+# -*- coding: utf-8 -*-
from django.conf import settings
-from lucene import SimpleFSDirectory, IndexWriter
+from lucene import SimpleFSDirectory, IndexWriter, File, Field, \
+ NumericField, Version, Document, JavaError, IndexSearcher, \
+ QueryParser, PerFieldAnalyzerWrapper, \
+ SimpleAnalyzer, PolishAnalyzer, ArrayList, \
+ KeywordAnalyzer, NumericRangeQuery, BooleanQuery, \
+ BlockJoinQuery, BlockJoinCollector, TermsFilter, \
+ HashSet, BooleanClause, Term, CharTermAttribute, \
+ PhraseQuery, MultiPhraseQuery, StringReader, TermQuery, BlockJoinQuery, \
+ FuzzyQuery, FuzzyTermEnum, Sort, Integer, \
+ SimpleHTMLFormatter, Highlighter, QueryScorer, TokenSources, TextFragment, \
+ initVM, CLASSPATH, JArray
+ # KeywordAnalyzer
+JVM = initVM(CLASSPATH)
+import sys
import os
+import errno
+from librarian import dcparser
+from librarian.parser import WLDocument
+import catalogue.models
+from multiprocessing.pool import ThreadPool
+from threading import current_thread
+import atexit
+import traceback
-class BookSearch(object):
+class WLAnalyzer(PerFieldAnalyzerWrapper):
def __init__(self):
- if not os.exists(settings.SEARCH_INDEX):
- os.mkdir(settings.SEARCH_INDEX)
- self.store = IndexWriter(store, )
-
+ polish = PolishAnalyzer(Version.LUCENE_34)
+ simple = SimpleAnalyzer(Version.LUCENE_34)
+ keyword = KeywordAnalyzer(Version.LUCENE_34)
+ # not sure if needed: there's NOT_ANALYZED meaning basically the same
+
+ PerFieldAnalyzerWrapper.__init__(self, polish)
+
+ self.addAnalyzer("tags", simple)
+ self.addAnalyzer("technical_editors", simple)
+ self.addAnalyzer("editors", simple)
+ self.addAnalyzer("url", keyword)
+ self.addAnalyzer("source_url", keyword)
+ self.addAnalyzer("source_name", simple)
+ self.addAnalyzer("publisher", simple)
+ self.addAnalyzer("author", simple)
+ self.addAnalyzer("is_book", keyword)
+
+ self.addAnalyzer("KEYWORD", keyword)
+ self.addAnalyzer("SIMPLE", simple)
+ self.addAnalyzer("NATURAL", polish)
+
+
+class IndexStore(object):
+ def __init__(self):
+ self.make_index_dir()
+ self.store = SimpleFSDirectory(File(settings.SEARCH_INDEX))
+
+ def make_index_dir(self):
+ try:
+ os.makedirs(settings.SEARCH_INDEX)
+ except OSError as exc:
+ if exc.errno == errno.EEXIST:
+ pass
+ else: raise
+
+
+class Index(IndexStore):
+ def __init__(self, analyzer=None):
+ IndexStore.__init__(self)
+ self.index = None
+ if not analyzer:
+ analyzer = WLAnalyzer()
+ self.analyzer = analyzer
+
+ def open(self, analyzer=None):
+ if self.index:
+ raise Exception("Index is already opened")
+ self.index = IndexWriter(self.store, self.analyzer,\
+ IndexWriter.MaxFieldLength.LIMITED)
+ return self.index
+
+ def close(self):
+ self.index.optimize()
+ self.index.close()
+ self.index = None
+
+ def remove_book(self, book):
+ q = NumericRangeQuery.newIntRange("book_id", book.id, book.id, True, True)
+ self.index.deleteDocuments(q)
+
+ def index_book(self, book, overwrite=True):
+ if overwrite:
+ self.remove_book(book)
+
+ doc = self.extract_metadata(book)
+ parts = self.extract_content(book)
+ block = ArrayList().of_(Document)
+
+ for p in parts:
+ block.add(p)
+ block.add(doc)
+ self.index.addDocuments(block)
+
+ master_tags = [
+ 'opowiadanie',
+ 'powiesc',
+ 'dramat_wierszowany_l',
+ 'dramat_wierszowany_lp',
+ 'dramat_wspolczesny', 'liryka_l', 'liryka_lp',
+ 'wywiad'
+ ]
+
+ skip_header_tags = ['autor_utworu', 'nazwa_utworu', 'dzielo_nadrzedne']
+
