+ IndexStore.__init__(self)
+
+ def check(self):
+ checker = CheckIndex(self.store)
+ status = checker.checkIndex()
+ return status
+
+
+class Snippets(object):
+ """
+ This class manages snippet files for indexed object (book)
+ the snippets are concatenated together, and their positions and
+ lengths are kept in lucene index fields.
+ """
+ SNIPPET_DIR = "snippets"
+
+ def __init__(self, book_id):
+ try:
+ os.makedirs(os.path.join(settings.SEARCH_INDEX, self.SNIPPET_DIR))
+ except OSError as exc:
+ if exc.errno == errno.EEXIST:
+ pass
+ else: raise
+ self.book_id = book_id
+ self.file = None
+
+ def open(self, mode='r'):
+ """
+ Open the snippet file. Call .close() afterwards.
+ """
+ if not 'b' in mode:
+ mode += 'b'
+ self.file = open(os.path.join(settings.SEARCH_INDEX, self.SNIPPET_DIR, str(self.book_id)), mode)
+ self.position = 0
+ return self
+
+ def add(self, snippet):
+ """
+ Append a snippet (unicode) to the snippet file.
+ Return a (position, length) tuple
+ """
+ txt = snippet.encode('utf-8')
+ l = len(txt)
+ self.file.write(txt)
+ pos = (self.position, l)
+ self.position += l
+ return pos
+
+ def get(self, pos):
+ """
+ Given a tuple of (position, length) return an unicode
+ of the snippet stored there.
+ """
+ self.file.seek(pos[0], 0)
+ txt = self.file.read(pos[1]).decode('utf-8')
+ return txt
+
+ def close(self):
+ """Close snippet file"""
+ self.file.close()
+
+
+class BaseIndex(IndexStore):
+ """
+ Base index class.
+ Provides basic operations on index: opening, closing, optimizing.
+ """
+ def __init__(self, analyzer=None):
+ super(BaseIndex, self).__init__()
+ 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 optimize(self):
+ self.index.optimize()
+
+ def close(self):
+ try:
+ self.index.optimize()
+ except JavaError, je:
+ print "Error during optimize phase, check index: %s" % je
+
+ self.index.close()
+ self.index = None
+
+ def __enter__(self):
+ self.open()
+ return self
+
+ def __exit__(self, type, value, tb):
+ self.close()
+
+
+class Index(BaseIndex):
+ """
+ Class indexing books.
+ """
+ def __init__(self, analyzer=None):
+ super(Index, self).__init__(analyzer)
+
+ def index_tags(self):
+ """
+ Re-index global tag list.
+ Removes all tags from index, then index them again.
+ Indexed fields include: id, name (with and without polish stems), category
+ """
+ q = NumericRangeQuery.newIntRange("tag_id", 0, Integer.MAX_VALUE, True, True)
+ self.index.deleteDocuments(q)
+
+ for tag in catalogue.models.Tag.objects.all():
+ doc = Document()
+ doc.add(NumericField("tag_id", Field.Store.YES, True).setIntValue(int(tag.id)))
+ doc.add(Field("tag_name", tag.name, Field.Store.NO, Field.Index.ANALYZED))
+ doc.add(Field("tag_name_pl", tag.name, Field.Store.NO, Field.Index.ANALYZED))
+ 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.
+ """
+ doc = Document()
+ doc.add(NumericField("book_id", Field.Store.YES, True).setIntValue(int(book.id)))
+ if book.parent is not None:
+ doc.add(NumericField("parent_id", Field.Store.YES, True).setIntValue(int(book.parent.id)))
+ return doc
+
+ def remove_book(self, book):
+ """Removes a book from search index.
+ book - Book instance."""
+ q = NumericRangeQuery.newIntRange("book_id", book.id, book.id, True, True)
+ self.index.deleteDocuments(q)
+
+ def index_book(self, book, book_info=None, overwrite=True):
+ """
+ Indexes the book.
+ Creates a lucene document for extracted metadata
+ and calls self.index_content() to index the contents of the book.
