. * * Modifiers can also be added to terms, lunr supports edit distance and boost modifiers on terms. A term * boost will make documents matching that term score higher, e.g. `foo^5`. Edit distance is also supported * to provide fuzzy matching, e.g. 'hello~2' will match documents with hello with an edit distance of 2. * Avoid large values for edit distance to improve query performance. * * Each term also supports a presence modifier. By default a term's presence in document is optional, however * this can be changed to either required or prohibited. For a term's presence to be required in a document the * term should be prefixed with a '+', e.g. `+foo bar` is a search for documents that must contain 'foo' and * optionally contain 'bar'. Conversely a leading '-' sets the terms presence to prohibited, i.e. it must not * appear in a document, e.g. `-foo bar` is a search for documents that do not contain 'foo' but may contain 'bar'. * * To escape special characters the backslash character '\' can be used, this allows searches to include * characters that would normally be considered modifiers, e.g. `foo\~2` will search for a term "foo~2" instead * of attempting to apply a boost of 2 to the search term "foo". * * @typedef {string} lunr.Index~QueryString * @example <caption>Simple single term query</caption> * hello * @example <caption>Multiple term query</caption> * hello world * @example <caption>term scoped to a field</caption> * title:hello * @example <caption>term with a boost of 10</caption> * hello^10 * @example <caption>term with an edit distance of 2</caption> * hello~2 * @example <caption>terms with presence modifiers</caption> * -foo +bar baz */ /** * Performs a search against the index using lunr query syntax. * * Results will be returned sorted by their score, the most relevant results * will be returned first. For details on how the score is calculated, please see * the {@link https://lunrjs.com/guides/searching.html#scoring|guide}. * * For more programmatic querying use lunr.Index#query. * * @param {lunr.Index~QueryString} queryString - A string containing a lunr query. * @throws {lunr.QueryParseError} If the passed query string cannot be parsed. * @returns {lunr.Index~Result[]} */ lunr.Index.prototype.search = function (queryString) { return this.query(function (query) { var parser = new lunr.QueryParser(queryString, query) parser.parse() }) } /** * A query builder callback provides a query object to be used to express * the query to perform on the index. * * @callback lunr.Index~queryBuilder * @param {lunr.Query} query - The query object to build up. * @this lunr.Query */ /** * Performs a query against the index using the yielded lunr.Query object. * * If performing programmatic queries against the index, this method is preferred * over lunr.Index#search so as to avoid the additional query parsing overhead. * * A query object is yielded to the supplied function which should be used to * express the query to be run against the index. * * Note that although this function takes a callback parameter it is _not_ an * asynchronous operation, the callback is just yielded a query object to be * customized. * * @param {lunr.Index~queryBuilder} fn - A function that is used to build the query. * @returns {lunr.Index~Result[]} */ lunr.Index.prototype.query = function (fn) { // for each query clause // * process terms // * expand terms from token set // * find matching documents and metadata // * get document vectors // * score documents var query = new lunr.Query(this.fields), matchingFields = Object.create(null), queryVectors = Object.create(null), termFieldCache = Object.create(null), requiredMatches = Object.create(null), prohibitedMatches = Object.create(null) /* * To support field level boosts a query vector is created per * field. An empty vector is eagerly created to support negated * queries. */ for (var i = 0; i < this.fields.length; i++) { queryVectors[this.fields[i]] = new lunr.Vector } fn.call(query, query) for (var i = 0; i < query.clauses.length; i++) { /* * Unless the pipeline has been disabled for this term, which is * the case for terms with wildcards, we need to pass the clause * term through the search pipeline. A pipeline returns an array * of processed terms. Pipeline functions may expand the passed * term, which means we may end up performing multiple index lookups * for a single query term. */ var clause = query.clauses[i], terms = null, clauseMatches = lunr.Set.empty if (clause.usePipeline) { terms = this.pipeline.runString(clause.term, { fields: clause.fields }) } else { terms = [clause.term] } for (var m = 0; m < terms.length; m++) { var term = terms[m] /* * Each term returned from the pipeline needs to use the same query * clause object, e.g. the same boost and or edit distance. The * simplest way to do this is to re-use the clause object but mutate * its term property. */ clause.term = term /* * From the term in the clause we create a token set which will then * be used to intersect the indexes token set to get a list of terms * to lookup in the inverted index */ var termTokenSet = lunr.TokenSet.fromClause(clause), expandedTerms = this.tokenSet.intersect(termTokenSet).toArray() /* * If a term marked as required does not exist in the tokenSet it is * impossible for the search to return any matches. We set all the field * scoped required matches set to empty and stop examining any further * clauses. */ if (expandedTerms.length === 0 && clause.presence === lunr.Query.presence.REQUIRED) { for (var k = 0; k < clause.fields.length; k++) { var field = clause.fields[k] requiredMatches[field] = lunr.Set.empty } break } for (var j = 0; j < expandedTerms.length; j++) { /* * For each term get the posting and termIndex, this is required for * building