+ def create_book_doc(self, book):
+ """
+ Create a lucene document connected to the book
+ """
+ doc = Document()
+ doc.add(NumericField("book_id", Field.Store.YES, True).setIntValue(book.id))
+ if book.parent is not None:
+ doc.add(NumericField("parent_id", Field.Store.YES, True).setIntValue(book.parent.id))
+ return doc
+
+ def extract_metadata(self, book):
+ book_info = dcparser.parse(book.xml_file)
+
+ print("extract metadata for book %s id=%d, thread%d" % (book.slug, book.id, current_thread().ident))
+
+ doc = self.create_book_doc(book)
+ doc.add(Field("slug", book.slug, Field.Store.NO, Field.Index.ANALYZED_NO_NORMS))
+ doc.add(Field("tags", ','.join([t.name for t in book.tags]), Field.Store.NO, Field.Index.ANALYZED))
+ doc.add(Field("is_book", 'true', Field.Store.NO, Field.Index.NOT_ANALYZED))
+
+ # validator, name
+ for field in dcparser.BookInfo.FIELDS:
+ if hasattr(book_info, field.name):
+ if not getattr(book_info, field.name):
+ continue
+ # since no type information is available, we use validator
+ type_indicator = field.validator
+ if type_indicator == dcparser.as_unicode:
+ s = getattr(book_info, field.name)
+ if field.multiple:
+ s = ', '.join(s)
+ try:
+ doc.add(Field(field.name, s, Field.Store.NO, Field.Index.ANALYZED))
+ except JavaError as je:
+ raise Exception("failed to add field: %s = '%s', %s(%s)" % (field.name, s, je.message, je.args))
+ elif type_indicator == dcparser.as_person:
+ p = getattr(book_info, field.name)
+ if isinstance(p, dcparser.Person):
+ persons = unicode(p)
+ else:
+ persons = ', '.join(map(unicode, p))
+ doc.add(Field(field.name, persons, Field.Store.NO, Field.Index.ANALYZED))
+ elif type_indicator == dcparser.as_date:
+ dt = getattr(book_info, field.name)
+ doc.add(Field(field.name, "%04d%02d%02d" % (dt.year, dt.month, dt.day), Field.Store.NO, Field.Index.NOT_ANALYZED))
+ return doc
+
+ def get_master(self, root):
+ for master in root.iter():
+ if master.tag in self.master_tags:
+ return master
+
+ def extract_content(self, book):
+ wld = WLDocument.from_file(book.xml_file.path)
+ root = wld.edoc.getroot()
+
+ # first we build a sequence of top-level items.
+ # book_id
+ # header_index - the 0-indexed position of header element.
+ # content
+ master = self.get_master(root)
+ if master is None:
+ return []
+
+ header_docs = []
+ for header, position in zip(list(master), range(len(master))):
+ if header.tag in self.skip_header_tags:
+ continue
+ doc = self.create_book_doc(book)
+ doc.add(NumericField("header_index", Field.Store.YES, True).setIntValue(position))
+ doc.add(Field("header_type", header.tag, Field.Store.YES, Field.Index.NOT_ANALYZED))
+ content = u' '.join([t for t in header.itertext()])
+ doc.add(Field("content", content, Field.Store.YES, Field.Index.ANALYZED))
+ header_docs.append(doc)
+
+ def walker(node):
+ yield node, None
+ for child in list(node):
+ for b, e in walker(child):
+ yield b, e
+ yield None, node
+ return
+
+ # Then we create a document for each fragments
+ # fragment_anchor - the anchor
+ # themes - list of themes [not indexed]
+ fragment_docs = []
+ # will contain (framgent id -> { content: [], themes: [] }
+ fragments = {}
+ for start, end in walker(master):
+ if start is not None and start.tag == 'begin':
+ fid = start.attrib['id'][1:]
+ fragments[fid] = {'content': [], 'themes': []}
+ fragments[fid]['content'].append(start.tail)
+ elif start is not None and start.tag == 'motyw':