+ """
+ if overwrite:
+ self.remove_book(book)
+
+ book_doc = self.create_book_doc(book)
+ meta_fields = self.extract_metadata(book, book_info)
+ for f in meta_fields.values():
+ if isinstance(f, list) or isinstance(f, tuple):
+ for elem in f:
+ book_doc.add(elem)
+ else:
+ book_doc.add(f)
+
+ self.index.addDocument(book_doc)
+ del book_doc
+
+ self.index_content(book, book_fields=[meta_fields['title'], meta_fields['authors'], meta_fields['published_date']])
+
+ master_tags = [
+ 'opowiadanie',
+ 'powiesc',
+ 'dramat_wierszowany_l',
+ 'dramat_wierszowany_lp',
+ 'dramat_wspolczesny', 'liryka_l', 'liryka_lp',
+ 'wywiad',
+ ]
+
+ ignore_content_tags = [
+ 'uwaga', 'extra',
+ 'zastepnik_tekstu', 'sekcja_asterysk', 'separator_linia', 'zastepnik_wersu',
+ 'didaskalia',
+ 'naglowek_aktu', 'naglowek_sceny', 'naglowek_czesc',
+ ]
+
+ footnote_tags = ['pa', 'pt', 'pr', 'pe']
+
+ skip_header_tags = ['autor_utworu', 'nazwa_utworu', 'dzielo_nadrzedne', '{http://www.w3.org/1999/02/22-rdf-syntax-ns#}RDF']
+
+ published_date_re = re.compile("([0-9]+)[\]. ]*$")
+
+ def extract_metadata(self, book, book_info=None):
+ """
+ Extract metadata from book and returns a map of fields keyed by fieldname
+ """
+ fields = {}
+
+ if book_info is None:
+ book_info = dcparser.parse(open(book.xml_file.path))
+
+ fields['slug'] = Field("slug", book.slug, Field.Store.NO, Field.Index.ANALYZED_NO_NORMS)
+ fields['tags'] = self.add_gaps([Field("tags", t.name, Field.Store.NO, Field.Index.ANALYZED) for t in book.tags], 'tags')
+ fields['is_book'] = 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:
+ fields[field.name] = 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))
+ fields[field.name] = Field(field.name, persons, Field.Store.NO, Field.Index.ANALYZED)
+ elif type_indicator == dcparser.as_date:
+ dt = getattr(book_info, field.name)
+ fields[field.name] = Field(field.name, "%04d%02d%02d" %\
+ (dt.year, dt.month, dt.day), Field.Store.NO, Field.Index.NOT_ANALYZED)
+
+ # get published date
+ pd = None
+ if hasattr(book_info, 'source_name') and book_info.source_name:
+ match = self.published_date_re.search(book_info.source_name)
+ if match is not None:
+ pd = str(match.groups()[0])
+ if not pd: pd = ""
+ fields["published_date"] = Field("published_date", pd, Field.Store.YES, Field.Index.NOT_ANALYZED)
+
+ return fields
+
+ def add_gaps(self, fields, fieldname):
+ """
+ Interposes a list of fields with gap-fields, which are indexed spaces and returns it.
+ This allows for doing phrase queries which do not overlap the gaps (when slop is 0).
+ """
+ def gap():
+ while True:
+ yield Field(fieldname, ' ', Field.Store.NO, Field.Index.NOT_ANALYZED)
+ return reduce(lambda a, b: a + b, zip(fields, gap()))[0:-1]
+
+ def get_master(self, root):
+ """
+ Returns the first master tag from an etree.
+ """
+ for master in root.iter():
+ if master.tag in self.master_tags:
+ return master
+
+ def index_content(self, book, book_fields=[]):
+ """
+ Walks the book XML and extract content from it.
+ Adds parts for each header tag and for each fragment.
