def text_search(command):
envir.vm_env.attachCurrentThread()
command_dict = parseCommand(command, "contents")
querys = BooleanQuery()
for k, v in command_dict.iteritems():
query = QueryParser(Version.LUCENE_CURRENT, k,
envir.analyzer).parse(v)
querys.add(query, BooleanClause.Occur.MUST)
scoreDocs = envir.text_searcher.search(querys, 30).scoreDocs
res = []
query_highlight = QueryParser(Version.LUCENE_CURRENT, k,
envir.analyzer).parse(command_dict["contents"])
myhighlighter = Highlighter(
SimpleHTMLFormatter(), QueryScorer(query_highlight))
myhighlighter.setTextFragmenter(SimpleFragmenter(50))
for scoreDoc in scoreDocs:
# find texts which are around the keyword
doc = envir.text_searcher.doc(scoreDoc.doc)
text = doc.get("contents")
key_text = "".join((myhighlighter.getBestFragments(
envir.analyzer, "contents", text, 3)))
key_text = re.sub('\s', '', key_text)
temp = [doc.get("title"), doc.get('url'), key_text]
res.append(temp)
return res
def search_synonym(self, query):
self.hits_dict = {}
self.hits = []
similar_terms = self.w2v_model.most_similar(query)
parser = QueryParser('text', self.analyzer)
query = parser.parse(query)
for s_term in similar_terms[:20]:
s_term_query = parser.parse(s_term[0])
hits = self.searcher.search(s_term_query, 1000).scoreDocs
hit_count = 0
for hit in hits:
doc = self.searcher.doc(hit.doc)
text = doc.get('text')
terms = text.split()
sentence = ''
for term in terms:
sentence += term
simpleHTMLFormatter = SimpleHTMLFormatter(
prefixHTML, suffixHTML)
highlighter = Highlighter(simpleHTMLFormatter,
QueryScorer(query))
highLightText = highlighter.getBestFragment(
self.analyzer, 'text', sentence)
if highLightText is not None:
self.hits.append(highLightText)
hit_count += 1
if hit_count >= 3:
break
if len(self.hits) > 0:
self.hits_dict[s_term] = self.hits
self.hits = []
return self.hits_dict
def search(self, query_str, restriction=2):
self.attachCurrentThread()
# 对query进行解析
result_contexts = []
# 根据有没有‘/’判断有没有词性，
if '/' in query_str:
# 有词性就转到search_phrases
result_contexts = self.search_phrases(query_str)
else:
# 有词性就转到search_terms
result_contexts = self.search_terms(
QueryParser("context", self.analyzer).parse(query_str))
# 将搜索结果复原为文章返回
self.recover_to_article(query_str, result_contexts, restriction)
final_result = []
#进行搜索结果中跟query相关的文段高量处理
simpleHTMLFormatter = SimpleHTMLFormatter(u"<b><font color='red'>",
u"</font></b>")
for index, recovered_query in enumerate(self.recovered_queries):
# 不是直接拿用户输入的query来进行高亮处理，而是通过我们自己处理好的包含了位置约束的query进行高亮处理
recovered_query = recovered_query.replace("/", ",")
highlighter = Highlighter(
simpleHTMLFormatter,
QueryScorer(
QueryParser("context",
self.analyzer).parse(recovered_query)))
highLightText = highlighter.getBestFragment(
self.analyzer, 'context', self.recovered_contexts[index])
if highLightText is not None:
final_result.append(highLightText)
return final_result
def run(command):
vm_env = lucene.getVMEnv()
vm_env.attachCurrentThread()
STORE_DIR = "index1"
directory = SimpleFSDirectory(File(STORE_DIR))
searcher = IndexSearcher(DirectoryReader.open(directory))
analyzer = WhitespaceAnalyzer(Version.LUCENE_CURRENT)
query = QueryParser(Version.LUCENE_CURRENT, "contents",
analyzer).parse(analysis(command))
HighlightFormatter = SimpleHTMLFormatter()
highlighter = Highlighter(HighlightFormatter, QueryScorer(query))
scoreDocs = searcher.search(query, 500).scoreDocs
print "%s total matching documents." % len(scoreDocs)
result = []
for scoreDoc in scoreDocs:
doc = searcher.doc(scoreDoc.doc)
print 'path:', doc.get("path"), 'name:', doc.get(
"name"), 'url:', doc.get("url"), 'title:', doc.get("title")
text = doc.get('contents')
highLightText = highlighter.getBestFragment(analyzer, "contents", text)
if highLightText != None:
highLightText = ''.join(highLightText.split(' '))
data = {}
data['url'] = doc.get("url")
data['title'] = doc.get('title')
data['highlight'] = highLightText
result.append(data)
return result
def highlighting(analyzer,contents,query):
formatter=SimpleHTMLFormatter("<b><font color='black'>","</font></b>")
highlighter=Highlighter(formatter,QueryScorer(query))
highlighter.setTextFragmenter(SimpleFragmenter(30))
tokenStream=analyzer.tokenStream('contents',contents)
light_content=highlighter.getBestFragments(tokenStream,contents,3,'...')
