BlockJoinQuery, BlockJoinCollector, TermsFilter, \
HashSet, BooleanClause, Term, CharTermAttribute, \
PhraseQuery, StringReader, TermQuery, BlockJoinQuery, \
- Sort
+ Sort, Integer
# KeywordAnalyzer
import sys
import os
'wywiad'
]
- skip_header_tags = ['autor_utworu', 'nazwa_utworu']
+ skip_header_tags = ['autor_utworu', 'nazwa_utworu', 'dzielo_nadrzedne']
def create_book_doc(self, 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.NO, Field.Index.ANALYZED))
+ doc.add(Field("content", content, Field.Store.YES, Field.Index.ANALYZED))
header_docs.append(doc)
def walker(node):
Field.Store.YES, Field.Index.NOT_ANALYZED))
doc.add(Field("content",
u' '.join(filter(lambda s: s is not None, frag['content'])),
- Field.Store.NO, Field.Index.ANALYZED))
+ Field.Store.YES, Field.Index.ANALYZED))
doc.add(Field("themes",
u' '.join(filter(lambda s: s is not None, frag['themes'])),
Field.Store.NO, Field.Index.ANALYZED))
class MultiSearch(Search):
"""Class capable of IMDb-like searching"""
def get_tokens(self, queryreader):
- if isinstance(queryreader, str):
+ if isinstance(queryreader, str) or isinstance(queryreader, unicode):
queryreader = StringReader(queryreader)
queryreader.reset()
tokens = self.analyzer.reusableTokenStream('content', queryreader)
toks.append(cta.toString())
return toks
- def make_phrase(self, tokens, field='content', joined=False, slop=2):
+ 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)
- if joined:
- phrase = self.content_query(phrase)
return phrase
- def make_term_query(self, tokens, field='content', modal=BooleanClause.Occur.SHOULD, joined=False):
+ def make_term_query(self, tokens, field='content', modal=BooleanClause.Occur.SHOULD):
q = BooleanQuery()
for t in tokens:
term = Term(field, t)
q.add(BooleanClause(TermQuery(term), modal))
- if joined:
- q = self.content_query(q)
return q
def content_query(self, query):
return BlockJoinQuery(query, self.parent_filter,
BlockJoinQuery.ScoreMode.Total)
+ def search_perfect(self, tokens, max_results=20):
+ qrys = [self.make_phrase(tokens, field=fld) for fld in ['author', 'title', 'content']]
+
+ books = []
+ for q in qrys:
+ top = self.searcher.search(q, max_results)
+ for found in top.scoreDocs:
+ book_info = self.searcher.doc(found.doc)
+ books.append((found.score, catalogue.models.Book.objects.get(id=book_info.get("book_id")), []))
+ return books
+
+ def search_everywhere(self, tokens, max_results=20):
+ 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))
+
+ for fld in ['author', 'title', 'epochs', 'genres', 'kinds']:
+ in_meta.add(BooleanClause(self.make_term_query(tokens, field=fld), 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))
+
+ 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:
+ doc_id = Integer.cast_(grp.groupValue).intValue()
+ book_data = self.searcher.doc(doc_id)
+ book = catalogue.models.Book.objects.get(id=book_data.get("book_id"))
+ parts = []
+ for part in grp.scoreDocs:
+ part_data = self.searcher.doc(part.doc)
+ header_type = part_data.get("header_type")
+ if header_type:
+ parts.append((part.score, {"header": header_type, "position": int(part_data.get("header_index"))}))
+ fragment = part_data.get("fragment_anchor")
+ if fragment:
+ fragment = book.fragments.get(anchor=fragment)
+ parts.append((part.score, {"fragment": fragment}))
+ books.append((grp.maxScore, book, parts))
+
+ return books
+
+
def multisearch(self, query, max_results=50):
"""
Search strategy:
-> tags
-> content
"""
- queryreader = StringReader(query)
- tokens = self.get_tokens(queryreader)
-
- top_level = BooleanQuery()
- Should = BooleanClause.Occur.SHOULD
+ # queryreader = StringReader(query)
+ # tokens = self.get_tokens(queryreader)
- phrase_level = BooleanQuery()
- phrase_level.setBoost(1.3)
+ # top_level = BooleanQuery()
+ # Should = BooleanClause.Occur.SHOULD
- p_content = self.make_phrase(tokens, joined=True)
- p_title = self.makxe_phrase(tokens, 'title')
- p_author = self.make_phrase(tokens, 'author')
+ # phrase_level = BooleanQuery()
+ # phrase_level.setBoost(1.3)
- phrase_level.add(BooleanClause(p_content, Should))
- phrase_level.add(BooleanClause(p_title, Should))
- phrase_level.add(BooleanClause(p_author, Should))
+ # p_content = self.make_phrase(tokens, joined=True)
+ # p_title = self.make_phrase(tokens, 'title')
+ # p_author = self.make_phrase(tokens, 'author')
- kw_level = BooleanQuery()
+ # phrase_level.add(BooleanClause(p_content, Should))
+ # phrase_level.add(BooleanClause(p_title, Should))
+ # phrase_level.add(BooleanClause(p_author, Should))
- 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)
+ # kw_level = BooleanQuery()
- top_level.add(BooleanClause(phrase_level, Should))
- top_level.add(BooleanClause(kw_level, Should))
+ # 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)
- collector = BlockJoinCollector(Sort.RELEVANCE, 100, True, True)
-
- self.searcher.search(kw_level, collector)
+ # top_level.add(BooleanClause(phrase_level, Should))
+ # top_level.add(BooleanClause(kw_level, Should))
- # frazy w treści:
- # ph1 = collector.getTopGroups(j_themes, Sort.RELEVANCE,
- # 0, 10, 0, True)
- # reload(search.index); realod(search); s = search.MultiSearch(); s.multisearch(u'dusiołek')
- # ph2 = collector.getTopGroups(j_con, Sort.RELEVANCE,
- # 0, 10, 0, True)
-
- import pdb; pdb.set_trace();
-
return None
fnp / wolnelektury.git / blobdiff