+ """
+ wld = WLDocument.from_file(book.xml_file.path, parse_dublincore=False)
+ root = wld.edoc.getroot()
+
+ master = self.get_master(root)
+ if master is None:
+ return []
+
+ def walker(node, ignore_tags=[]):
+
+ if node.tag not in ignore_tags:
+ yield node, None, None
+ if node.text is not None:
+ yield None, node.text, None
+ for child in list(node):
+ for b, t, e in walker(child):
+ yield b, t, e
+ yield None, None, node
+
+ if node.tail is not None:
+ yield None, node.tail, None
+ return
+
+ def fix_format(text):
+ # separator = [u" ", u"\t", u".", u";", u","]
+ if isinstance(text, list):
+ # need to join it first
+ text = filter(lambda s: s is not None, content)
+ text = u' '.join(text)
+ # for i in range(len(text)):
+ # if i > 0:
+ # if text[i][0] not in separator\
+ # and text[i - 1][-1] not in separator:
+ # text.insert(i, u" ")
+
+ return re.sub("(?m)/$", "", text)
+
+ def add_part(snippets, **fields):
+ doc = self.create_book_doc(book)
+ for f in book_fields:
+ doc.add(f)
+
+ doc.add(NumericField('header_index', Field.Store.YES, True).setIntValue(fields["header_index"]))
+ doc.add(NumericField("header_span", Field.Store.YES, True)\
+ .setIntValue('header_span' in fields and fields['header_span'] or 1))
+ doc.add(Field('header_type', fields["header_type"], Field.Store.YES, Field.Index.NOT_ANALYZED))
+
+ doc.add(Field('content', fields["content"], Field.Store.NO, Field.Index.ANALYZED, \
+ Field.TermVector.WITH_POSITIONS_OFFSETS))
+
+ snip_pos = snippets.add(fields["content"])
+ doc.add(NumericField("snippets_position", Field.Store.YES, True).setIntValue(snip_pos[0]))
+ doc.add(NumericField("snippets_length", Field.Store.YES, True).setIntValue(snip_pos[1]))
+
+ if 'fragment_anchor' in fields:
+ doc.add(Field("fragment_anchor", fields['fragment_anchor'],
+ Field.Store.YES, Field.Index.NOT_ANALYZED))
+
+ if 'themes' in fields:
+ themes, themes_pl = zip(*[
+ (Field("themes", theme, Field.Store.YES, Field.Index.ANALYZED, Field.TermVector.WITH_POSITIONS),
+ Field("themes_pl", theme, Field.Store.NO, Field.Index.ANALYZED, Field.TermVector.WITH_POSITIONS))
+ for theme in fields['themes']])
+
+ themes = self.add_gaps(themes, 'themes')
+ themes_pl = self.add_gaps(themes_pl, 'themes_pl')
+
+ for t in themes:
+ doc.add(t)
+ for t in themes_pl:
+ doc.add(t)
+
+ return doc
+
+ def give_me_utf8(s):
+ if isinstance(s, unicode):
+ return s.encode('utf-8')
+ else:
+ return s
+
+ fragments = {}
+ snippets = Snippets(book.id).open('w')
+ try:
+ for header, position in zip(list(master), range(len(master))):
+
+ if header.tag in self.skip_header_tags:
+ continue
+ if header.tag is etree.Comment:
+ continue
+
+ # section content
+ content = []
+ footnote = []
+
+ def all_content(text):
+ for frag in fragments.values():
+ frag['content'].append(text)
+ content.append(text)
+ handle_text = [all_content]
+
+
+ for start, text, end in walker(header, ignore_tags=self.ignore_content_tags):
+ # handle footnotes
+ if start is not None and start.tag in self.footnote_tags:
+ footnote = []
+ def collect_footnote(t):
+ footnote.append(t)
+ handle_text.append(collect_footnote)
+ elif end is not None and footnote is not [] and end.tag in self.footnote_tags:
+ handle_text.pop()
+ doc = add_part(snippets, header_index=position, header_type=header.tag,
+ content=u''.join(footnote),
+ is_footnote=Field("is_footnote", 'true', Field.Store.NO, Field.Index.NOT_ANALYZED))
+
+ self.index.addDocument(doc)
+ #print "@ footnote text: %s" % footnote
+ footnote = []
+
+ # handle fragments and themes.