+ fid = start.attrib['id'][1:]
+ fragments[fid]['themes'].append(start.text)
+ fragments[fid]['content'].append(start.tail)
+ elif start is not None and start.tag == 'end':
+ fid = start.attrib['id'][1:]
+ if fid not in fragments:
+ continue # a broken <end> node, skip it
+ frag = fragments[fid]
+ del fragments[fid]
+
+ def jstr(l):
+ return u' '.join(map(
+ lambda x: x == None and u'(none)' or unicode(x),
+ l))
+
+ doc = self.create_book_doc(book)
+ doc.add(Field("fragment_anchor", fid,
+ Field.Store.YES, Field.Index.NOT_ANALYZED))
+ doc.add(Field("content",
+ u' '.join(filter(lambda s: s is not None, frag['content'])),
+ Field.Store.YES, Field.Index.ANALYZED, Field.TermVector.WITH_POSITIONS_OFFSETS))
+ doc.add(Field("themes",
+ u' '.join(filter(lambda s: s is not None, frag['themes'])),
+ Field.Store.NO, Field.Index.ANALYZED))
+
+ fragment_docs.append(doc)
+ elif start is not None:
+ for frag in fragments.values():
+ frag['content'].append(start.text)
+ elif end is not None:
+ for frag in fragments.values():
+ frag['content'].append(end.tail)
+
+ return header_docs + fragment_docs
+
+ def __enter__(self):
+ self.open()
+ return self
+
+ def __exit__(self, type, value, tb):
+ self.close()
+
+
+def log_exception_wrapper(f):
+ def _wrap(*a):
+ try:
+ f(*a)
+ except Exception, e:
+ print("Error in indexing thread: %s" % e)
+ traceback.print_exc()
+ raise e
+ return _wrap
+
+
+class ReusableIndex(Index):
+ """
+ Works like index, but does not close/optimize Lucene index
+ until program exit (uses atexit hook).
+ This is usefull for importbooks command.
+
+ if you cannot rely on atexit, use ReusableIndex.close_reusable() yourself.
+ """
+ index = None
+ pool = None
+ pool_jobs = None
+
+ def open(self, analyzer=None, threads=4):
+ if ReusableIndex.index is not None:
+ self.index = ReusableIndex.index
+ else:
+ print("opening index")
+ ReusableIndex.pool = ThreadPool(threads, initializer=lambda: JVM.attachCurrentThread() )
+ ReusableIndex.pool_jobs = []
+ Index.open(self, analyzer)
+ ReusableIndex.index = self.index
+ atexit.register(ReusableIndex.close_reusable)
+
+ def index_book(self, *args, **kw):
+ job = ReusableIndex.pool.apply_async(log_exception_wrapper(Index.index_book), (self,) + args, kw)
+ ReusableIndex.pool_jobs.append(job)
+
+ @staticmethod
+ def close_reusable():
+ if ReusableIndex.index is not None:
+ print("wait for indexing to finish")
+ for job in ReusableIndex.pool_jobs:
+ job.get()
+ sys.stdout.write('.')
+ sys.stdout.flush()
+ print("done.")
+ ReusableIndex.pool.close()
+
+ ReusableIndex.index.optimize()
+ ReusableIndex.index.close()
+ ReusableIndex.index = None
+
+ def close(self):
+ pass
+
+
+class Search(IndexStore):
+ def __init__(self, default_field="content"):
+ IndexStore.__init__(self)
+ self.analyzer = WLAnalyzer() #PolishAnalyzer(Version.LUCENE_34)
+ ## self.analyzer = WLAnalyzer()
+ self.searcher = IndexSearcher(self.store, True)
+ self.parser = QueryParser(Version.LUCENE_34, default_field,
+ self.analyzer)
+
+ self.parent_filter = TermsFilter()
+ self.parent_filter.addTerm(Term("is_book", "true"))
+
+ def query(self, query):
+ return self.parser.parse(query)
+
+ def wrapjoins(self, query, fields=[]):
+ """
+ This functions modifies the query in a recursive way,
+ so Term and Phrase Queries contained, which match
+ provided fields are wrapped in a BlockJoinQuery,
+ and so delegated to children documents.
