Python lucene.QueryParser类代码示例

    def searchXYPair(self,x,y):
        """
        Returns all sentences, which are tagged with the given two entities (x,y)
        """
        tmp_hm = {}
        if x == "" or y == "":
            return []
        try:
            array = re.findall(r'[\w\s]+',x)
            x = ""
            for item in array:
                x+=item
            qp = QueryParser(Version.LUCENE_35, "X", analyzer)
            qp.setDefaultOperator(qp.Operator.AND)
            query = qp.parse(x)
            MAX = 100000
            result_list = []
            hits = searcher.search(query, MAX)
            for hit in hits.scoreDocs:
                doc = searcher.doc(hit.doc)
                y_entry = doc["Y"]
                if y_entry == y:
                    tmp_hm[doc["Sentence"]]=""
                    
            for key in tmp_hm:
                result_list.append(IndexUtils.sentence_wrapper(key))
            tmp_hm = {}
            return result_list
        except:
            print("Fail (search XYPair) in x:"+x+" y:"+y)
            print "Unexpected error:", sys.exc_info()[0]
            print

            
        return []

    def main(cls, argv):

        allBooks = MatchAllDocsQuery()
        parser = QueryParser(Version.LUCENE_CURRENT, "contents",
                             StandardAnalyzer(Version.LUCENE_CURRENT))
        query = BooleanQuery()
        query.add(allBooks, BooleanClause.Occur.SHOULD)
        query.add(parser.parse("java OR action"), BooleanClause.Occur.SHOULD)

        indexDir = System.getProperty("index.dir")
        directory = SimpleFSDirectory(File(indexDir))

        example = SortingExample(directory)

        example.displayResults(query, Sort.RELEVANCE)
        example.displayResults(query, Sort.INDEXORDER)
        example.displayResults(query,
                               Sort(SortField("category", SortField.STRING)))
        example.displayResults(query,
                               Sort(SortField("pubmonth", SortField.INT, True)))

        example.displayResults(query,
                               Sort([SortField("category", SortField.STRING),
                                     SortField.FIELD_SCORE,
                                     SortField("pubmonth", SortField.INT, True)]))

        example.displayResults(query,
                               Sort([SortField.FIELD_SCORE,
                                     SortField("category", SortField.STRING)]))
        directory.close()

def search(r, keyword=""):
    import logging

    logger = logging.getLogger("search")
    bench = Benchmark(logger)
    from lucene import IndexSearcher, StandardAnalyzer, FSDirectory, QueryParser, File, Hit
    import lucene, os

    os.environ["JAVA_HOME"] = "/usr/local/jdk1.6.0_17"
    lucene.initVM(lucene.CLASSPATH)

    directory = FSDirectory.open(File(CONFIG.INDEX_PATH))
    ROBOT_INDEX = IndexSearcher(directory, True)
    ROBOT_ANALYZER = StandardAnalyzer()

    keyword = keyword or r.GET["keyword"]
    query = QueryParser("context", ROBOT_ANALYZER)
    query = query.parse('"%s"' % keyword)

    bench.start_mark("search")
    hits = ROBOT_INDEX.search(query)
    count = len(hits)
    result = []
    i = 0
    for hit in hits:
        i += 1
        if i > 100:
            break
        doc = Hit.cast_(hit).getDocument()
        result.append(SearchResult(doc, i, keyword))
    ROBOT_INDEX.close()

    et = bench.stop_mark()

    return render_to_response("robot_search_result.html", {"result": result, "count": count, "elaspe": et})

    def searchForDbpediaURI(self, uri):
        """
        Returns all anchor texts, which are related to the given DBpedia URI.
        Also returns for each anchor text the corresponding URI and the number of how often the anchor appears on the english Wikipedia
        """
        uri_old = uri
        uri = uri.replace("http://dbpedia.org/resource/","")

        array = re.findall(r'[\w\s]+',uri)
        uri = ""
        for item in array:
            uri+=item
        
