from django.conf import settings
from lucene import SimpleFSDirectory, IndexWriter, File, Field, \
NumericField, Version, Document, JavaError, IndexSearcher, \
- QueryParser, Term, PerFieldAnalyzerWrapper, \
+ QueryParser, PerFieldAnalyzerWrapper, \
SimpleAnalyzer, PolishAnalyzer, ArrayList, \
KeywordAnalyzer, NumericRangeQuery, BooleanQuery, \
BlockJoinQuery, BlockJoinCollector, TermsFilter, \
HashSet, BooleanClause, Term, CharTermAttribute, \
- PhraseQuery, StringReader, TermQuery, BlockJoinQuery, \
- Sort, Integer, \
- initVM, CLASSPATH
+ PhraseQuery, MultiPhraseQuery, StringReader, TermQuery, BlockJoinQuery, \
+ FuzzyQuery, FuzzyTermEnum, Sort, Integer, \
+ SimpleHTMLFormatter, Highlighter, QueryScorer, TokenSources, TextFragment, \
+ initVM, CLASSPATH, JArray
# KeywordAnalyzer
JVM = initVM(CLASSPATH)
import sys
import atexit
import traceback
+
class WLAnalyzer(PerFieldAnalyzerWrapper):
def __init__(self):
polish = PolishAnalyzer(Version.LUCENE_34)
self.addAnalyzer("author", simple)
self.addAnalyzer("is_book", keyword)
- #self.addanalyzer("fragment_anchor", keyword)
+ self.addAnalyzer("KEYWORD", keyword)
+ self.addAnalyzer("SIMPLE", simple)
+ self.addAnalyzer("NATURAL", polish)
class IndexStore(object):
self.index = None
def remove_book(self, book):
- q = NumericRangeQuery.newIntRange("book_id", book.id, book.id, True,True)
+ q = NumericRangeQuery.newIntRange("book_id", book.id, book.id, True, True)
self.index.deleteDocuments(q)
def index_book(self, book, overwrite=True):
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("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
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()
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:
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.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))
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
+ try:
+ f(*a)
+ except Exception, e:
+ print("Error in indexing thread: %s" % e)
+ traceback.print_exc()
+ raise e
return _wrap
class Search(IndexStore):
def __init__(self, default_field="content"):
IndexStore.__init__(self)
- self.analyzer = PolishAnalyzer(Version.LUCENE_34)
+ self.analyzer = WLAnalyzer() #PolishAnalyzer(Version.LUCENE_34)
## self.analyzer = WLAnalyzer()
self.searcher = IndexSearcher(self.store, True)
self.parser = QueryParser(Version.LUCENE_34, default_field,
class SearchResult(object):
- def __init__(self, searcher, scoreDocs, score=None):
+ def __init__(self, searcher, scoreDocs, score=None, highlight_query=None):
if score:
self.score = score
else:
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)
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
class MultiSearch(Search):
"""Class capable of IMDb-like searching"""
- def get_tokens(self, queryreader):
- if isinstance(queryreader, str) or isinstance(queryreader, unicode):
- queryreader = StringReader(queryreader)
- queryreader.reset()
- tokens = self.analyzer.reusableTokenStream('content', queryreader)
+ 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 make_phrase(self, tokens, field='content', slop=2):
- phrase = PhraseQuery()
- phrase.setSlop(slop)
- for t in tokens:
- term = Term(field, t)
- phrase.add(term)
+ 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):
+ def make_term_query(self, tokens, field='content', modal=BooleanClause.Occur.SHOULD, fuzzy=False):
q = BooleanQuery()
for t in tokens:
term = Term(field, t)
- q.add(BooleanClause(TermQuery(term), modal))
+ 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, tokens, max_results=20):
- qrys = [self.make_phrase(tokens, field=fld) for fld in ['author', 'title']]
+ 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:
books.append(SearchResult(self.searcher, found))
return books
- def search_perfect_parts(self, tokens, max_results=20):
- qrys = [self.make_phrase(tokens, field=fld) for fld in ['content']]
+ 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))
+ books.append(SearchResult(self.searcher, found).add_snippets(self.get_snippets(found, q)))
return books
- def search_everywhere(self, tokens, max_results=20):
+ 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), BooleanClause.Occur.SHOULD))
+ 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 ['author', 'title', 'epochs', 'genres', 'kinds']:
- in_meta.add(BooleanClause(self.make_term_query(tokens, field=fld), 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)
- books = []
-
top_groups = collector.getTopGroups(in_content_join, Sort.RELEVANCE, 0, max_results, 0, True)
if top_groups:
for grp in top_groups.groups:
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.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 / commitdiff