+ if start is not None and start.tag == 'begin':
+ fid = start.attrib['id'][1:]
+ fragments[fid] = {'content': [], 'themes': [], 'start_section': position, 'start_header': header.tag}
+
+ # themes for this fragment
+ elif start is not None and start.tag == 'motyw':
+ fid = start.attrib['id'][1:]
+ handle_text.append(None)
+ if start.text is not None:
+ fragments[fid]['themes'] += map(str.strip, map(give_me_utf8, start.text.split(',')))
+ elif end is not None and end.tag == 'motyw':
+ handle_text.pop()
+
+ 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]
+ if frag['themes'] == []:
+ continue # empty themes list.
+ del fragments[fid]
+
+ doc = add_part(snippets,
+ header_type=frag['start_header'],
+ header_index=frag['start_section'],
+ header_span=position - frag['start_section'] + 1,
+ fragment_anchor=fid,
+ content=fix_format(frag['content']),
+ themes=frag['themes'])
+ #print '@ FRAG %s' % frag['content']
+ self.index.addDocument(doc)
+
+ # Collect content.
+
+ if text is not None and handle_text is not []:
+ hdl = handle_text[-1]
+ if hdl is not None:
+ hdl(text)
+
+ # in the end, add a section text.
+ doc = add_part(snippets, header_index=position, header_type=header.tag,
+ content=fix_format(content))
+ #print '@ CONTENT: %s' % fix_format(content)
+
+ self.index.addDocument(doc)
+
+ finally:
+ snippets.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
+
+ def open(self, analyzer=None, threads=4):
+ if ReusableIndex.index is not None:
+ self.index = ReusableIndex.index
+ else:
+ print("opening index")
+ 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:
+ ReusableIndex.index.optimize()
+ ReusableIndex.index.close()
+ ReusableIndex.index = None
+
+ def close(self):
+ pass
+
+
+class JoinSearch(object):
+ """
+ This mixin could be used to handle block join queries.
+ (currently unused)
+ """
+ def __init__(self, *args, **kw):
+ super(JoinSearch, self).__init__(*args, **kw)
+
+ 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 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)
+
+
+class SearchResult(object):
+ def __init__(self, search, scoreDocs, score=None, how_found=None, snippets=None, searched=None, tokens_cache=None):
+ if tokens_cache is None: tokens_cache = {}
+
+ if score:
+ self._score = score
+ else:
+ self._score = scoreDocs.score
+
+ self.boost = 1.0
+
+ self._hits = []
+ self._processed_hits = None # processed hits
+
+ stored = search.searcher.doc(scoreDocs.doc)
+ self.book_id = int(stored.get("book_id"))
+
+ pd = stored.get("published_date")
+ if pd is None:
+ pd = 0
+ self.published_date = int(pd)
+
+ 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")
+
+ 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
+ self.tokens_cache = tokens_cache
+
+ @property
+ def score(self):
+ return self._score * self.boost
+
+ 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._hits += other._hits
+ if other.score > self.score:
+ self._score = other._score
+ return self
+
+ def get_book(self):
+ return catalogue.models.Book.objects.get(id=self.book_id)
+
+ book = property(get_book)
+
+ @property
+ def hits(self):
+ if self._processed_hits is not None:
+ return self._processed_hits
+
+ POSITION = 0
+ FRAGMENT = 1
+ POSITION_INDEX = 1
+ POSITION_SPAN = 2
+ SCORE = 2
+ OTHER = 3
+
+ # to sections and fragments
+ frags = filter(lambda r: r[FRAGMENT] is not None, self._hits)
+ sect = filter(lambda r: r[FRAGMENT] is None, self._hits)
+ sect = filter(lambda s: 0 == len(filter(
+ lambda f: s[POSITION][POSITION_INDEX] >= f[POSITION][POSITION_INDEX]
+ and s[POSITION][POSITION_INDEX] < f[POSITION][POSITION_INDEX] + f[POSITION][POSITION_SPAN],
+ frags)), sect)
+
+ hits = []
+
+ # remove duplicate fragments
+ fragments = {}
+ for f in frags:
+ fid = f[FRAGMENT]
+ if fid in fragments:
+ if fragments[fid][SCORE] >= f[SCORE]:
+ continue
+ fragments[fid] = f
+ frags = fragments.values()
+
+ # remove duplicate sections
+ sections = {}
+
+ for s in sect:
+ si = s[POSITION][POSITION_INDEX]
+ # skip existing
+ if si in sections:
+ if sections[si]['score'] >= s[SCORE]:
+ continue
+
+ m = {'score': s[SCORE],
+ 'section_number': s[POSITION][POSITION_INDEX] + 1,
+ }
+ m.update(s[OTHER])
+ sections[si] = m
+
+ hits = sections.values()
+
+ for f in frags:
+ try:
+ frag = catalogue.models.Fragment.objects.get(anchor=f[FRAGMENT])
+ except catalogue.models.Fragment.DoesNotExist:
+ # stale index
+ continue
+
+ # Figure out if we were searching for a token matching some word in theme name.