the query vector. */ var expandedTerm = expandedTerms[j], posting = this.invertedIndex[expandedTerm], termIndex = posting._index for (var k = 0; k < clause.fields.length; k++) { /* * For each field that this query term is scoped by (by default * all fields are in scope) we need to get all the document refs * that have this term in that field. * * The posting is the entry in the invertedIndex for the matching * term from above. */ var field = clause.fields[k], fieldPosting = posting[field], matchingDocumentRefs = Object.keys(fieldPosting), termField = expandedTerm + "/" + field, matchingDocumentsSet = new lunr.Set(matchingDocumentRefs) /* * if the presence of this term is required ensure that the matching * documents are added to the set of required matches for this clause. * */ if (clause.presence == lunr.Query.presence.REQUIRED) { clauseMatches = clauseMatches.union(matchingDocumentsSet) if (requiredMatches[field] === undefined) { requiredMatches[field] = lunr.Set.complete } } /* * if the presence of this term is prohibited ensure that the matching * documents are added to the set of prohibited matches for this field, * creating that set if it does not yet exist. */ if (clause.presence == lunr.Query.presence.PROHIBITED) { if (prohibitedMatches[field] === undefined) { prohibitedMatches[field] = lunr.Set.empty } prohibitedMatches[field] = prohibitedMatches[field].union(matchingDocumentsSet) /* * Prohibited matches should not be part of the query vector used for * similarity scoring and no metadata should be extracted so we continue * to the next field */ continue } /* * The query field vector is populated using the termIndex found for * the term and a unit value with the appropriate boost applied. * Using upsert because there could already be an entry in the vector * for the term we are working with. In that case we just add the scores * together. */ queryVectors[field].upsert(termIndex, clause.boost, function (a, b) { return a + b }) /** * If we've already seen this term, field combo then we've already collected * the matching documents and metadata, no need to go through all that again */ if (termFieldCache[termField]) { continue } for (var l = 0; l < matchingDocumentRefs.length; l++) { /* * All metadata for this term/field/document triple * are then extracted and collected into an instance * of lunr.MatchData ready to be returned in the query * results */ var matchingDocumentRef = matchingDocumentRefs[l], matchingFieldRef = new lunr.FieldRef (matchingDocumentRef, field), metadata = fieldPosting[matchingDocumentRef], fieldMatch if ((fieldMatch = matchingFields[matchingFieldRef]) === undefined) { matchingFields[matchingFieldRef] = new lunr.MatchData (expandedTerm, field, metadata) } else { fieldMatch.add(expandedTerm, field, metadata) } } termFieldCache[termField] = true } } } /** * If the presence was required we need to update the requiredMatches field sets. * We do this after all fields for the term have collected their matches because * the clause terms presence is required in _any_ of the fields not _all_ of the * fields. */ if (clause.presence === lunr.Query.presence.REQUIRED) { for (var k = 0; k < clause.fields.length; k++) { var field = clause.fields[k] requiredMatches[field] = requiredMatches[field].intersect(clauseMatches) } } } /** * Need to combine the field scoped required and prohibited * matching documents into a global set of required and prohibited * matches */ var allRequiredMatches = lunr.Set.complete, allProhibitedMatches = lunr.Set.empty for (var i = 0; i < this.fields.length; i++) { var field = this.fields[i] if (requiredMatches[field]) { allRequiredMatches = allRequiredMatches.intersect(requiredMatches[field]) } if (prohibitedMatches[field]) { allProhibitedMatches = allProhibitedMatches.union(prohibitedMatches[field]) } } var matchingFieldRefs = Object.keys(matchingFields), results = [], matches = Object.create(null) /* * If the query is negated (contains only prohibited terms) * we need to get _all_ fieldRefs currently existing in the * index. This is only done when we know that the query is * entirely prohibited terms to avoid any cost of getting all * fieldRefs unnecessarily. * * Additionally, blank MatchData must be created to correctly * populate the results. */ if (query.isNegated()) { matchingFieldRefs = Object.keys(this.fieldVectors) for (var i = 0; i < matchingFieldRefs.length; i++) { var matchingFieldRef = matchingFieldRefs[i] var fieldRef = lunr.FieldRef.fromString(matchingFieldRef) matchingFields[matchingFieldRef] = new lunr.MatchData } } for (var i = 0; i < matchingFieldRefs.length; i++) { /* * Currently we have document fields that match the query, but we * need to return documents. The matchData and scores are combined * from multiple fields belonging to the same document. * * Scores are calculated by field, using the query vectors created * above, and combined into a final document score using addition. */ var fieldRef = lunr.FieldRef.fromString(matchingFieldRefs[i]), docRef = fieldRef.docRef if (!allRequiredMatches.contains(docRef)) { continue } if (allProhibitedMatches.contains(docRef)) { continue } var fieldVector = this.fieldVectors[fieldRef], score = queryVectors[fieldRef.fieldName].similarity(fieldVector), docMatch if ((docMatch = matches[docRef]) !