return light_content
def search(self, q, page=1, duplicates=False):
query = self.parser.parse(q)
if not duplicates:
query = self.addDuplicatesQuery(query)
perPage = 10
start = (page - 1) * perPage
results = TopScoreDocCollector.create(1000, True)
self.searcher.search(query, results)
highlighter = Highlighter(QueryScorer(query))
highlighter.setTextFragmenter(SimpleFragmenter(40))
docs = []
for scoreDoc in results.topDocs(start, perPage).scoreDocs:
doc = self.searcher.doc(scoreDoc.doc)
tokenStream = self.analyzer.tokenStream(
"contents", StringReader(doc['contents']))
highlight = highlighter.getBestFragments(tokenStream,
doc['contents'], 3, "...")
docs.append({
'title': doc['title'],
'url': doc['url'],
'duplicate': doc['duplicate'],
'highlight': highlight
})
del self.searcher
totalPages = int(math.ceil(results.getTotalHits() / float(perPage)))
return totalPages, docs
def output(self, score_docs, command):
'''
Highlight and return the search results.
Input: `score_docs`: search results from the index
Output: list of documents info found in the index,
details includes `title`, `url` and `abstract`
'''
query = QueryParser('contents', self.analyzer).parse(command)
highlighter = Highlighter(self.formatter, QueryScorer(query))
highlighter.setTextFragmenter(
SimpleFragmenter(200)) # Limit the max number of characters
results = []
for score_doc in score_docs:
doc = self.searcher.doc(score_doc.doc)
contents = doc.get('contents')
stream = self.analyzer.tokenStream("contents", contents)
abstract = highlighter.getBestFragment(
stream, contents) # Get the abstract and highlight
result = {
'title': doc.get('title'),
'url': doc.get('url'),
'abstract': abstract.replace(' ', '')
}
results.append(result)
return results
def testSimpleHighlighter(self):
self.doSearching("Wicked")
highlighter = Highlighter(QueryScorer(self.query))
highlighter.setTextFragmenter(SimpleFragmenter(40))
maxNumFragmentsRequired = 2
for scoreDoc in self.scoreDocs:
text = self.searcher.doc(scoreDoc.doc).get(self.FIELD_NAME)
tokenStream = self.analyzer.tokenStream(self.FIELD_NAME,
StringReader(text))
result = highlighter.getBestFragments(tokenStream, text,
maxNumFragmentsRequired,
"...")
print "\t", result
def search_multi_terms(self, query):
print('Multiterms search')
hits = self.searcher.search(query, 100).scoreDocs
for hit in hits:
doc = self.searcher.doc(hit.doc)
text = doc.get("text")
terms = text.split()
sentence = ''
for term in terms:
sentence += term
simpleHTMLFormatter = SimpleHTMLFormatter(prefixHTML, suffixHTML)
highlighter = Highlighter(simpleHTMLFormatter, QueryScorer(query))
highLightText = highlighter.getBestFragment(
self.analyzer, 'text', sentence)
if highLightText is not None:
self.hits.append(highLightText)
def doStandardHighlights(self):
formatter = TestFormatter(self)
highlighter = Highlighter(formatter, QueryScorer(self.query))
highlighter.setTextFragmenter(SimpleFragmenter(20))
for scoreDoc in self.scoreDocs:
text = self.searcher.doc(scoreDoc.doc).get(self.FIELD_NAME)
maxNumFragmentsRequired = 2
fragmentSeparator = "..."