+ themes = frag.tags.filter(category='theme')
+ themes_hit = []
+ if self.searched is not None:
+ tokens = self.search.get_tokens(self.searched, 'POLISH', cached=self.tokens_cache)
+ for theme in themes:
+ name_tokens = self.search.get_tokens(theme.name, 'POLISH')
+ for t in tokens:
+ if t in name_tokens:
+ if not theme in themes_hit:
+ themes_hit.append(theme)
+ break
+
+ m = {'score': f[SCORE],
+ 'fragment': frag,
+ 'section_number': f[POSITION][POSITION_INDEX] + 1,
+ 'themes': themes,
+ 'themes_hit': themes_hit
+ }
+ m.update(f[OTHER])
+ hits.append(m)
+
+ hits.sort(lambda a, b: cmp(a['score'], b['score']), reverse=True)
+
+ self._processed_hits = hits
+
+ return hits
+
+ 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):
+ c = cmp(self.score, other.score)
+ if c == 0:
+ # this is inverted, because earlier date is better
+ return cmp(other.published_date, self.published_date)
+ else:
+ return c
+
+
+class Hint(object):
+ """
+ Given some hint information (information we already know about)
+ our search target - like author, title (specific book), epoch, genre, kind
+ we can narrow down search using filters.
+ """
+ def __init__(self, search):
+ """
+ Accepts a Searcher instance.
+ """
+ self.search = search
+ self.book_tags = {}
+ self.part_tags = []
+ self._books = []
+
+ def books(self, *books):
+ """
+ Give a hint that we search these books.
+ """
+ self._books = books
+
+ def tags(self, tags):
+ """
+ Give a hint that these Tag objects (a list of)
+ is necessary.
+ """
+ for t in tags:
+ if t.category in ['author', 'title', 'epoch', 'genre', 'kind']:
+ lst = self.book_tags.get(t.category, [])
+ lst.append(t)
+ self.book_tags[t.category] = lst
+ if t.category in ['theme', 'theme_pl']:
+ self.part_tags.append(t)
+
+ def tag_filter(self, tags, field='tags'):
+ """
+ Given a lsit of tags and an optional field (but they are normally in tags field)
+ returns a filter accepting only books with specific tags.
+ """
+ q = BooleanQuery()
+
+ for tag in tags:
+ toks = self.search.get_tokens(tag.name, field=field)
+ tag_phrase = PhraseQuery()
+ for tok in toks:
+ tag_phrase.add(Term(field, tok))
+ q.add(BooleanClause(tag_phrase, BooleanClause.Occur.MUST))
+
+ return QueryWrapperFilter(q)
+
+ def book_filter(self):
+ """
+ Filters using book tags (all tag kinds except a theme)
+ """
+ tags = reduce(lambda a, b: a + b, self.book_tags.values(), [])
+ if tags:
+ return self.tag_filter(tags)
+ else:
+ return None
+
+ def part_filter(self):
+ """
+ This filter can be used to look for book parts.
+ It filters on book id and/or themes.