== undefined) { docMatch.score += score docMatch.matchData.combine(matchingFields[fieldRef]) } else { var match = { ref: docRef, score: score, matchData: matchingFields[fieldRef] } matches[docRef] = match results.push(match) } } /* * Sort the results objects by score, highest first. */ return results.sort(function (a, b) { return b.score - a.score }) } /** * Prepares the index for JSON serialization. * * The schema for this JSON blob will be described in a * separate JSON schema file. * * @returns {Object} */ lunr.Index.prototype.toJSON = function () { var invertedIndex = Object.keys(this.invertedIndex) .sort() .map(function (term) { return [term, this.invertedIndex[term]] }, this) var fieldVectors = Object.keys(this.fieldVectors) .map(function (ref) { return [ref, this.fieldVectors[ref].toJSON()] }, this) return { version: lunr.version, fields: this.fields, fieldVectors: fieldVectors, invertedIndex: invertedIndex, pipeline: this.pipeline.toJSON() } } /** * Loads a previously serialized lunr.Index * * @param {Object} serializedIndex - A previously serialized lunr.Index * @returns {lunr.Index} */ lunr.Index.load = function (serializedIndex) { var attrs = {}, fieldVectors = {}, serializedVectors = serializedIndex.fieldVectors, invertedIndex = Object.create(null), serializedInvertedIndex = serializedIndex.invertedIndex, tokenSetBuilder = new lunr.TokenSet.Builder, pipeline = lunr.Pipeline.load(serializedIndex.pipeline) if (serializedIndex.version != lunr.version) { lunr.utils.warn("Version mismatch when loading serialised index. Current version of lunr '" + lunr.version + "' does not match serialized index '" + serializedIndex.version + "'") } for (var i = 0; i < serializedVectors.length; i++) { var tuple = serializedVectors[i], ref = tuple[0], elements = tuple[1] fieldVectors[ref] = new lunr.Vector(elements) } for (var i = 0; i < serializedInvertedIndex.length; i++) { var tuple = serializedInvertedIndex[i], term = tuple[0], posting = tuple[1] tokenSetBuilder.insert(term) invertedIndex[term] = posting } tokenSetBuilder.finish() attrs.fields = serializedIndex.fields attrs.fieldVectors = fieldVectors attrs.invertedIndex = invertedIndex attrs.tokenSet = tokenSetBuilder.root attrs.pipeline = pipeline return new lunr.Index(attrs) } /*! * lunr.Builder * Copyright (C) 2020 Oliver Nightingale */ /** * lunr.Builder performs indexing on a set of documents and * returns instances of lunr.Index ready for querying. * * All configuration of the index is done via the builder, the * fields to index, the document reference, the text processing * pipeline and document scoring parameters are all set on the * builder before indexing. * * @constructor * @property {string} _ref - Internal reference to the document reference field. * @property {string[]} _fields - Internal reference to the document fields to index. * @property {object} invertedIndex - The inverted index maps terms to document fields. * @property {object} documentTermFrequencies - Keeps track of document term frequencies. * @property {object} documentLengths - Keeps track of the length of documents added to the index. * @property {lunr.tokenizer} tokenizer - Function for splitting strings into tokens for indexing. * @property {lunr.Pipeline} pipeline - The pipeline performs text processing on tokens before indexing. * @property {lunr.Pipeline} searchPipeline - A pipeline for processing search terms before querying the index. * @property {number} documentCount - Keeps track of the total number of documents indexed. * @property {number} _b - A parameter to control field length normalization, setting this to 0 disabled normalization, 1 fully normalizes field lengths, the default value is 0.75. * @property {number} _k1 - A parameter to control how quickly an increase in term frequency results in term frequency saturation, the default value is 1.2. * @property {number} termIndex - A counter incremented for each unique term, used to identify a terms position in the vector space. * @property {array} metadataWhitelist - A list of metadata keys that have been whitelisted for entry in the index. */ lunr.Builder = function () { this._ref = "id" this._fields = Object.create(null) this._documents = Object.create(null) this.invertedIndex = Object.create(null) this.fieldTermFrequencies = {} this.fieldLengths = {} this.tokenizer = lunr.tokenizer this.pipeline = new lunr.Pipeline this.searchPipeline = new lunr.Pipeline this.documentCount = 0 this._b = 0.75 this._k1 = 1.2 this.termIndex = 0 this.metadataWhitelist = [] } /** * Sets the document field used as the document reference. Every document must have this field. * The type of this field in the document should be a string, if it is not a string it will be * coerced into a string by calling toString. * * The default ref is 'id'. * * The ref should _not_ be changed during indexing, it should be set before any documents are * added to the index. Changing it during indexing can lead to inconsistent results. * * @param {string} ref - The name of the reference field in the document. */ lunr.Builder.prototype.ref = function (ref) { this._ref = ref } /** * A function that is used to extract a field from a document. * * Lunr expects a field to be at the top level of a document, if however the field * is deeply nested within a document an extractor function can be used to extract * the right field for indexing. * * @callback fieldExtractor * @param {object} doc - The document being added to the index. * @returns {?