self.addAnalyzer("source_url", keyword)
self.addAnalyzer("source_name", simple)
self.addAnalyzer("publisher", simple)
- self.addAnalyzer("author", simple)
+ self.addAnalyzer("authors", simple)
+ self.addAnalyzer("title", simple)
+
self.addAnalyzer("is_book", keyword)
# shouldn't the title have two forms? _pl and simple?
class IndexStore(object):
+ """
+ Provides access to search index.
+
+ self.store - lucene index directory
+ """
def __init__(self):
self.make_index_dir()
self.store = SimpleFSDirectory(File(settings.SEARCH_INDEX))
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):
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)
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)
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 Index(IndexStore):
+class BaseIndex(IndexStore):
+ """
+ Base index class.
+ Provides basic operations on index: opening, closing, optimizing.
+ """
def __init__(self, analyzer=None):
- IndexStore.__init__(self)
+ super(BaseIndex, self).__init__()
self.index = None
if not analyzer:
analyzer = WLAnalyzer()
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)
doc.add(Field("tag_category", tag.category, Field.Store.NO, 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(book.id))
+ if book.parent is not None:
+ doc.add(NumericField("parent_id", Field.Store.YES, True).setIntValue(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, overwrite=True):
+ 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)
+ 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:
self.index.addDocument(book_doc)
del book_doc
- self.index_content(book, book_fields=[meta_fields['title'], meta_fields['author']])
+ self.index_content(book, book_fields=[meta_fields['title'], meta_fields['authors']])
master_tags = [
'opowiadanie',
skip_header_tags = ['autor_utworu', 'nazwa_utworu', 'dzielo_nadrzedne']
- def create_book_doc(self, book):
+ def extract_metadata(self, book, book_info=None):
"""
- Create a lucene document connected to the book
+ Extract metadata from book and returns a map of fields keyed by fieldname
"""
- doc = Document()
- doc.add(NumericField("book_id", Field.Store.YES, True).setIntValue(book.id))
- if book.parent is not None:
- doc.add(NumericField("parent_id", Field.Store.YES, True).setIntValue(book.parent.id))
- return doc
-
- def extract_metadata(self, book):
fields = {}
- book_info = dcparser.parse(open(book.xml_file.path))
- print("extract metadata for book %s id=%d, thread%d" % (book.slug, book.id, current_thread().ident))
+ 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')
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)
- return fields
- def get_master(self, root):
- for master in root.iter():
- if master.tag in self.master_tags:
- return master
+ 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=[]):
- wld = WLDocument.from_file(book.xml_file.path)
+ """
+ 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)
return
def fix_format(text):
- return re.sub("/$", "", text, flags=re.M)
+ return re.sub("(?m)/$", "", text)
def add_part(snippets, **fields):
doc = self.create_book_doc(book)
else:
return s
-
fragments = {}
snippets = Snippets(book.id).open('w')
try:
snippets.close()
- def __enter__(self):
- self.open()
- return self
-
- def __exit__(self, type, value, tb):
- self.close()
-
-
def log_exception_wrapper(f):
def _wrap(*a):
try:
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)
+ # 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("wait for indexing to finish")
- for job in ReusableIndex.pool_jobs:
- job.get()
- sys.stdout.write('.')
- sys.stdout.flush()
- print("done.")
- ReusableIndex.pool.close()
-
ReusableIndex.index.optimize()
ReusableIndex.index.close()
ReusableIndex.index = None
pass
-class Search(IndexStore):
- 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):
- return self.parser.parse(query)
+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=[]):
"""
return BlockJoinQuery(query, self.parent_filter,
BlockJoinQuery.ScoreMode.Total)
- def simple_search(self, query, max_results=50):
- """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 search(self, query, max_results=50):
- query = self.query(query)
- query = self.wrapjoins(query, ["content", "themes"])
-
- tops = self.searcher.search(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 bsearch(self, query, max_results=50):
q = self.query(query)
bjq = BlockJoinQuery(q, self.parent_filter, BlockJoinQuery.ScoreMode.Avg)
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, how_found=None, snippets=None):
- self.snippets = []
-
if score:
self.score = score
else:
self.score = scoreDocs.score
- self.hits = []
+ self._hits = []
+ self.hits = None # processed hits
stored = searcher.doc(scoreDocs.doc)
self.book_id = int(stored.get("book_id"))
fragment = stored.get("fragment_anchor")
- hit = (sec + (header_span,), fragment, scoreDocs.score, {'how_found': how_found, 'snippets': snippets})
+ hit = (sec + (header_span,), fragment, scoreDocs.score, {'how_found': how_found, 'snippets': snippets and [snippets] or []})
- self.hits.append(hit)
+ self._hits.append(hit)
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
+ self._hits += other._hits
if other.score > self.score:
self.score = other.score
return self
book = property(get_book)
def process_hits(self):
- frags = filter(lambda r: r[1] is not None, self.hits)
- sect = filter(lambda r: r[1] is None, self.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[0][1] >= f[0][1] and s[0][1] < f[0][1] + f[0][2],
+ 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:
- m = {'score': s[2],
- 'header_index': s[0][1]
+ si = s[POSITION][POSITION_INDEX]
+ # skip existing
+ if si in sections:
+ if sections[si]['score'] >= s[SCORE]:
+ continue
+
+ m = {'score': s[SCORE],
+ 'header_index': s[POSITION][POSITION_INDEX]
}
- m.update(s[3])
- hits.append(m)
+ m.update(s[OTHER])
+ sections[si] = m
+
+ hits = sections.values()
for f in frags:
- frag = catalogue.models.Fragment.objects.get(anchor=f[1])
- m = {'score': f[2],
+ frag = catalogue.models.Fragment.objects.get(anchor=f[FRAGMENT])