        try:
            qp = QueryParser(Version.LUCENE_35, "dbpedia_uri", analyzer)
            qp.setDefaultOperator(qp.Operator.AND)
            query = qp.parse(uri)
            MAX = 10000
            result = []
            hits = searcher.search(query, MAX)
            for hit in hits.scoreDocs:
                doc = searcher.doc(hit.doc)
                dbpedia_uri = doc["dbpedia_uri"].encode("utf-8")
                if dbpedia_uri == uri_old:
                    result.append([doc["anchor"].encode("utf-8"), doc["anchor_uri"].encode("utf-8"), dbpedia_uri, doc["number"].encode("utf-8")])
            return result
        except:
            print("searchForDbpediaURI - Fail in uri: "+uri)
            return []

    def searchKey(self, key , rank = None):
        query = ""
        try:
            MAX = 100000
            qp = QueryParser(Version.LUCENE_35, "key", analyzer)
            qp.setDefaultOperator(qp.Operator.AND)
            query = qp.parse(key)
#             print ("query",query)
                        
            hits = searcher.search(query, MAX)

            sentence_list = []
            for hit in hits.scoreDocs:
                doc = searcher.doc(hit.doc)
                try:
                    sentence_list.append(eval(doc.get("sentence").encode("utf-8")))
                except:
                    print doc.get("sentence")
            return sentence_list
        except:
            print("Fail in receiving sentence with term "+key)
            print ("query",query)
            print "Unexpected error:", sys.exc_info()[0]
#            raw_input("wait")
            print
            return []

    def query(indexName, queryString):

        indSearcher = IndexSearcher(SimpleFSDirectory(File(indexName)))
        qp = QueryParser(Version.LUCENE_CURRENT, "content", StandardAnalyzer(Version.LUCENE_CURRENT))
        qp.setDefaultOperator(qp.Operator.AND)
         
        query = qp.parse(queryString.replace("-","_"))
                
        aux = indSearcher.search(query, 100)
        results = aux.scoreDocs
        hits = aux.totalHits
        
        ir = indSearcher.getIndexReader()

        #results = collector.topDocs()
        i = 0

        res = []
    
        for r in results:        
            doc = ir.document(i)
            res.insert(i, doc.get('id'))
            i+=1
            
        return res

    def testPrefixQuery(self):

        parser = QueryParser(Version.LUCENE_CURRENT, "category",
                             StandardAnalyzer(Version.LUCENE_CURRENT))
        parser.setLowercaseExpandedTerms(False)

        print parser.parse("/Computers/technology*").toString("category")

    def search(self, string ,special = None):
        query = ""
        try:
            MAX = 100000
            #for dates such as 1931.08.06
            string = string.replace("."," ")
            
            array = re.findall(r'[\w\s]+',string)
            string = ""
            for item in array:
                string+=item
            qp = QueryParser(Version.LUCENE_35, "title", analyzer)
            qp.setDefaultOperator(qp.Operator.AND)
            query = qp.parse(string)
#            print ("query",query)
                        
            hits = searcher.search(query, MAX)
            
            sentence_list = []
            for hit in hits.scoreDocs:
                doc = searcher.doc(hit.doc)
                sentence_list.append(doc.get("title").encode("utf-8"))
            return sentence_list
        except:
            print("Fail in receiving sentence with term "+string)
            print ("query",query)
            print "Unexpected error:", sys.exc_info()[0]
#            raw_input("wait")
            print
            return []

    def searchForDbpediaURI(self, uri):
        """
        Returns all sentences, which are tagged with the given DBpedia URI
        """
        print "in searchForDbpediaURI" 
        uri_old = uri
        uri = uri.replace("http://dbpedia.org/ontology/","")
        uri = uri.replace("http://dbpedia.org/property/","")
        uri = uri.replace("http://dbpedia.org/resource/","")

        array = re.findall(r'[\w\s]+',uri)
        uri = ""
        for item in array:
            uri+=item
        