+ """
+ fs = []
+ if self.part_tags:
+ fs.append(self.tag_filter(self.part_tags, field='themes'))
+
+ if self._books != []:
+ bf = BooleanFilter()
+ for b in self._books:
+ id_filter = NumericRangeFilter.newIntRange('book_id', b.id, b.id, True, True)
+ bf.add(FilterClause(id_filter, BooleanClause.Occur.SHOULD))
+ fs.append(bf)
+
+ return Search.chain_filters(fs)
+
+ def should_search_for_book(self):
+ return self._books == []
+
+ def just_search_in(self, all):
+ """Holds logic to figure out which indexes should be search, when we have some hinst already"""
+ some = []
+ for field in all:
+ if field == 'authors' and 'author' in self.book_tags:
+ continue
+ if field == 'title' and self._books != []:
+ continue
+ if (field == 'themes' or field == 'themes_pl') and self.part_tags:
+ continue
+ some.append(field)
+ return some
+
+
+class Search(IndexStore):
+ """
+ Search facilities.
+ """
+ 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):
+ """Parse query in default Lucene Syntax. (for humans)
+ """
+ return self.parser.parse(query)
+
+ def simple_search(self, query, max_results=50):
+ """Runs a query for books using lucene syntax. (for humans)
+ 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 get_tokens(self, searched, field='content', cached=None):
+ """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 cached is not None and field in cached:
+ return cached[field]
+
+ 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())
+
+ if cached is not None:
+ cached[field] = toks
+
+ return toks
+
+ def fuzziness(self, fuzzy):
+ """Helper method to sanitize fuzziness"""
+ 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):
+ """
+ Return a PhraseQuery with a series of tokens.
+ """
+ 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):
+ """
+ Returns term queries joined by boolean query.
+ modal - applies to boolean query
+ fuzzy - should the query by fuzzy.
+ """
+ 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 search_phrase(self, searched, field, book=True, max_results=20, fuzzy=False,
+ filters=None, tokens_cache=None, boost=None, snippets=False, slop=2):
+ if filters is None: filters = []
+ if tokens_cache is None: tokens_cache = {}
+
+ tokens = self.get_tokens(searched, field, cached=tokens_cache)
+
+ query = self.make_phrase(tokens, field=field, fuzzy=fuzzy, slop=slop)
+ if book:
+ filters.append(self.term_filter(Term('is_book', 'true')))
+ top = self.searcher.search(query, self.chain_filters(filters), max_results)
+
+ return [SearchResult(self, found, snippets=(snippets and self.get_snippets(found, query) or None), searched=searched) for found in top.scoreDocs]
+
+ def search_some(self, searched, fields, book=True, max_results=20, fuzzy=False,
+ filters=None, tokens_cache=None, boost=None, snippets=True):
+ if filters is None: filters = []
+ if tokens_cache is None: tokens_cache = {}
+
+ if book:
+ filters.append(self.term_filter(Term('is_book', 'true')))
+
+ query = BooleanQuery()
+
+ for fld in fields:
+ tokens = self.get_tokens(searched, fld, cached=tokens_cache)
+
+ query.add(BooleanClause(self.make_term_query(tokens, field=fld,
+ fuzzy=fuzzy), BooleanClause.Occur.SHOULD))
+
+ top = self.searcher.search(query, self.chain_filters(filters), max_results)
+
+ return [SearchResult(self, found, searched=searched, tokens_cache=tokens_cache,
+ snippets=(snippets and self.get_snippets(found, query) or None)) for found in top.scoreDocs]
+
+ def search_perfect_book(self, searched, max_results=20, fuzzy=False, hint=None):
+ """
+ Search for perfect book matches. Just see if the query matches with some author or title,
+ taking hints into account.