+ """
+ if BooleanQuery.instance_(query):
+ qs = BooleanQuery.cast_(query)
+ for clause in qs:
+ clause = BooleanClause.cast_(clause)
+ clause.setQuery(self.wrapjoins(clause.getQuery(), fields))
+ return qs
+ else:
+ termset = HashSet()
+ query.extractTerms(termset)
+ for t in termset:
+ t = Term.cast_(t)
+ if t.field() not in fields:
+ return query
+ return BlockJoinQuery(query, self.parent_filter,
+ BlockJoinQuery.ScoreMode.Total)
+
+ def simple_search(self, query, max_results=50):
+ """Returns (books, total_hits)
+ """
+
+ tops = self.searcher.search(self.query(query), max_results)
+ bks = []
+ for found in tops.scoreDocs:
+ doc = self.searcher.doc(found.doc)
+ bks.append(catalogue.models.Book.objects.get(id=doc.get("book_id")))
+ return (bks, tops.totalHits)
+
+ def search(self, query, max_results=50):
+ query = self.query(query)
+ query = self.wrapjoins(query, ["content", "themes"])
+
+ tops = self.searcher.search(query, max_results)
+ bks = []
+ for found in tops.scoreDocs:
+ doc = self.searcher.doc(found.doc)
+ bks.append(catalogue.models.Book.objects.get(id=doc.get("book_id")))
+ return (bks, tops.totalHits)
+
+ def bsearch(self, query, max_results=50):
+ q = self.query(query)
+ bjq = BlockJoinQuery(q, self.parent_filter, BlockJoinQuery.ScoreMode.Avg)
+
+ tops = self.searcher.search(bjq, max_results)
+ bks = []
+ for found in tops.scoreDocs:
+ doc = self.searcher.doc(found.doc)
+ bks.append(catalogue.models.Book.objects.get(id=doc.get("book_id")))
+ return (bks, tops.totalHits)
+
+# TokenStream tokenStream = analyzer.tokenStream(fieldName, reader);
+# OffsetAttribute offsetAttribute = tokenStream.getAttribute(OffsetAttribute.class);
+# CharTermAttribute charTermAttribute = tokenStream.getAttribute(CharTermAttribute.class);
+
+# while (tokenStream.incrementToken()) {
+# int startOffset = offsetAttribute.startOffset();
+# int endOffset = offsetAttribute.endOffset();
+# String term = charTermAttribute.toString();
+# }
+
+
+class SearchResult(object):
+ def __init__(self, searcher, scoreDocs, score=None, highlight_query=None):
+ if score:
+ self.score = score
+ else:
+ self.score = scoreDocs.score
+
+ self.fragments = []
+ self.scores = {}
+ self.sections = []
+
+ stored = searcher.doc(scoreDocs.doc)
+ self.book_id = int(stored.get("book_id"))
+
+ fragment = stored.get("fragment_anchor")
+ if fragment:
+ self.fragments.append(fragment)
+ self.scores[fragment] = scoreDocs.score
+
+ header_type = stored.get("header_type")
+ if header_type:
+ sec = (header_type, int(stored.get("header_index")))
+ self.sections.append(sec)
+ self.scores[sec] = scoreDocs.score
+
+ self.snippets = []
+
+ def add_snippets(self, snippets):
+ self.snippets += snippets
+ return self
+
+ def get_book(self):
+ return catalogue.models.Book.objects.get(id=self.book_id)
+
+ book = property(get_book)
+
+ def get_parts(self):
+ book = self.book
+ parts = [{"header": s[0], "position": s[1], '_score_key': s} for s in self.sections] \
+ + [{"fragment": book.fragments.get(anchor=f), '_score_key':f} for f in self.fragments]
+
+ parts.sort(lambda a, b: cmp(self.scores[a['_score_key']], self.scores[b['_score_key']]))
+ print("bookid: %d parts: %s" % (self.book_id, parts))
+ return parts
+
+ parts = property(get_parts)
+
+ def merge(self, other):
+ if self.book_id != other.book_id:
+ raise ValueError("this search result is or book %d; tried to merge with %d" % (self.book_id, other.book_id))
+ self.fragments += other.fragments
+ self.sections += other.sections
+ self.snippets += other.snippets
+ self.scores.update(other.scores)
+ if other.score > self.score:
+ self.score = other.score
+ return self
+
+ def __unicode__(self):
+ return u'SearchResult(book_id=%d, score=%d)' % (self.book_id, self.score)
+
+ @staticmethod
+ def aggregate(*result_lists):
+ books = {}
+ for rl in result_lists:
+ for r in rl:
+ if r.book_id in books:
+ books[r.book_id].merge(r)
+ #print(u"already have one with score %f, and this one has score %f" % (books[book.id][0], found.score))
+ else:
+ books[r.book_id] = r
+ return books.values()
+
+ def __cmp__(self, other):
+ return cmp(self.score, other.score)
+
+
+class MultiSearch(Search):
+ """Class capable of IMDb-like searching"""
+ def get_tokens(self, searched, field='content'):
+ """returns tokens analyzed by a proper (for a field) analyzer
+ argument can be: StringReader, string/unicode, or tokens. In the last case
+ they will just be returned (so we can reuse tokens, if we don't change the analyzer)
+ """
+ if isinstance(searched, str) or isinstance(searched, unicode):
+ searched = StringReader(searched)
+ elif isinstance(searched, list):
+ return searched
+
+ searched.reset()
+ tokens = self.analyzer.reusableTokenStream(field, searched)
+ toks = []
+ while tokens.incrementToken():
+ cta = tokens.getAttribute(CharTermAttribute.class_)
+ toks.append(cta.toString())
+ return toks
+
+ def fuzziness(self, fuzzy):
+ if not fuzzy:
+ return None
+ if isinstance(fuzzy, float) and fuzzy > 0.0 and fuzzy <= 1.0:
+ return fuzzy
+ else:
+ return 0.5
+
+ def make_phrase(self, tokens, field='content', slop=2, fuzzy=False):
+ if fuzzy:
+ phrase = MultiPhraseQuery()
+ for t in tokens:
+ term = Term(field, t)
+ fuzzterm = FuzzyTermEnum(self.searcher.getIndexReader(), term, self.fuzziness(fuzzy))
+ fuzzterms = []
+
+ while True:
+ # print("fuzz %s" % unicode(fuzzterm.term()).encode('utf-8'))
+ ft = fuzzterm.term()
+ if ft:
+ fuzzterms.append(ft)
+ if not fuzzterm.next(): break
+ if fuzzterms:
+ phrase.add(JArray('object')(fuzzterms, Term))
+ else:
+ phrase.add(term)
+ else:
+ phrase = PhraseQuery()
+ phrase.setSlop(slop)
+ for t in tokens:
+ term = Term(field, t)
+ phrase.add(term)
+ return phrase
+
+ def make_term_query(self, tokens, field='content', modal=BooleanClause.Occur.SHOULD, fuzzy=False):
+ q = BooleanQuery()
+ for t in tokens:
+ term = Term(field, t)
+ if fuzzy:
+ term = FuzzyQuery(term, self.fuzziness(fuzzy))
+ else:
+ term = TermQuery(term)
+ q.add(BooleanClause(term, modal))
+ return q
+
+ def content_query(self, query):
+ return BlockJoinQuery(query, self.parent_filter,
+ BlockJoinQuery.ScoreMode.Total)
+
+ def search_perfect_book(self, searched, max_results=20, fuzzy=False):
+ qrys = [self.make_phrase(self.get_tokens(searched, field=fld), field=fld, fuzzy=fuzzy) for fld in ['author', 'title']]
+
+ books = []
+ for q in qrys:
+ top = self.searcher.search(q, max_results)
+ for found in top.scoreDocs:
+ books.append(SearchResult(self.searcher, found))
+ return books
+
+ def search_perfect_parts(self, searched, max_results=20, fuzzy=False):
+ qrys = [self.make_phrase(self.get_tokens(searched), field=fld, fuzzy=fuzzy) for fld in ['content']]
+
+ books = []
+ for q in qrys:
+ top = self.searcher.search(q, max_results)
+ for found in top.scoreDocs:
+ books.append(SearchResult(self.searcher, found).add_snippets(self.get_snippets(found, q)))
+
+ return books
+
+ def search_everywhere(self, searched, max_results=20, fuzzy=False):
+ books = []
+
+ # content only query : themes x content
+ q = BooleanQuery()
+
+ tokens = self.get_tokens(searched)
+ q.add(BooleanClause(self.make_term_query(tokens, field='themes', fuzzy=fuzzy), BooleanClause.Occur.MUST))
