from librarian.parser import WLDocument
from lxml import etree
import catalogue.models
+from pdcounter.models import Author as PDCounterAuthor
from multiprocessing.pool import ThreadPool
from threading import current_thread
import atexit
doc.add(Field("tag_category", tag.category, Field.Store.NO, Field.Index.NOT_ANALYZED))
self.index.addDocument(doc)
+ for pdtag in PDCounterAuthor.objects.all():
+ doc = Document()
+ doc.add(NumericField("tag_id", Field.Store.YES, True).setIntValue(int(pdtag.id)))
+ doc.add(Field("tag_name", pdtag.name, Field.Store.NO, Field.Index.ANALYZED))
+ doc.add(Field("tag_name_pl", pdtag.name, Field.Store.NO, Field.Index.ANALYZED))
+ doc.add(Field("tag_category", 'pdcounter', Field.Store.NO, Field.Index.NOT_ANALYZED))
+ doc.add(Field("is_pdcounter", 'true', Field.Store.YES, Field.Index.NOT_ANALYZED))
+ self.index.addDocument(doc)
+
def create_book_doc(self, book):
"""
Create a lucene document referring book id.
# get published date
source = book_info.source_name
- match = self.published_date_re.search(source)
- if match is not None:
- fields["published_date"] = Field("published_date", str(match.groups()[0]), Field.Store.YES, Field.Index.NOT_ANALYZED)
+ if hasattr(book_info, 'source_name'):
+ match = self.published_date_re.search(source)
+ if match is not None:
+ fields["published_date"] = Field("published_date", str(match.groups()[0]), Field.Store.YES, Field.Index.NOT_ANALYZED)
return fields
stored = search.searcher.doc(scoreDocs.doc)
self.book_id = int(stored.get("book_id"))
- header_type = stored.get("header_type")
- if not header_type:
- return
-
- sec = (header_type, int(stored.get("header_index")))
- header_span = stored.get('header_span')
- header_span = header_span is not None and int(header_span) or 1
-
- fragment = stored.get("fragment_anchor")
-
pd = stored.get("published_date")
if pd is None:
pd = 0
self.published_date = int(pd)
- if snippets:
- snippets = snippets.replace("/\n", "\n")
- hit = (sec + (header_span,), fragment, scoreDocs.score, {'how_found': how_found, 'snippets': snippets and [snippets] or []})
+ header_type = stored.get("header_type")
+ # we have a content hit in some header of fragment
+ if header_type is not None:
+ sec = (header_type, int(stored.get("header_index")))
+ header_span = stored.get('header_span')
+ header_span = header_span is not None and int(header_span) or 1
+
+ fragment = stored.get("fragment_anchor")
- self._hits.append(hit)
+ if snippets:
+ snippets = snippets.replace("/\n", "\n")
+ hit = (sec + (header_span,), fragment, scoreDocs.score, {'how_found': how_found, 'snippets': snippets and [snippets] or []})
+
+ self._hits.append(hit)
self.search = search
self.searched = searched
if terms:
return JArray('object')(terms, Term)
- def search_tags(self, query, filter=None, max_results=40):
+ def search_tags(self, query, filters=None, max_results=40, pdcounter=False):
"""
Search for Tag objects using query.
"""
- tops = self.searcher.search(query, filter, max_results)
+ if not pdcounter:
+ filters = self.chain_filters([filter, self.term_filter(Term('is_pdcounter', 'true'), inverse=True)])
+ tops = self.searcher.search(query, filters, max_results)
tags = []
for found in tops.scoreDocs:
doc = self.searcher.doc(found.doc)
- tag = catalogue.models.Tag.objects.get(id=doc.get("tag_id"))
- tags.append(tag)
- print "%s (%d) -> %f" % (tag, tag.id, found.score)
-
+ is_pdcounter = doc.get('is_pdcounter')
+ if is_pdcounter:
+ tag = PDCounterAuthor.objects.get(id=doc.get('tag_id'))
+ else:
+ tag = catalogue.models.Tag.objects.get(id=doc.get("tag_id"))
+ # don't add the pdcounter tag if same tag already exists
+ if not (is_pdcounter and filter(lambda t: tag.slug == t.slug, tags)):
+ tags.append(tag)
+ # print "%s (%d) -> %f" % (tag, tag.id, found.score)
+ print 'returning %s' % tags
return tags
def search_books(self, query, filter=None, max_results=10):
bks.append(catalogue.models.Book.objects.get(id=doc.get("book_id")))
return bks
- def create_prefix_phrase(self, toks, field):
+ def make_prefix_phrase(self, toks, field):
q = MultiPhraseQuery()
for i in range(len(toks)):
t = Term(field, toks[i])
return only_term
- def hint_tags(self, string, max_results=50):
+ def hint_tags(self, string, max_results=50, pdcounter=True, prefix=True):
"""
Return auto-complete hints for tags
using prefix search.
top = BooleanQuery()
for field in ['tag_name', 'tag_name_pl']:
- q = self.create_prefix_phrase(toks, field)
+ if prefix:
+ q = self.make_prefix_phrase(toks, field)
+ else:
+ q = self.make_term_query(toks, field)
top.add(BooleanClause(q, BooleanClause.Occur.SHOULD))
no_book_cat = self.term_filter(Term("tag_category", "book"), inverse=True)
- return self.search_tags(top, no_book_cat, max_results=max_results)
+ return self.search_tags(top, no_book_cat, max_results=max_results, pdcounter=pdcounter)
- def hint_books(self, string, max_results=50):
+ def hint_books(self, string, max_results=50, prefix=True):
"""
Returns auto-complete hints for book titles
Because we do not index 'pseudo' title-tags.
"""
toks = self.get_tokens(string, field='SIMPLE')
- q = self.create_prefix_phrase(toks, 'title')
+ if prefix:
+ q = self.make_prefix_phrase(toks, 'title')
+ else:
+ q = self.make_term_query(toks, 'title')
return self.search_books(q, self.term_filter(Term("is_book", "true")), max_results=max_results)
fnp / wolnelektury.git / blobdiff