(string|object|object[])} obj - The object that will be indexed for this field. * @example <caption>Extracting a nested field</caption> * function (doc) { return doc.nested.field } */ /** * Adds a field to the list of document fields that will be indexed. Every document being * indexed should have this field. Null values for this field in indexed documents will * not cause errors but will limit the chance of that document being retrieved by searches. * * All fields should be added before adding documents to the index. Adding fields after * a document has been indexed will have no effect on already indexed documents. * * Fields can be boosted at build time. This allows terms within that field to have more * importance when ranking search results. Use a field boost to specify that matches within * one field are more important than other fields. * * @param {string} fieldName - The name of a field to index in all documents. * @param {object} attributes - Optional attributes associated with this field. * @param {number} [attributes.boost=1] - Boost applied to all terms within this field. * @param {fieldExtractor} [attributes.extractor] - Function to extract a field from a document. * @throws {RangeError} fieldName cannot contain unsupported characters '/' */ lunr.Builder.prototype.field = function (fieldName, attributes) { if (/\//.test(fieldName)) { throw new RangeError ("Field '" + fieldName + "' contains illegal character '/'") } this._fields[fieldName] = attributes || {} } /** * A parameter to tune the amount of field length normalisation that is applied when * calculating relevance scores. A value of 0 will completely disable any normalisation * and a value of 1 will fully normalise field lengths. The default is 0.75. Values of b * will be clamped to the range 0 - 1. * * @param {number} number - The value to set for this tuning parameter. */ lunr.Builder.prototype.b = function (number) { if (number < 0) { this._b = 0 } else if (number > 1) { this._b = 1 } else { this._b = number } } /** * A parameter that controls the speed at which a rise in term frequency results in term * frequency saturation. The default value is 1.2. Setting this to a higher value will give * slower saturation levels, a lower value will result in quicker saturation. * * @param {number} number - The value to set for this tuning parameter. */ lunr.Builder.prototype.k1 = function (number) { this._k1 = number } /** * Adds a document to the index. * * Before adding fields to the index the index should have been fully setup, with the document * ref and all fields to index already having been specified. * * The document must have a field name as specified by the ref (by default this is 'id') and * it should have all fields defined for indexing, though null or undefined values will not * cause errors. * * Entire documents can be boosted at build time. Applying a boost to a document indicates that * this document should rank higher in search results than other documents. * * @param {object} doc - The document to add to the index. * @param {object} attributes - Optional attributes associated with this document. * @param {number} [attributes.boost=1] - Boost applied to all terms within this document. */ lunr.Builder.prototype.add = function (doc, attributes) { var docRef = doc[this._ref], fields = Object.keys(this._fields) this._documents[docRef] = attributes || {} this.documentCount += 1 for (var i = 0; i < fields.length; i++) { var fieldName = fields[i], extractor = this._fields[fieldName].extractor, field = extractor ? extractor(doc) : doc[fieldName], tokens = this.tokenizer(field, { fields: [fieldName] }), terms = this.pipeline.run(tokens), fieldRef = new lunr.FieldRef (docRef, fieldName), fieldTerms = Object.create(null) this.fieldTermFrequencies[fieldRef] = fieldTerms this.fieldLengths[fieldRef] = 0 // store the length of this field for this document this.fieldLengths[fieldRef] += terms.length // calculate term frequencies for this field for (var j = 0; j < terms.length; j++) { var term = terms[j] if (fieldTerms[term] == undefined) { fieldTerms[term] = 0 } fieldTerms[term] += 1 // add to inverted index // create an initial posting if one doesn't exist if (this.invertedIndex[term] == undefined) { var posting = Object.create(null) posting["_index"] = this.termIndex this.termIndex += 1 for (var k = 0; k < fields.length; k++) { posting[fields[k]] = Object.create(null) } this.invertedIndex[term] = posting } // add an entry for this term/fieldName/docRef to the invertedIndex if (this.invertedIndex[term][fieldName][docRef] == undefined) { this.invertedIndex[term][fieldName][docRef] = Object.create(null) } // store all whitelisted metadata about this token in the // inverted index for (var l = 0; l < this.metadataWhitelist.length; l++) { var metadataKey = this.metadataWhitelist[l], metadata = term.metadata[metadataKey] if (this.invertedIndex[term][fieldName][docRef][metadataKey] == undefined) { this.invertedIndex[term][fieldName][docRef][metadataKey] = [] } this.invertedIndex[term][fieldName][docRef][metadataKey].push(metadata) } } } } /** * Calculates the average document length for this index * * @private */ lunr.Builder.prototype.calculateAverageFieldLengths = function () { var fieldRefs = Object.keys(this.fieldLengths), numberOfFields = fieldRefs.length, accumulator = {}, documentsWithField = {} for (var i = 0; i < numberOfFields; i++) { var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]), field = fieldRef.fieldName documentsWithField[field] || (documentsWithField[field] = 0) documentsWithField[field] += 1 accumulator[field] || (accumulator[field] = 0) accumulator[field] += this.fieldLengths[fieldRef] } var fields = Object.keys(this._fields) for (var i = 0; i < fields.length; i++) { var fieldName = fields[i] accumulator[fieldName] = accumulator[fieldName] / documentsWithField[fieldName] } this.averageFieldLength = accumulator } /** * Builds a vector space model of every document using lunr.Vector * * @private */ lunr.Builder.prototype.createFieldVectors = function () { var fieldVectors = {}, fieldRefs = Object.keys(this.fieldTermFrequencies), fieldRefsLength = fieldRefs.length, termIdfCache = Object.create(null) for (var i = 0; i < fieldRefsLength; i++) { var fieldRef = lunr.FieldRef.fromString(fieldRefs[i]), fieldName = fieldRef.fieldName, fieldLength = this.fieldLengths[fieldRef], fieldVector = new lunr.Vector, termFrequencies = this.fieldTermFrequencies[fieldRef], terms = Object.keys(termFrequencies), termsLength = terms.length var fieldBoost = this._fields[fieldName].boost || 1, docBoost = this._documents[fieldRef.docRef].boost || 1 for (var j = 0; j < termsLength; j++) { var term = terms[j], tf = termFrequencies[term], termIndex = this.invertedIndex[term]._index, idf, score, scoreWithPrecision if (termIdfCache[term] === undefined) { idf = lunr.idf(this.invertedIndex[term], this.documentCount) termIdfCache[term] = idf } else { idf = termIdfCache[term] } score = idf * ((this._k1 + 1) * tf) / (this._k1 * (1 - this._b + this._b * (fieldLength / this.averageFieldLength[fieldName])) + tf) score *= fieldBoost score *= docBoost scoreWithPrecision = Math.round(score * 1000) / 1000 // Converts 1.23456789 to 1.234. // Reducing the precision so that the vectors take up less // space when serialised. Doing it now so that they behave // the same before and after serialisation. Also, this is // the fastest approach to reducing a number's precision in // JavaScript. fieldVector.insert(termIndex, scoreWithPrecision) } fieldVectors[fieldRef] = fieldVector } this.fieldVectors = fieldVectors } /** * Creates a token set of all tokens in the index using lunr.TokenSet * * @private */ lunr.Builder.prototype.createTokenSet = function () { this.tokenSet = lunr.TokenSet.fromArray( Object.keys(this.invertedIndex).sort() ) } /** * Builds the index, creating an instance of lunr.Index. * * This completes the indexing process and should only be called * once all documents have been added to the index. * * @returns {lunr.Index} */ lunr.Builder.prototype.build = function () { this.calculateAverageFieldLengths() this.createFieldVectors() this.createTokenSet() return new lunr.Index({ invertedIndex: this.invertedIndex, fieldVectors: this.fieldVectors, tokenSet: this.tokenSet, fields: Object.keys(this._fields), pipeline: this.searchPipeline }) } /** * Applies a plugin to the index builder. * * A plugin is a function that is called with the index builder as its context. * Plugins can be used to customise or extend the behaviour of the index * in some way. A plugin is just a function, that encapsulated the custom * behaviour that should be applied when building the index. * * The plugin function will be called with the index builder as its argument, additional * arguments can also be passed when calling use. The function will be called * with the index builder as its context. * * @param {Function} plugin The plugin to apply. */ lunr.Builder.prototype.use = function (fn) { var args = Array.prototype.slice.call(arguments, 1) args.unshift(this) fn.apply(this, args) } /** * Contains and collects metadata about a matching document. * A single instance of lunr.MatchData is returned as part of every * lunr.Index~Result. * * @constructor * @param {string} term - The term this match data is associated with * @param {string} field - The field in which the term was found * @param {object} metadata - The metadata recorded about this term in this field * @property {object} metadata - A cloned collection of metadata associated with this document. * @see {@link lunr.Index~Result} */ lunr.MatchData = function (term, field, metadata) { var clonedMetadata = Object.create(null), metadataKeys = Object.keys(metadata || {}) // Cloning the metadata to prevent the original // being mutated during match data combination. // Metadata is kept in an array within the inverted // index so cloning the data can be done with // Array#slice for (var i = 0; i < metadataKeys.length; i++) { var key = metadataKeys[i] clonedMetadata[key] = metadata[key].slice() } this.metadata = Object.create(null) if (term !== undefined) { this.metadata[term] = Object.create(null) this.metadata[term][field] = clonedMetadata } } /** * An instance of lunr.MatchData will be created for every term that matches a * document. However only one instance is required in a lunr.Index~Result. This * method combines metadata from another instance of lunr.MatchData with this * objects metadata. * * @param {lunr.MatchData} otherMatchData - Another instance of match data to merge with this one. * @see {@link lunr.Index~Result} */ lunr.MatchData.prototype.combine = function (otherMatchData) { var terms = Object.keys(otherMatchData.metadata) for (var i = 0; i < terms.length; i++) { var term = terms[i], fields = Object.keys(otherMatchData.metadata[term]) if (this.metadata[term] == undefined) { this.metadata[term] = Object.create(null) } for (var j = 0; j < fields.length; j++) { var field = fields[j], keys = Object.keys(otherMatchData.metadata[term][field]) if (this.metadata[term][field] == undefined) { this.metadata[term][field] = Object.create(null) } for (var k = 0; k < keys.length; k++) { var key = keys[k] if (this.metadata[term][field][key] == undefined) { this.metadata[term][field][key] = otherMatchData.metadata[term][field][key] } else { this.metadata[term][field][key] = this.metadata[term][field][key].concat(otherMatchData.metadata[term][field][key]) } } } } } /** * Add metadata for a term/field pair to this instance of match data. * * @param {string} term - The term this match data is associated with * @param {string} field - The field in which the term was found * @param {object} metadata - The metadata recorded about this term in this field */ lunr.MatchData.prototype.add = function (term, field, metadata) { if (!(term in this.metadata)) { this.metadata[term] = Object.create(null) this.metadata[term][field] = metadata return } if (!