tokenStream = self.analyzer.tokenStream(self.FIELD_NAME,
StringReader(text))
result = highlighter.getBestFragments(tokenStream, text,
maxNumFragmentsRequired,
fragmentSeparator)
print "\t", result
def search_by(self, **kwargs):
command = kwargs.get('command', '')
if command == '':
return None
field = kwargs.get('field')
query_type = kwargs.get('query_type', 'chi')
if query_type == 'chi':
if field in ['token_taglist', 'token_content', 'token_title', 'token_author']:
command = ' '.join(jieba.cut_for_search(command))
hlt_analyzer = self.analyzer['ChineseAnalyzer']
else:
if field in ['token_content', 'token_title']:
command = ' '.join(map(stem, command.split()))
hlt_analyzer = self.analyzer['StandardAnalyzer']
analyzer = self.analyzer['SimpleAnalyzer']
num = kwargs.get('num', 50)
attrs = kwargs.get('attrs', ['url', 'title'])
print "[%s]\tSearching for '%s' in field '%s'" % (query_type, command, field)
query = QueryParser(Version.LUCENE_CURRENT, field, analyzer).parse(command)
if field in ['token_content', 'token_title']:
getAbs = True
query_for_highlight = QueryParser(Version.LUCENE_CURRENT, 'content', hlt_analyzer).parse(command)
scorer = QueryScorer(query_for_highlight)
formatter = SimpleHTMLFormatter("<strong>", "</strong>")
# formatter = SimpleHTMLFormatter("<span class=\"highlight\">", "</span>")
highlighter = Highlighter(formatter, scorer)
fragmenter = SimpleFragmenter(20)
highlighter.setTextFragmenter(fragmenter)
else:
getAbs = False
scoreDocs = self.searcher.search(query, num).scoreDocs
print "%s total matching documents." % len(scoreDocs)
articles = []
for scoreDoc in scoreDocs:
doc = self.searcher.doc(scoreDoc.doc)
article = {}
for attr in attrs:
article[attr] = doc.get(attr)
if getAbs is True:
content = doc.get('content')
tokenStream = hlt_analyzer.tokenStream("content", StringReader(content))
article['abstract'] = highlighter.getBestFragments(tokenStream, content, 3, "...")
articles.append(article)
return articles
def search_phrase(self, term, phrase):
print('Phrase search')
self.hits = []
index_list = []
parser = QueryParser('text', self.analyzer)
query = parser.parse(term)
hits = self.searcher.search(query, 1000).scoreDocs
if hits is None:
return
for hit in hits:
index = []
doc = self.searcher.doc(hit.doc)
text = doc.get("text")
phrases = doc.get("phrase")
# processing with saved text and phrase
terms = text.split()
phrases = phrases.split()
flag = 1 # this flag is judging for phrase in every target term in text
index = [] # index number for searched term, maybe many terms
for i in range(len(terms)):
if term == terms[i]:
index.append(i)
if not phrase == phrases[i]:
flag = 0
break
if flag == 1:
self.hits.append(text)
index_list.append(index)
self.recover_sentence(index_list)
hits_copy = self.hits
self.hits = []
# add font tags for terms
for hit in hits_copy:
simpleHTMLFormatter = SimpleHTMLFormatter(prefixHTML, suffixHTML)
highlighter = Highlighter(simpleHTMLFormatter, QueryScorer(query))
highLightText = highlighter.getBestFragment(
self.analyzer, 'text', hit)
if highLightText is not None:
self.hits.append(highLightText)
return self.hits[:40]
def search(self, terms, n_hits=5):
"""
Run search query.