+ """
+ fields_to_search = ['authors', 'title']
+ only_in = None
+ if hint:
+ if not hint.should_search_for_book():
+ return []
+ fields_to_search = hint.just_search_in(fields_to_search)
+ only_in = hint.book_filter()
+
+ qrys = [self.make_phrase(self.get_tokens(searched, field=fld), field=fld, fuzzy=fuzzy) for fld in fields_to_search]
+
+ books = []
+ for q in qrys:
+ top = self.searcher.search(q,
+ self.chain_filters([only_in, self.term_filter(Term('is_book', 'true'))]),
+ max_results)
+ for found in top.scoreDocs:
+ books.append(SearchResult(self, found, how_found="search_perfect_book"))
+ return books
+
+ def search_book(self, searched, max_results=20, fuzzy=False, hint=None):
+ fields_to_search = ['tags', 'authors', 'title']
+
+ only_in = None
+ if hint:
+ if not hint.should_search_for_book():
+ return []
+ fields_to_search = hint.just_search_in(fields_to_search)
+ only_in = hint.book_filter()
+
+ tokens = self.get_tokens(searched, field='SIMPLE')
+
+ q = BooleanQuery()
+
+ for fld in fields_to_search:
+ q.add(BooleanClause(self.make_term_query(tokens, field=fld,
+ fuzzy=fuzzy), BooleanClause.Occur.SHOULD))
+
+ books = []
+ top = self.searcher.search(q,
+ self.chain_filters([only_in, self.term_filter(Term('is_book', 'true'))]),
+ max_results)
+ for found in top.scoreDocs:
+ books.append(SearchResult(self, found, how_found="search_book"))
+
+ return books
+
+ def search_perfect_parts(self, searched, max_results=20, fuzzy=False, hint=None):
+ """
+ Search for book parts which contains a phrase perfectly matching (with a slop of 2, default for make_phrase())
+ some part/fragment of the book.
+ """
+ qrys = [self.make_phrase(self.get_tokens(searched), field=fld, fuzzy=fuzzy) for fld in ['content']]
+
+ flt = None
+ if hint:
+ flt = hint.part_filter()
+
+ books = []
+ for q in qrys:
+ top = self.searcher.search(q,
+ self.chain_filters([self.term_filter(Term('is_book', 'true'), inverse=True),
+ flt]),
+ max_results)
+ for found in top.scoreDocs:
+ books.append(SearchResult(self, found, snippets=self.get_snippets(found, q), how_found='search_perfect_parts'))
+
+ return books
+
+ def search_everywhere(self, searched, max_results=20, fuzzy=False, hint=None, tokens_cache=None):
+ """
+ Tries to use search terms to match different fields of book (or its parts).
+ E.g. one word can be an author survey, another be a part of the title, and the rest
+ are some words from third chapter.
+ """
+ if tokens_cache is None: tokens_cache = {}
+ books = []
+ only_in = None
+
+ if hint:
+ only_in = hint.part_filter()
+
+ # content only query : themes x content
+ q = BooleanQuery()
+
+ tokens_pl = self.get_tokens(searched, field='content', cached=tokens_cache)
+ tokens = self.get_tokens(searched, field='SIMPLE', cached=tokens_cache)
+
+ # only search in themes when we do not already filter by themes
+ if hint is None or hint.just_search_in(['themes']) != []:
+ q.add(BooleanClause(self.make_term_query(tokens_pl, field='themes_pl',
+ fuzzy=fuzzy), BooleanClause.Occur.MUST))
+
+ q.add(BooleanClause(self.make_term_query(tokens_pl, field='content',
+ fuzzy=fuzzy), BooleanClause.Occur.SHOULD))
+
+ topDocs = self.searcher.search(q, only_in, max_results)
+ for found in topDocs.scoreDocs:
+ books.append(SearchResult(self, found, how_found='search_everywhere_themesXcontent', searched=searched))
+ print "* %s theme x content: %s" % (searched, books[-1]._hits)
+
+ # query themes/content x author/title/tags
+ q = BooleanQuery()
+ in_content = BooleanQuery()
+ in_meta = BooleanQuery()
+
+ for fld in ['themes_pl', 'content']:
+ in_content.add(BooleanClause(self.make_term_query(tokens_pl, field=fld, fuzzy=False), BooleanClause.Occur.SHOULD))
+
+ for fld in ['tags', 'authors', 'title']:
+ in_meta.add(BooleanClause(self.make_term_query(tokens, field=fld, fuzzy=False), BooleanClause.Occur.SHOULD))
+
+ q.add(BooleanClause(in_content, BooleanClause.Occur.MUST))
+ q.add(BooleanClause(in_meta, BooleanClause.Occur.SHOULD))
+
+ topDocs = self.searcher.search(q, only_in, max_results)
+ for found in topDocs.scoreDocs:
+ books.append(SearchResult(self, found, how_found='search_everywhere', searched=searched))
+ print "* %s scatter search: %s" % (searched, books[-1]._hits)
+
+ return books
+
+ # def multisearch(self, query, max_results=50):
+ # """
+ # Search strategy:
+ # - (phrase) OR -> content
+ # -> title
+ # -> authors
+ # - (keywords) -> authors
+ # -> 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 get_snippets(self, scoreDoc, query, field='content'):
+ """
+ Returns a snippet for found scoreDoc.