(field in this.metadata[term])) { this.metadata[term][field] = metadata return } var metadataKeys = Object.keys(metadata) for (var i = 0; i < metadataKeys.length; i++) { var key = metadataKeys[i] if (key in this.metadata[term][field]) { this.metadata[term][field][key] = this.metadata[term][field][key].concat(metadata[key]) } else { this.metadata[term][field][key] = metadata[key] } } } /** * A lunr.Query provides a programmatic way of defining queries to be performed * against a {@link lunr.Index}. * * Prefer constructing a lunr.Query using the {@link lunr.Index#query} method * so the query object is pre-initialized with the right index fields. * * @constructor * @property {lunr.Query~Clause[]} clauses - An array of query clauses. * @property {string[]} allFields - An array of all available fields in a lunr.Index. */ lunr.Query = function (allFields) { this.clauses = [] this.allFields = allFields } /** * Constants for indicating what kind of automatic wildcard insertion will be used when constructing a query clause. * * This allows wildcards to be added to the beginning and end of a term without having to manually do any string * concatenation. * * The wildcard constants can be bitwise combined to select both leading and trailing wildcards. * * @constant * @default * @property {number} wildcard.NONE - The term will have no wildcards inserted, this is the default behaviour * @property {number} wildcard.LEADING - Prepend the term with a wildcard, unless a leading wildcard already exists * @property {number} wildcard.TRAILING - Append a wildcard to the term, unless a trailing wildcard already exists * @see lunr.Query~Clause * @see lunr.Query#clause * @see lunr.Query#term * @example <caption>query term with trailing wildcard</caption> * query.term('foo', { wildcard: lunr.Query.wildcard.TRAILING }) * @example <caption>query term with leading and trailing wildcard</caption> * query.term('foo', { * wildcard: lunr.Query.wildcard.LEADING | lunr.Query.wildcard.TRAILING * }) */ lunr.Query.wildcard = new String ("*") lunr.Query.wildcard.NONE = 0 lunr.Query.wildcard.LEADING = 1 lunr.Query.wildcard.TRAILING = 2 /** * Constants for indicating what kind of presence a term must have in matching documents. * * @constant * @enum {number} * @see lunr.Query~Clause * @see lunr.Query#clause * @see lunr.Query#term * @example <caption>query term with required presence</caption> * query.term('foo', { presence: lunr.Query.presence.REQUIRED }) */ lunr.Query.presence = { /** * Term's presence in a document is optional, this is the default value. */ OPTIONAL: 1, /** * Term's presence in a document is required, documents that do not contain * this term will not be returned. */ REQUIRED: 2, /** * Term's presence in a document is prohibited, documents that do contain * this term will not be returned. */ PROHIBITED: 3 } /** * A single clause in a {@link lunr.Query} contains a term and details on how to * match that term against a {@link lunr.Index}. * * @typedef {Object} lunr.Query~Clause * @property {string[]} fields - The fields in an index this clause should be matched against. * @property {number} [boost=1] - Any boost that should be applied when matching this clause. * @property {number} [editDistance] - Whether the term should have fuzzy matching applied, and how fuzzy the match should be. * @property {boolean} [usePipeline] - Whether the term should be passed through the search pipeline. * @property {number} [wildcard=lunr.Query.wildcard.NONE] - Whether the term should have wildcards appended or prepended. * @property {number} [presence=lunr.Query.presence.OPTIONAL] - The terms presence in any matching documents. */ /** * Adds a {@link lunr.Query~Clause} to this query. * * Unless the clause contains the fields to be matched all fields will be matched. In addition * a default boost of 1 is applied to the clause. * * @param {lunr.Query~Clause} clause - The clause to add to this query. * @see lunr.Query~Clause * @returns {lunr.Query} */ lunr.Query.prototype.clause = function (clause) { if (!('fields' in clause)) { clause.fields = this.allFields } if (!('boost' in clause)) { clause.boost = 1 } if (!('usePipeline' in clause)) { clause.usePipeline = true } if (!('wildcard' in clause)) { clause.wildcard = lunr.Query.wildcard.NONE } if ((clause.wildcard & lunr.Query.wildcard.LEADING) && (clause.term.charAt(0) != lunr.Query.wildcard)) { clause.term = "*" + clause.term } if ((clause.wildcard & lunr.Query.wildcard.TRAILING) && (clause.term.slice(-1) != lunr.Query.wildcard)) { clause.term = "" + clause.term + "*" } if (!('presence' in clause)) { clause.presence = lunr.Query.presence.OPTIONAL } this.clauses.push(clause) return this } /** * A negated query is one in which every clause has a presence of * prohibited. These queries require some special processing to return * the expected results. * * @returns boolean */ lunr.Query.prototype.isNegated = function () { for (var i = 0; i < this.clauses.length; i++) { if (this.clauses[i].presence != lunr.Query.presence.PROHIBITED) { return false } } return true } /** * Adds a term to the current query, under the covers this will create a {@link lunr.Query~Clause} * to the list of clauses that make up this query. * * The term is used as is, i.e. no tokenization will be performed by this method. Instead conversion * to a token or token-like string should be done before calling this method. * * The term will be converted to a string by calling `toString`. Multiple terms can be passed as an * array, each term in the array will share the same options. * * @param {object|object[]} term - The term(s) to add to the query. * @param {object} [options] - Any additional properties to add to the query clause. * @returns {lunr.Query} * @see lunr.Query#clause * @see lunr.Query~Clause * @example <caption>adding a single term to a query</caption> * query.term("foo") * @example <caption>adding a single term to a query and specifying search fields, term boost and automatic trailing wildcard</caption> * query.term("foo", { * fields: ["title"], * boost: 10, * wildcard: lunr.Query.wildcard.TRAILING * }) * @example <caption>using lunr.tokenizer to convert a