"""
# TODO: support date range queries
# build query
parser = MultiFieldQueryParser(['fullpath', 'body'], self.analyzer)
#parser.setDefaultOperator(QueryParser.Operator.AND) # defaults to OR unless terms have modifier
query = MultiFieldQueryParser.parse(
parser, terms) # https://stackoverflow.com/a/26853987/130164
# create a highlighter
highlighter = Highlighter(SimpleHTMLFormatter('*', '*'),
QueryScorer(query))
# execute search for top N hits
return [
self._process_search_result(result, highlighter)
for result in self.searcher.search(query, n_hits).scoreDocs
]
def get_highlighted_hits(self):
extracted_fragments = []
scorer = QueryScorer(self.query)
fragmenter = SimpleSpanFragmenter(scorer, 10)
highlighter = Highlighter(self.formatter, scorer)
highlighter.setTextFragmenter(fragmenter)
for hit in self.hits.scoreDocs:
document = self.searcher.doc(hit.doc)
stream = TokenSources.getAnyTokenStream(self.index_reader, hit.doc,
'contents', self.analyzer)
best_fragments = highlighter.getBestFragments(
stream, document.get('contents'), 10)
for fragment in best_fragments:
print('fragment: ', fragment)
extracted_fragments.append((hit.doc, best_fragments))
return extracted_fragments
def search(self, term, window=2):
self.hits = []
index_list = []
sort_para = term
parser = QueryParser('text', self.analyzer)
query = parser.parse(term)
print(query)
# Jump to multi-terms search if there are several words
if self.multi_terms(query):
self.search_multi_terms(query)
return self.hits[:40]
hits = self.searcher.search(query, 1000).scoreDocs
for hit in hits:
index = []
doc = self.searcher.doc(hit.doc)
text = doc.get("text")
self.hits.append(text)
# save indexes of target term in each document
terms = text.split()
for i in range(len(terms)):
if term == terms[i]:
index.append(i)
index_list.append(index)
self.recover_sentence(index_list, window)
hits_copy = self.hits
self.hits = []
for hit in hits_copy:
simpleHTMLFormatter = SimpleHTMLFormatter(prefixHTML, suffixHTML)
highlighter = Highlighter(simpleHTMLFormatter, QueryScorer(query))
highLightText = highlighter.getBestFragment(
self.analyzer, 'text', hit)
if highLightText is not None:
self.hits.append(highLightText)
print('search over')
return self.hits[:40]
def run(searcher, analyzer, command):
command_dict = parseCommand(command)
seg_list = jieba.cut(command_dict['contents'])
command_dict['contents'] = (" ".join(seg_list))
querys = BooleanQuery()
for k, v in command_dict.iteritems():
query = QueryParser(Version.LUCENE_CURRENT, k, analyzer).parse(v)
querys.add(query, BooleanClause.Occur.MUST)
scoreDocs = searcher.search(querys, 50).scoreDocs
print "%s total matching documents." % len(scoreDocs)
scorer = QueryScorer(query)
fragmenter = SimpleSpanFragmenter(scorer, 250)
simpleHTMLFormatter = SimpleHTMLFormatter("<b>", "</b>")
highlighter = Highlighter(simpleHTMLFormatter, scorer)
highlighter.setTextFragmenter(fragmenter)
results = []
for i, scoreDoc in enumerate(scoreDocs):
doc = searcher.doc(scoreDoc.doc)
contents = doc.get("contents")
if contents:
tkStream = analyzer.tokenStream("contents", contents)
highlight = highlighter.getBestFragment(tkStream, contents)
highlightseg = highlight.split()
highlight = ''.join(highlightseg)
results.append(
(doc.get("title").strip(), doc.get("url"), highlight))
'''
print 'path:', doc.get("path"), \
'\nname:', doc.get("name"), \
'\ntitle:', doc.get("title"), \
"url:",doc.get("url"), \
"\nsite:",doc.get("site"),\
"\ncontent:",highlight,"\n"
'''
# print 'explain:', searcher.explain(query, scoreDoc.doc)
return results
def get_lm_doc_snippets(query,
searcher,
qparser,
analyzer,
preprocessor,
topk=10):
"""
Fetches the topk document snippets given query, searcher and qparser and
returns (did, text) pair list
:param query:
:param searcher:
:param qparser:
:param topk:
:return:
"""
dids_text = []
query = qparser.parse(query)
scoreDocs = searcher.search(query, topk).scoreDocs
highlighter = Highlighter(QueryScorer(query))
highlighter.setTextFragmenter(SimpleFragmenter(100))
for scoreDoc in scoreDocs:
doc = searcher.doc(scoreDoc.doc)
did = doc.get("id")
text = doc.get("raw")
token_stream = analyzer.tokenStream("raw", StringReader(text))
result = highlighter.getBestFragments(token_stream, text, 4, "... ")
text = get_parsed_text(result)
text = preprocess_text(preprocessor, [text])
text = " ".join(text)
dids_text.append((did, text))
return dids_text
def work(searcher, analyzer, command, low=None, high=None):
global prefixHTML
global suffixHTML
if command == '':
return 0, []
tmp = jieba.cut(command)
if command == '':
return 0, []
tmp = jieba.cut(command)
tmp = ''.join(command)
command = tmp
query = QueryParser(Version.LUCENE_CURRENT, "contents",
analyzer).parse(command)
scoreDocs = searcher.search(query, 50).scoreDocs
print "%s total matching documents." % len(scoreDocs)
simpleHTMLFormatter = SimpleHTMLFormatter(prefixHTML, suffixHTML)
highlighter = Highlighter(simpleHTMLFormatter, QueryScorer(query))
result = []
match_count = len(scoreDocs)
for scoreDoc in scoreDocs:
doc = searcher.doc(scoreDoc.doc)
text = doc.get("contents")
content = highlighter.getBestFragment(analyzer, "contents", text)
if (low == None) and (high == None):
result.append({
"url": doc.get('url'),
"Content": content,
"pic_url": doc.get('pic_url'),
"title": doc.get('title'),
"price": doc.get('price'),
"description": doc.get('description')
})
elif (low != None and high != None):
if doc.get('price') >= int(low) and doc.get('price') <= int(high):
result.append({
"url": doc.get('url'),
"Content": content,
"pic_url": doc.get('pic_url'),
"title": doc.get('title'),
"price": doc.get('price'),
"description": doc.get('description')
})
elif (low == None and high != None):
if doc.get('price') <= int(high):
result.append({
"url": doc.get('url'),
"Content": content,
"pic_url": doc.get('pic_url'),
"title": doc.get('title'),
"price": doc.get('price'),
"description": doc.get('description')
})
else:
if doc.get('price') >= int(low):
result.append({
"url": doc.get('url'),
"Content": content,
"pic_url": doc.get('pic_url'),
"title": doc.get('title'),
"price": doc.get('price'),
"description": doc.get('description')
})
result = sorted(result, key=lambda x: float(x["price"]), reverse=True)
return match_count, result
def run(searcher, analyzer, command, urlclick):
if command == '':
return []
res = firstsearch(searcher, analyzer, command)
command = ''.join(my_jieba.cut(command))
command = " ".join(jieba.cut(command, cut_all=True))
if len(res) > 0:
scoreDocs = res
else:
querys = BooleanQuery()
for k in tag:
query = QueryParser(Version.LUCENE_CURRENT, k,
analyzer).parse(command)
if k == 'taste' or k == 'tech':
query.setBoost(0.5)
querys.add(query, BooleanClause.Occur.SHOULD)
scoreDocs = searcher.search(querys, 10000).scoreDocs
swxc_res = findres(command, scoreDocs, searcher)
formatter = SimpleHTMLFormatter("<span style='color:red'>", "</span>")
formatter_name = SimpleHTMLFormatter("<span,style='color:red'>", "</span>")
scorer = QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'name', analyzer).parse(command))
highlighter1 = Highlighter(formatter_name, scorer)
highlighter2 = Highlighter(
formatter_name,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'content',
analyzer).parse(command)))
highlighter3 = Highlighter(
formatter,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'ingredient',
analyzer).parse(command)))
highlighter4 = Highlighter(
formatter,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'taste',
analyzer).parse(command)))
highlighter5 = Highlighter(
formatter,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'tech',
analyzer).parse(command)))
highlighter6 = Highlighter(
formatter,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'others',
analyzer).parse(command)))
fragmenter = SimpleFragmenter(1000)
highlighter1.setTextFragmenter(fragmenter)
highlighter2.setTextFragmenter(fragmenter)
highlighter3.setTextFragmenter(fragmenter)
highlighter4.setTextFragmenter(fragmenter)
highlighter5.setTextFragmenter(fragmenter)
highlighter6.setTextFragmenter(fragmenter)
results = []