+ """
+ htmlFormatter = SimpleHTMLFormatter()
+ highlighter = Highlighter(htmlFormatter, QueryScorer(query))
+
+ stored = self.searcher.doc(scoreDoc.doc)
+
+ position = stored.get('snippets_position')
+ length = stored.get('snippets_length')
+ if position is None or length is None:
+ return None
+ # locate content.
+ snippets = Snippets(stored.get('book_id')).open()
+ try:
+ text = snippets.get((int(position),
+ int(length)))
+ finally:
+ snippets.close()
+
+ tokenStream = TokenSources.getAnyTokenStream(self.searcher.getIndexReader(), scoreDoc.doc, field, self.analyzer)
+ # highlighter.getBestTextFragments(tokenStream, text, False, 10)
+ snip = highlighter.getBestFragments(tokenStream, text, 3, "...")
+
+ return snip
+
+ @staticmethod
+ def enum_to_array(enum):
+ """
+ Converts a lucene TermEnum to array of Terms, suitable for
+ addition to queries
+ """
+ terms = []
+
+ while True:
+ t = enum.term()
+ if t:
+ terms.append(t)
+ if not enum.next(): break
+
+ if terms:
+ return JArray('object')(terms, Term)
+
+ def search_tags(self, query, filters=None, max_results=40, pdcounter=False):
+ """
+ Search for Tag objects using query.
+ """
+ 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)
+ 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):
+ """
+ Searches for Book objects using query
+ """
+ bks = []
+ tops = self.searcher.search(query, filter, max_results)
+ 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
+
+ def make_prefix_phrase(self, toks, field):
+ q = MultiPhraseQuery()
+ for i in range(len(toks)):
+ t = Term(field, toks[i])
+ if i == len(toks) - 1:
+ pterms = Search.enum_to_array(PrefixTermEnum(self.searcher.getIndexReader(), t))
+ if pterms:
+ q.add(pterms)
+ else:
+ q.add(t)
+ else:
+ q.add(t)
+ return q
+
+ @staticmethod
+ def term_filter(term, inverse=False):
+ only_term = TermsFilter()
+ only_term.addTerm(term)
+
+ if inverse:
+ neg = BooleanFilter()
+ neg.add(FilterClause(only_term, BooleanClause.Occur.MUST_NOT))
+ only_term = neg
+
+ return only_term
+
+ def hint_tags(self, string, max_results=50, pdcounter=True, prefix=True):
+ """
+ Return auto-complete hints for tags
+ using prefix search.
+ """
+ toks = self.get_tokens(string, field='SIMPLE')
+ top = BooleanQuery()
+
+ for field in ['tag_name', 'tag_name_pl']:
+ 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, pdcounter=pdcounter)
+
+ 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.
+ Prefix search.
+ """
+ toks = self.get_tokens(string, field='SIMPLE')
+
+ 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)
+
+ @staticmethod
+ def chain_filters(filters, op=ChainedFilter.AND):
+ """
+ Chains a filter list together
+ """
+ filters = filter(lambda x: x is not None, filters)
+ if not filters or filters is []:
+ return None
+ chf = ChainedFilter(JArray('object')(filters, Filter), op)
+ return chf
+
+ def filtered_categories(self, tags):
+ """
+ Return a list of tag categories, present in tags list.
+ """
+ cats = {}
+ for t in tags:
+ cats[t.category] = True
+ return cats.keys()
+
+ def hint(self):
+ return Hint(self)
fnp / wolnelektury.git / blobdiff