+ m = {'score': f[SCORE],
'fragment': frag,
'themes': frag.tags.filter(category='theme')
}
- m.update(f[3])
+ m.update(f[OTHER])
hits.append(m)
hits.sort(lambda a, b: cmp(a['score'], b['score']), reverse=True)
- print("--- %s" % hits)
+ self.hits = hits
- return hits
+ return self
def __unicode__(self):
return u'SearchResult(book_id=%d, score=%d)' % (self.book_id, self.score)
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']:
+ 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:
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)
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 MultiSearch.chain_filters(fs)
-
+
+ return Search.chain_filters(fs)
+
def should_search_for_book(self):
return self._books == []
"""Holds logic to figure out which indexes should be search, when we have some hinst already"""
some = []
for field in all:
- if field == 'author' and 'author' in self.book_tags:
+ if field == 'authors' and 'author' in self.book_tags:
continue
if field == 'title' and self._books != []:
continue
return some
-class MultiSearch(Search):
- """Class capable of IMDb-like searching"""
+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'):
"""returns tokens analyzed by a proper (for a field) analyzer
argument can be: StringReader, string/unicode, or tokens. In the last case
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 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:
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)
# BlockJoinQuery.ScoreMode.Total)
def search_perfect_book(self, searched, max_results=20, fuzzy=False, hint=None):
- fields_to_search = ['author', 'title']
+ """
+ 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():
books = []
for q in qrys:
top = self.searcher.search(q,
- self.chain_filters([only_in, self.term_filter(Term('is_book', 'true'))]),
+ self.chain_filters([only_in, self.term_filter(Term('is_book', 'true'))]),
max_results)
for found in top.scoreDocs:
books.append(SearchResult(self.searcher, found))
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.searcher, found))
+
+ return books
+
def search_perfect_parts(self, searched, max_results=20, fuzzy=False, hint=None):
+ """
+ Search for book parts which containt 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
for q in qrys:
top = self.searcher.search(q,
self.chain_filters([self.term_filter(Term('is_book', 'true'), inverse=True),
- flt
- ]),
+ flt]),
max_results)
for found in top.scoreDocs:
books.append(SearchResult(self.searcher, found, snippets=self.get_snippets(found, q)))
return books
def search_everywhere(self, searched, max_results=20, fuzzy=False, hint=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.
+ """
books = []
only_in = None
# content only query : themes x content
q = BooleanQuery()
- tokens = self.get_tokens(searched)
- if hint is None or hint.just_search_in(['themes_pl']) != []:
- q.add(BooleanClause(self.make_term_query(tokens, field='themes_pl',
+ tokens_pl = self.get_tokens(searched, field='content')
+ tokens = self.get_tokens(searched, field='SIMPLE')
+
+ # 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, field='content',
+ 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.searcher, found))
+ print "* %s theme x content: %s" % (searched, books[-1]._hits)
# query themes/content x author/title/tags
q = BooleanQuery()
- in_meta = 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 ['themes', 'content', 'tags', 'author', 'title']:
- in_content.add(BooleanClause(self.make_term_query(tokens, 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.searcher, found))
+ print "* %s scatter search: %s" % (searched, books[-1]._hits)
return books
-
- def multisearch(self, query, max_results=50):
- """
- Search strategy:
- - (phrase) OR -> content
- -> title
- -> author
- - (keywords) -> author
- -> motyw
- -> tags
- -> content
- """
+ # 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.add(BooleanClause(phrase_level, Should))
# top_level.add(BooleanClause(kw_level, Should))
- return None
+ # return None
- def book_search(self, query, filter=None, max_results=50, collector=None):
- tops = self.searcher.search(query, filter, 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
def get_snippets(self, scoreDoc, query, field='content'):
+ """
+ Returns a snippet for found scoreDoc.
+ """
htmlFormatter = SimpleHTMLFormatter()
highlighter = Highlighter(htmlFormatter, QueryScorer(query))
tokenStream = TokenSources.getAnyTokenStream(self.searcher.getIndexReader(), scoreDoc.doc, field, self.analyzer)
# highlighter.getBestTextFragments(tokenStream, text, False, 10)
- # import pdb; pdb.set_trace()
snip = highlighter.getBestFragments(tokenStream, text, 3, "...")
- return [snip]
+ return snip
@staticmethod
def enum_to_array(enum):
return JArray('object')(terms, Term)
def search_tags(self, query, filter=None, max_results=40):
+ """
+ Search for Tag objects using query.
+ """
tops = self.searcher.search(query, filter, max_results)
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:
for i in range(len(toks)):
t = Term(field, toks[i])
if i == len(toks) - 1:
- pterms = MultiSearch.enum_to_array(PrefixTermEnum(self.searcher.getIndexReader(), t))
+ pterms = Search.enum_to_array(PrefixTermEnum(self.searcher.getIndexReader(), t))
if pterms:
q.add(pterms)
else:
return only_term
def hint_tags(self, string, max_results=50):
+ """
+ Return auto-complete hints for tags
+ using prefix search.
+ """
toks = self.get_tokens(string, field='SIMPLE')
top = BooleanQuery()
return self.search_tags(top, no_book_cat, max_results=max_results)
def hint_books(self, string, max_results=50):
+ """
+ Returns auto-complete hints for book titles
+ Because we do not index 'pseudo' title-tags.
+ Prefix search.
+ """
toks = self.get_tokens(string, field='SIMPLE')
q = self.create_prefix_phrase(toks, 'title')
- return self.book_search(q, self.term_filter(Term("is_book", "true")), max_results=max_results)
+ 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:
return None
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
fnp / wolnelektury.git / blobdiff