for scoreDoc in scoreDocs:
if (len(scoreDocs) > 200 and
len(scoreDocs) * scoreDoc.score < 2) or scoreDoc.score < 0.002:
continue
doc = searcher.doc(scoreDoc.doc)
highlighterContent = highlighter1.getBestFragment(
analyzer, 'name', doc.get('name'))
highlighterContent2 = highlighter2.getBestFragment(
analyzer, 'content', doc.get('content'))
highlighterContent3 = highlighter3.getBestFragment(
analyzer, 'ingredient', doc.get('ingredient'))
highlighterContent4 = highlighter4.getBestFragment(
analyzer, 'taste', doc.get('taste'))
highlighterContent5 = highlighter5.getBestFragment(
analyzer, 'tech', doc.get('tech'))
highlighterContent6 = highlighter6.getBestFragment(
analyzer, 'others', doc.get('others'))
if highlighterContent:
highlighterContent = highlighterContent.replace(' ', '')
highlighterContent = highlighterContent.replace(',', ' ')
else:
highlighterContent = doc.get('name').replace(' ', '')
if highlighterContent2:
highlighterContent2 = highlighterContent2.replace(' ', '')
highlighterContent2 = highlighterContent2.replace(',', ' ')
else:
highlighterContent2 = doc.get('content').replace(' ', '')
if highlighterContent3:
highlighterContent3 = highlighterContent3.replace(',', '')
else:
highlighterContent3 = (doc.get('ingredient')).replace(',', '')
if highlighterContent4:
pass
else:
highlighterContent4 = doc.get('taste')
if highlighterContent5:
pass
else:
highlighterContent5 = doc.get('tech')
if highlighterContent6:
highlighterContent6 = highlighterContent6.replace(',', '')
else:
highlighterContent6 = (doc.get('others')).replace(',', '')
results.append(
(highlighterContent, doc.get('img'), highlighterContent2,
highlighterContent3, highlighterContent4, highlighterContent5,
highlighterContent6, doc.get('url'), scoreDoc.score))
for i in range(0, min(20, len(results)) - 1):
flag = True
for j in range(0, min(20, len(results)) - i - 1):
if abs(results[j][8] - results[j + 1][8]) < 0.1 and urlclick[
results[j][7]] < urlclick[results[j + 1][7]]:
flag = False
results[j], results[j + 1] = results[j + 1], results[j]
if flag:
break
return results, swxc_res
def build_highlighter(parsed_query):
scorer = QueryScorer(parsed_query, 'content')
highlighter = Highlighter(SimpleHTMLFormatter(), scorer)
fragmenter = SimpleSpanFragmenter(scorer, FRAGMENT_SIZE)
highlighter.setTextFragmenter(fragmenter)
return highlighter
def superSearch(command, command_dict, urlclick):
vm_env = lucene.getVMEnv()
vm_env.attachCurrentThread()
directory = SimpleFSDirectory(File('index2.3'))
print "run super search..."
searcher = IndexSearcher(DirectoryReader.open(directory))
analyzer = SimpleAnalyzer(Version.LUCENE_CURRENT)
command = ' '.join(jieba.cut_for_search(command))
querys = BooleanQuery()
if command:
query = QueryParser(Version.LUCENE_CURRENT, 'nameforsearch',
analyzer).parse(command)
querys.add(query, BooleanClause.Occur.SHOULD)
for k, v in (command_dict[0]).items():
query = QueryParser(Version.LUCENE_CURRENT, k, analyzer).parse(v)
query.setBoost(0.1)
querys.add(query, BooleanClause.Occur.MUST)
for k, v in (command_dict[1]).items():
query = QueryParser(Version.LUCENE_CURRENT, k, analyzer).parse(v)
querys.add(query, BooleanClause.Occur.MUST_NOT)
scoreDocs = searcher.search(querys, 10000).scoreDocs
swxc_res = findres(command + ' ' + command_dict[0].get("ingredient", ''),
scoreDocs, searcher)
formatter = SimpleHTMLFormatter("<span style='color:red'>", "</span>")
formatter_name = SimpleHTMLFormatter("<span,style='color:red'>", "</span>")
if command:
scorer = QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'name',
analyzer).parse(command))
highlighters = [Highlighter(formatter_name, scorer)]
else:
highlighters = ['']
if command_dict[0].get('ingredient'):
highlighters.append(
Highlighter(
formatter,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'ingredient',
analyzer).parse(
command_dict[0]['ingredient']))))
else:
highlighters.append('')
if command_dict[0].get('taste'):
highlighters.append(
Highlighter(
formatter,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'taste',