        try:
            qp = QueryParser(Version.LUCENE_35, "URI", analyzer)
            qp.setDefaultOperator(qp.Operator.AND)
            query = qp.parse(uri)
            print "query: "+str(query)
            MAX = 500000
            result = []
            hits = searcher.search(query, MAX)
            for hit in hits.scoreDocs:
                doc = searcher.doc(hit.doc)
                dbpedia_uri = doc["URI"]
                if dbpedia_uri == uri_old:
                    result.append([IndexUtils.sentence_wrapper(doc["Sentence"]), doc["X"], doc["Y"],dbpedia_uri])
            return result
        except:
            print("Fail in uri: "+uri)
            print "Unexpected error:", sys.exc_info()[0]
            return result

    def searchString(self, string):
        'searches for a string and returns an array of POS-tagged sentences'
        query = ""
        #print("Input String: ",string)
        try:
            MAX = 100000
            #for dates such as 1931.08.06
            string = string.replace("."," ")
            
            array = re.findall(r'[\w\s]+',string)
            string = ""
            for item in array:
                string+=item
            #print("Input String2: ",string)
            qp = QueryParser(Version.LUCENE_35, "sentence", analyzer)
            qp.setDefaultOperator(qp.Operator.AND)
            query = qp.parse(string)
            #print ("query",query)
                        
            hits = searcher.search(query, MAX)
            #print len(hits)
            sentence_list = []
            for hit in hits.scoreDocs:
                doc = searcher.doc(hit.doc)
                #print doc.get("sentence")
                sentence_list.append(eval(doc.get("sentence").encode("utf-8")))
            return sentence_list
        except:
            print("Fail in receiving sentence with term "+string+" in search term")
            print ("query",query)
            print "Unexpected error:", sys.exc_info()[0]
#            raw_input("wait")
            print
            return []

 def does_line_existNew(self,line,x,y):
     """
     Checks, if parsed sentence already exists in index
     """
     query = ""
     try:
         array = re.findall(r'[\w]+',line)
         string = ""
         for item in array:
             string+=item+" "
         qp = QueryParser(Version.LUCENE_35, "Sentence", analyzer)
         qp.setDefaultOperator(qp.Operator.AND)
         query = qp.parse(string)
         
         MAX = 10
         hits = searcher.search(query, MAX)
         if len(hits.scoreDocs)>0:
             return True
         else:
             return False
     except Exception:
         s_tmp =  str(sys.exc_info())
         if "too many boolean clauses" in s_tmp:
             print "too many boolean clauses"
             """
             Returns true, so that the sentence is not added each time, to avoid further error messages.
             Only occours with very large sentences.
             """
             return True
         else:
             print "Unexpected error:", sys.exc_info()[0]
             print "in does line exist"
             print s_tmp
     return False

    def testPhraseQuery(self):

        analyzer = StandardAnalyzer(Version.LUCENE_24)
        q = QueryParser(Version.LUCENE_24, "field", analyzer).parse('"This is Some Phrase*"')
        self.assertEqual('"some phrase"', q.toString("field"), "analyzed")

        q = QueryParser(Version.LUCENE_CURRENT, "field", self.analyzer).parse('"term"')
        self.assert_(TermQuery.instance_(q), "reduced to TermQuery")

    def main(cls):

        query = QueryParser(Version.LUCENE_CURRENT, "content",
                            cls.synonymAnalyzer).parse('"fox jumps"')
        print "\"fox jumps\" parses to ", query.toString("content")

        print "From AnalyzerUtils.tokensFromAnalysis: "
        AnalyzerUtils.displayTokens(cls.synonymAnalyzer, "\"fox jumps\"")
        print ''

    def __init__(self, emoticon, searcher, analyzer, english_only=False):
        super(PMICalculator, self).__init__()