+ q.add(BooleanClause(self.make_term_query(tokens, field='content', fuzzy=fuzzy), BooleanClause.Occur.SHOULD))
+
+ topDocs = self.searcher.search(q, max_results)
+ for found in topDocs.scoreDocs:
+ books.append(SearchResult(self.searcher, found))
+
+ # joined query themes/content x author/title/epochs/genres/kinds
+ q = BooleanQuery()
+ in_meta = BooleanQuery()
+ in_content = BooleanQuery()
+
+ for fld in ['themes', 'content']:
+ in_content.add(BooleanClause(self.make_term_query(tokens, field=fld, fuzzy=False), BooleanClause.Occur.SHOULD))
+
+ in_meta.add(BooleanClause(self.make_term_query(self.get_tokens(searched, field='author'), field='author', fuzzy=fuzzy), BooleanClause.Occur.SHOULD))
+
+ for fld in ['title', 'epochs', 'genres', 'kinds']:
+ in_meta.add(BooleanClause(self.make_term_query(tokens, field=fld, fuzzy=fuzzy), BooleanClause.Occur.SHOULD))
+
+ q.add(BooleanClause(in_meta, BooleanClause.Occur.MUST))
+ in_content_join = self.content_query(in_content)
+ q.add(BooleanClause(in_content_join, BooleanClause.Occur.MUST))
+ # import pdb; pdb.set_trace()
+ collector = BlockJoinCollector(Sort.RELEVANCE, 100, True, True)
+
+ self.searcher.search(q, collector)
+
+ top_groups = collector.getTopGroups(in_content_join, Sort.RELEVANCE, 0, max_results, 0, True)
+ if top_groups:
+ for grp in top_groups.groups:
+ for part in grp.scoreDocs:
+ books.append(SearchResult(self.searcher, part, score=grp.maxScore))
+ return books
+
+ def multisearch(self, query, max_results=50):
+ """
+ Search strategy:
+ - (phrase) OR -> content
+ -> title
+ -> author
+ - (keywords) -> author
+ -> motyw
+ -> tags
+ -> content
+ """
+ # queryreader = StringReader(query)
+ # tokens = self.get_tokens(queryreader)
+
+ # top_level = BooleanQuery()
+ # Should = BooleanClause.Occur.SHOULD
+
+ # phrase_level = BooleanQuery()
+ # phrase_level.setBoost(1.3)
+
+ # p_content = self.make_phrase(tokens, joined=True)
+ # p_title = self.make_phrase(tokens, 'title')
+ # p_author = self.make_phrase(tokens, 'author')
+
+ # phrase_level.add(BooleanClause(p_content, Should))
+ # phrase_level.add(BooleanClause(p_title, Should))
+ # phrase_level.add(BooleanClause(p_author, Should))
+
+ # kw_level = BooleanQuery()
+
+ # kw_level.add(self.make_term_query(tokens, 'author'), Should)
+ # j_themes = self.make_term_query(tokens, 'themes', joined=True)
+ # kw_level.add(j_themes, Should)
+ # kw_level.add(self.make_term_query(tokens, 'tags'), Should)
+ # j_con = self.make_term_query(tokens, joined=True)
+ # kw_level.add(j_con, Should)
+
+ # top_level.add(BooleanClause(phrase_level, Should))
+ # top_level.add(BooleanClause(kw_level, Should))
+
+ return None
+
+
+ def do_search(self, query, max_results=50, collector=None):
+ tops = self.searcher.search(query, max_results)
+ #tops = self.searcher.search(p_content, max_results)
+
+ bks = []
+ for found in tops.scoreDocs:
+ doc = self.searcher.doc(found.doc)
+ b = catalogue.models.Book.objects.get(id=doc.get("book_id"))
+ bks.append(b)
+ print "%s (%d) -> %f" % (b, b.id, found.score)
+ return (bks, tops.totalHits)
+
+ def get_snippets(self, scoreDoc, query, field='content'):
+ htmlFormatter = SimpleHTMLFormatter()
+ highlighter = Highlighter(htmlFormatter, QueryScorer(query))
+
+ stored = self.searcher.doc(scoreDoc.doc)
+ text = stored.get(field)
+ tokenStream = TokenSources.getAnyTokenStream(self.searcher.getIndexReader(), scoreDoc.doc, field, self.analyzer)
+ # highlighter.getBestTextFragments(tokenStream, text, False, 10)
+ snip = highlighter.getBestFragments(tokenStream, text, 3, "...")
+ print('snips: %s' % snip)
+
+ return [snip]
fnp / wolnelektury.git / blobdiff