# -*- coding: utf-8 -*-
+
from django.conf import settings
from lucene import SimpleFSDirectory, IndexWriter, File, Field, \
NumericField, Version, Document, JavaError, IndexSearcher, \
SimpleAnalyzer, PolishAnalyzer, ArrayList, \
KeywordAnalyzer, NumericRangeQuery, BooleanQuery, \
BlockJoinQuery, BlockJoinCollector, TermsFilter, \
- HashSet, BooleanClause, Term
+ HashSet, BooleanClause, Term, CharTermAttribute, \
+ PhraseQuery, StringReader, TermQuery, BlockJoinQuery, \
+ Sort, Integer, \
+ initVM, CLASSPATH
# 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 WLAnalyzer(PerFieldAnalyzerWrapper):
def __init__(self):
'wywiad'
]
+ skip_header_tags = ['autor_utworu', 'nazwa_utworu', 'dzielo_nadrzedne']
+
def create_book_doc(self, book):
"""
Create a lucene document connected to the book
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))
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()
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.NO, Field.Index.ANALYZED))
+ doc.add(Field("content", content, Field.Store.YES, Field.Index.ANALYZED))
header_docs.append(doc)
def walker(node):
return u' '.join(map(
lambda x: x == None and u'(none)' or unicode(x),
l))
- s = u"Fragment %s complete, themes: %s contents: %s" % \
- (fid, jstr(frag['themes']), jstr(frag['content']))
- print(s.encode('utf-8'))
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.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))
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("closing index")
+ for job in ReusableIndex.pool_jobs:
+ job.get()
+ sys.stdout.write('.')
+ sys.stdout.flush()
+ 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)
def bsearch(self, query, max_results=50):
q = self.query(query)
- f = TermsFilter()
- f.addTerm(Term("is_book", "true"))
- bjq = BlockJoinQuery(q, f, BlockJoinQuery.ScoreMode.Avg)
+ bjq = BlockJoinQuery(q, self.parent_filter, BlockJoinQuery.ScoreMode.Avg)
tops = self.searcher.search(bjq, max_results)
bks = []
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):
+ 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
+
+ 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.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, queryreader):
+ if isinstance(queryreader, str) or isinstance(queryreader, unicode):
+ queryreader = StringReader(queryreader)
+ queryreader.reset()
+ tokens = self.analyzer.reusableTokenStream('content', queryreader)
+ 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)
+ return phrase
+
+ 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))
+ 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']]
+
+ 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, tokens, max_results=20):
+ qrys = [self.make_phrase(tokens, field=fld) 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))
+
+ 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:
+ 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)
fnp / wolnelektury.git / blobdiff