        self.field = "emoticons"
        self.emoticon = emoticon
        self.searcher = searcher
        self.analyzer = analyzer
        self.escaped_emoticon = QueryParser.escape(self.emoticon)
        self.query = QueryParser("emoticons", self.analyzer).parse(self.escaped_emoticon)
        self.raw_stats_dir = "/Volumes/TerraFirma/SharedData/vdb5/emoticons_raw_files/"
        if english_only:
            country = "United States"
            country_prefix = "US"
        else:
            country = None
            country_prefix = ""
        self.pmi_file_name = (
            self.raw_stats_dir
            + normalizeEmoticonName(self.emoticon).rstrip("_")
            + ("_%s" % (country_prefix)) * english_only
            + ".pmidata"
        )
        self.sample_tweets_name = (
            self.raw_stats_dir
            + normalizeEmoticonName(self.emoticon).rstrip("_")
            + ("_%s" % (country_prefix)) * english_only
            + ".samptweets"
        )
        self.sample_tweets_file = codecs.open(self.sample_tweets_name, encoding="utf-8", mode="w")
        self.term_count_collector = TermCountCollector(searcher, emoticon, country)
        print "starting query at: ", time.time()
        hits = self.searcher.search(self.query, self.term_count_collector)
        # print "terms: ", self.terms
        if emoticon == ":P":
            ee_two = QueryParser.escape(":p")
        elif emoticon == "T_T":
            ee_two = QueryParser.escape("TT")
        elif emoticon == "^_^":
            ee_two = QueryParser.escape("^^")
        if emoticon in [":P", "T_T", "^_^"]:
            q_two = QueryParser("emoticons", self.analyzer).parse(ee_two)
            hits_two = self.searcher.search(q_two, self.term_count_collector)
        self.terms = self.term_count_collector.getTerms()
        self.query_result_count = self.term_count_collector.getDocCount()
        for p_term, p_term_tweets in self.term_count_collector.popular_terms_hash.items():
            for p_term_tweet in p_term_tweets:
                self.sample_tweets_file.write("term: " + p_term + " tweet: " + p_term_tweet + "\n")
        self.sample_tweets_file.close()
        self.base_stats_file = open(
            "/Volumes/TerraFirma/SharedData/vdb5/emoticons_raw_files/emoticon_pmi_stats.txt", "r"
        )
        self.n = int(self.base_stats_file.read().strip().split(":")[1])

        print "computing PMI for query: ", self.emoticon, " at: ", time.time()

        self.p_query_result = self.query_result_count * 1.0 / self.n

def extractFeatureQueryWords(query):
    import string
    from lucene import Document, TermQuery, Term
    
    # create analyzer
    aux_analyzer = StandardAnalyzer(Version.LUCENE_CURRENT)
    
    try:
        file = open('../features.txt', 'r')
        
        featurelist = []
        for line in file.readlines():
            words_in_line = line.split()
            featurelist += words_in_line
             
        querywordlist = query.split()
        
        featureQueryList = []
        productQueryList = []
        
        for word in querywordlist:
            if word in featurelist:
                featureQueryList.append(word)
            else:
                # create parser for word
                aux_parser = QueryParser(Version.LUCENE_CURRENT, "title", aux_analyzer)
                aux_query = aux_parser.parse(word)
                scoreDocs = searcher.search(aux_query, 50).scoreDocs
                if scoreDocs:
                    productQueryList.append(word)

        
        featureQuery = ""
        if featureQueryList:
            featureQuery = "("
            for i in range(len(featureQueryList)):
                if i == len(featureQueryList) - 1:
                    featureQuery += featureQueryList[i] + ")"
                else:
                    featureQuery += featureQueryList[i] + " AND "
                
            print featureQuery
        
        productQuery = ""
        if productQueryList:
            productQuery = "("
            for i in range(len(productQueryList)):
                if i == len(productQueryList) - 1:
                    productQuery += productQueryList[i] + ")"
                else:
                    productQuery += productQueryList[i] + " AND "
            
        return (featureQuery, productQuery, featureQueryList, productQueryList)
    except Exception, ex:
        print "Could not separate feature query words. Reason: ", ex
        return ("", "(" + query + ")", [], querywordlist)