analyzer).parse(command_dict[0]['taste']))))
else:
highlighters.append('')
if command_dict[0].get('tech'):
highlighters.append(
Highlighter(
formatter,
QueryScorer(
QueryParser(Version.LUCENE_CURRENT, 'tech',
analyzer).parse(command_dict[0]['tech']))))
else:
highlighters.append('')
fragmenter = SimpleFragmenter(1000)
for h in highlighters:
if h:
h.setTextFragmenter(fragmenter)
results = []
for scoreDoc in scoreDocs:
if (scoreDoc.score * len(scoreDocs) < 200
and len(scoreDocs) > 200) or scoreDoc.score < 0.1:
continue
doc = searcher.doc(scoreDoc.doc)
if command:
highlighterContent = highlighters[0].getBestFragment(
analyzer, 'name', doc.get('name'))
else:
highlighterContent = ''
if highlighters[1]:
highlighterContent2 = highlighters[1].getBestFragment(
analyzer, 'ingredient', doc.get('ingredient'))
else:
highlighterContent2 = ''
if highlighters[2]:
highlighterContent3 = highlighters[2].getBestFragment(
analyzer, 'taste', doc.get('taste'))
else:
highlighterContent3 = ''
if highlighters[3]:
highlighterContent4 = highlighters[3].getBestFragment(
analyzer, 'tech', doc.get('tech'))
else:
highlighterContent4 = ''
if highlighterContent:
highlighterContent = highlighterContent.replace(' ', '')
highlighterContent = highlighterContent.replace(',', ' ')
else:
highlighterContent = doc.get('name').replace(' ', '')
if highlighterContent2:
highlighterContent2 = highlighterContent2.replace(',', '')
else:
highlighterContent2 = (doc.get('ingredient')).replace(',', '')
if highlighterContent3:
pass
else:
highlighterContent3 = doc.get('taste')
if highlighterContent4:
pass
else:
highlighterContent4 = doc.get('tech')
results.append(
(highlighterContent, doc.get('img'),
doc.get('content').replace(' ', ''),
highlighterContent2, highlighterContent3, highlighterContent4,
doc.get('others').replace(',',
''), doc.get('url'), scoreDoc.score))
for i in range(0, min(20, len(results)) - 1):
flag = True
for j in range(0, min(20, len(results)) - i - 1):
if abs(results[j][8] - results[j + 1][8]) < 0.1 and urlclick[
results[j][7]] < urlclick[results[j + 1][7]]:
flag = False
results[j], results[j + 1] = results[j + 1], results[j]
if flag:
break
return results, swxc_res
def run(self, writer=None, analyzer=None):
if writer is None:
writer = self.writer
if analyzer is None:
analyzer = self.analyzer
searcher = IndexSearcher(DirectoryReader.open(\
SimpleFSDirectory.open(File(self.store_dir))))
while True:
print()
print("Hit enter with no input to quit.")
command = input("Query:")
if command == '':
return
print("Searching for:", command)
query = QueryParser(Version.LUCENE_43, "contents",
analyzer).parse(command)
# We'll just show the top 10 matching documents for now
scoreDocs = searcher.search(query, 10).scoreDocs
print("%s total matching documents." % len(scoreDocs))
# Highlight the matching text in red
highlighter = Highlighter(
SimpleHTMLFormatter('<b><font color\
="red">', '</font></b>'), QueryScorer(query))
# Using NullFragmenter since we still want to see
# the whole document
highlighter.setTextFragmenter(NullFragmenter())
for scoreDoc in scoreDocs:
doc = searcher.doc(scoreDoc.doc)
tokenStream = analyzer.tokenStream(
"contents", StringReader(doc.get("contents")))
# arg 3: the maximum number of fragments
# arg 4: the separator used to intersperse the
# document fragments (typically "...")
# arg 3 and 4 don't really matter with NullFragmenter
result = highlighter.getBestFragments(tokenStream,
doc.get("contents"), 2,
"...")
if len(result) > 10:
file_handler = open(self.hits_dir + '/' + doc.get("name"),
'w+')
file_handler.write(result)
# create hit fragments, if we want to show them
# arg 1: fragment size
highlighter.setTextFragmenter(SimpleFragmenter(200))
for scoreDoc in scoreDocs:
doc = searcher.doc(scoreDoc.doc)
tokenStream = analyzer.tokenStream(
"contents", StringReader(doc.get("contents")))
result = highlighter.getBestFragments(tokenStream,
doc.get("contents"), 2,
"...")
if len(result) > 10:
file_handler = open(self.frags_dir + '/' + doc.get("name"),
'w+')
file_handler.write(result)