string to tokens before using them as terms</caption> * query.term(lunr.tokenizer("foo bar")) */ lunr.Query.prototype.term = function (term, options) { if (Array.isArray(term)) { term.forEach(function (t) { this.term(t, lunr.utils.clone(options)) }, this) return this } var clause = options || {} clause.term = term.toString() this.clause(clause) return this } lunr.QueryParseError = function (message, start, end) { this.name = "QueryParseError" this.message = message this.start = start this.end = end } lunr.QueryParseError.prototype = new Error lunr.QueryLexer = function (str) { this.lexemes = [] this.str = str this.length = str.length this.pos = 0 this.start = 0 this.escapeCharPositions = [] } lunr.QueryLexer.prototype.run = function () { var state = lunr.QueryLexer.lexText while (state) { state = state(this) } } lunr.QueryLexer.prototype.sliceString = function () { var subSlices = [], sliceStart = this.start, sliceEnd = this.pos for (var i = 0; i < this.escapeCharPositions.length; i++) { sliceEnd = this.escapeCharPositions[i] subSlices.push(this.str.slice(sliceStart, sliceEnd)) sliceStart = sliceEnd + 1 } subSlices.push(this.str.slice(sliceStart, this.pos)) this.escapeCharPositions.length = 0 return subSlices.join('') } lunr.QueryLexer.prototype.emit = function (type) { this.lexemes.push({ type: type, str: this.sliceString(), start: this.start, end: this.pos }) this.start = this.pos } lunr.QueryLexer.prototype.escapeCharacter = function () { this.escapeCharPositions.push(this.pos - 1) this.pos += 1 } lunr.QueryLexer.prototype.next = function () { if (this.pos >= this.length) { return lunr.QueryLexer.EOS } var char = this.str.charAt(this.pos) this.pos += 1 return char } lunr.QueryLexer.prototype.width = function () { return this.pos - this.start } lunr.QueryLexer.prototype.ignore = function () { if (this.start == this.pos) { this.pos += 1 } this.start = this.pos } lunr.QueryLexer.prototype.backup = function () { this.pos -= 1 } lunr.QueryLexer.prototype.acceptDigitRun = function () { var char, charCode do { char = this.next() charCode = char.charCodeAt(0) } while (charCode > 47 && charCode < 58) if (char != lunr.QueryLexer.EOS) { this.backup() } } lunr.QueryLexer.prototype.more = function () { return this.pos < this.length } lunr.QueryLexer.EOS = 'EOS' lunr.QueryLexer.FIELD = 'FIELD' lunr.QueryLexer.TERM = 'TERM' lunr.QueryLexer.EDIT_DISTANCE = 'EDIT_DISTANCE' lunr.QueryLexer.BOOST = 'BOOST' lunr.QueryLexer.PRESENCE = 'PRESENCE' lunr.QueryLexer.lexField = function (lexer) { lexer.backup() lexer.emit(lunr.QueryLexer.FIELD) lexer.ignore() return lunr.QueryLexer.lexText } lunr.QueryLexer.lexTerm = function (lexer) { if (lexer.width() > 1) { lexer.backup() lexer.emit(lunr.QueryLexer.TERM) } lexer.ignore() if (lexer.more()) { return lunr.QueryLexer.lexText } } lunr.QueryLexer.lexEditDistance = function (lexer) { lexer.ignore() lexer.acceptDigitRun() lexer.emit(lunr.QueryLexer.EDIT_DISTANCE) return lunr.QueryLexer.lexText } lunr.QueryLexer.lexBoost = function (lexer) { lexer.ignore() lexer.acceptDigitRun() lexer.emit(lunr.QueryLexer.BOOST) return lunr.QueryLexer.lexText } lunr.QueryLexer.lexEOS = function (lexer) { if (lexer.width() > 0) { lexer.emit(lunr.QueryLexer.TERM) } } // This matches the separator used when tokenising fields // within a document. These should match otherwise it is // not possible to search for some tokens within a document. // // It is possible for the user to change the separator on the // tokenizer so it _might_ clash with any other of the special // characters already used within the search string, e.g. :. // // This means that it is possible to change the separator in // such a way that makes some words unsearchable using a search // string. lunr.QueryLexer.termSeparator = lunr.tokenizer.separator lunr.QueryLexer.lexText = function (lexer) { while (true) { var char = lexer.next() if (char == lunr.QueryLexer.EOS) { return lunr.QueryLexer.lexEOS } // Escape character is '\' if (char.charCodeAt(0) == 92) { lexer.escapeCharacter() continue } if (char == ":") { return lunr.QueryLexer.lexField } if (char == "~") { lexer.backup() if (lexer.width() > 0) { lexer.emit(lunr.QueryLexer.TERM) } return lunr.QueryLexer.lexEditDistance } if (char == "^") { lexer.backup() if (lexer.width() > 0) { lexer.emit(lunr.QueryLexer.TERM) } return lunr.QueryLexer.lexBoost } // "+" indicates term presence is required // checking for length to ensure that only // leading "+" are considered if (char == "+" && lexer.width() === 1) { lexer.emit(lunr.QueryLexer.PRESENCE) return lunr.QueryLexer.lexText } // "-" indicates term presence is prohibited // checking for length to ensure that only // leading "-" are considered if (char == "-" && lexer.width() === 1) { lexer.emit(lunr.QueryLexer.PRESENCE) return lunr.QueryLexer.lexText } if (char.match(lunr.QueryLexer.termSeparator)) { return lunr.QueryLexer.lexTerm } } } lunr.QueryParser = function (str, query) { this.lexer = new lunr.QueryLexer (str) this.query = query this.currentClause = {} this.lexemeIdx = 0 } lunr.QueryParser.prototype.parse = function () { this.lexer.run() this.lexemes = this.lexer.lexemes var state = lunr.QueryParser.parseClause while (state) { state = state(this) } return this.query } lunr.QueryParser.prototype.peekLexeme = function () { return this.lexemes[this.lexemeIdx] } lunr.QueryParser.prototype.consumeLexeme = function () { var lexeme = this.peekLexeme() this.lexemeIdx += 1 return lexeme } lunr.QueryParser.prototype.nextClause = function () { var completedClause = this.currentClause this.query.clause(completedClause) this.currentClause = {} } lunr.QueryParser.parseClause = function (parser) { var lexeme = parser.peekLexeme() if (lexeme == undefined) { return } switch (lexeme.type) { case lunr.QueryLexer.PRESENCE: return lunr.QueryParser.parsePresence case lunr.QueryLexer.FIELD: return lunr.QueryParser.parseField case lunr.QueryLexer.TERM: return lunr.QueryParser.parseTerm default: var errorMessage = "expected either a field or a term, found " + lexeme.type if (lexeme.str.length >= 1) { errorMessage += " with value '" + lexeme.str + "'" } throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) } } lunr.QueryParser.parsePresence = function (parser) { var lexeme = parser.consumeLexeme() if (lexeme == undefined) { return } switch (lexeme.str) { case "-": parser.currentClause.presence = lunr.Query.presence.PROHIBITED break case "+": parser.currentClause.presence = lunr.Query.presence.REQUIRED break default: var errorMessage = "unrecognised presence operator'" + lexeme.str + "'" throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) } var nextLexeme = parser.peekLexeme() if (nextLexeme == undefined) { var errorMessage = "expecting term or field, found nothing" throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) } switch (nextLexeme.type) { case lunr.QueryLexer.FIELD: return lunr.QueryParser.parseField case lunr.QueryLexer.TERM: return lunr.QueryParser.parseTerm default: var errorMessage = "expecting term or field, found '" + nextLexeme.type + "'" throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) } } lunr.QueryParser.parseField = function (parser) { var lexeme = parser.consumeLexeme() if (lexeme == undefined) { return } if (parser.query.allFields.indexOf(lexeme.str) == -1) { var possibleFields = parser.query.allFields.map(function (f) { return "'" + f + "'" }).join(', '), errorMessage = "unrecognised field '" + lexeme.str + "', possible fields: " + possibleFields throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) } parser.currentClause.fields = [lexeme.str] var nextLexeme = parser.peekLexeme() if (nextLexeme == undefined) { var errorMessage = "expecting term, found nothing" throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) } switch (nextLexeme.type) { case lunr.QueryLexer.TERM: return lunr.QueryParser.parseTerm default: var errorMessage = "expecting term, found '" + nextLexeme.type + "'" throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) } } lunr.QueryParser.parseTerm = function (parser) { var lexeme = parser.consumeLexeme() if (lexeme == undefined) { return } parser.currentClause.term = lexeme.str.toLowerCase() if (lexeme.str.indexOf("*") != -1) { parser.currentClause.usePipeline = false } var nextLexeme = parser.peekLexeme() if (nextLexeme == undefined) { parser.nextClause() return } switch (nextLexeme.type) { case lunr.QueryLexer.TERM: parser.nextClause() return lunr.QueryParser.parseTerm case lunr.QueryLexer.FIELD: parser.nextClause() return lunr.QueryParser.parseField case lunr.QueryLexer.EDIT_DISTANCE: return lunr.QueryParser.parseEditDistance case lunr.QueryLexer.BOOST: return lunr.QueryParser.parseBoost case lunr.QueryLexer.PRESENCE: parser.nextClause() return lunr.QueryParser.parsePresence default: var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) } } lunr.QueryParser.parseEditDistance = function (parser) { var lexeme = parser.consumeLexeme() if (lexeme == undefined) { return } var editDistance = parseInt(lexeme.str, 10) if (isNaN(editDistance)) { var errorMessage = "edit distance must be numeric" throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) } parser.currentClause.editDistance = editDistance var nextLexeme = parser.peekLexeme() if (nextLexeme == undefined) { parser.nextClause() return } switch (nextLexeme.type) { case lunr.QueryLexer.TERM: parser.nextClause() return lunr.QueryParser.parseTerm case lunr.QueryLexer.FIELD: parser.nextClause() return lunr.QueryParser.parseField case lunr.QueryLexer.EDIT_DISTANCE: return lunr.QueryParser.parseEditDistance case lunr.QueryLexer.BOOST: return lunr.QueryParser.parseBoost case lunr.QueryLexer.PRESENCE: parser.nextClause() return lunr.QueryParser.parsePresence default: var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) } } lunr.QueryParser.parseBoost = function (parser) { var lexeme = parser.consumeLexeme() if (lexeme == undefined) { return } var boost = parseInt(lexeme.str, 10) if (isNaN(boost)) { var errorMessage = "boost must be numeric" throw new lunr.QueryParseError (errorMessage, lexeme.start, lexeme.end) } parser.currentClause.boost = boost var nextLexeme = parser.peekLexeme() if (nextLexeme == undefined) { parser.nextClause() return } switch (nextLexeme.type) { case lunr.QueryLexer.TERM: parser.nextClause() return lunr.QueryParser.parseTerm case lunr.QueryLexer.FIELD: parser.nextClause() return lunr.QueryParser.parseField case lunr.QueryLexer.EDIT_DISTANCE: return lunr.QueryParser.parseEditDistance case lunr.QueryLexer.BOOST: return lunr.QueryParser.parseBoost case lunr.QueryLexer.PRESENCE: parser.nextClause() return lunr.QueryParser.parsePresence default: var errorMessage = "Unexpected lexeme type '" + nextLexeme.type + "'" throw new lunr.QueryParseError (errorMessage, nextLexeme.start, nextLexeme.end) } } /** * export the module via AMD, CommonJS or as a browser global * Export code from https://github.com/umdjs/umd/blob/master/returnExports.js */ ;(function (root, factory) { if (typeof define === 'function' && define.amd) { // AMD. Register as an anonymous module. define(factory) } else if (typeof exports === 'object') { /** * Node. Does not work with strict CommonJS, but * only CommonJS-like enviroments that support module.exports, * like Node. */ module.exports = factory() } else { // Browser globals (root is window) root.lunr = factory() } }(this, function () { /** * Just return a value to define the module export. * This example returns an object, but the module * can return a function as the exported value. */ return lunr })) })();
